scaled variables for poisson
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mjgaughan
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R/.Rhistory
858
R/.Rhistory
@ -1,313 +1,367 @@
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window_num <- 10
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longer <- longer %>%
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filter(week >= (26 - window_num) & week <= (26 + window_num))
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#testing out analysis below
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longer[which(longer$observation_type == "all"),] |>
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ggplot(aes(x = week, y = count)) +
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geom_point() +
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geom_vline(xintercept = 26)
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longer[which(longer$observation_type == "all"),] |>
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mutate(D = ifelse(week >= 26, 1, 0)) |>
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lm(formula = count ~ D * I(week - 26)) |>
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summary()
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longer[which(longer$observation_type == "all"),] |>
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select(count, week) |>
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mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
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ggplot(aes(x = week, y = count, color = D)) +
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geom_point() +
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geom_smooth(se = FALSE) +
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geom_vline(xintercept = 26)
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
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# }
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# test_two
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#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
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# https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
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new_test <- readme_df[697,]
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longer <- new_test |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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window_num <- 27
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longer <- longer %>%
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filter(week >= (26 - window_num) & week <= (26 + window_num))
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#testing out analysis below
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longer[which(longer$observation_type == "all"),] |>
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ggplot(aes(x = week, y = count)) +
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geom_point() +
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geom_vline(xintercept = 26)
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longer[which(longer$observation_type == "all"),] |>
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mutate(D = ifelse(week >= 26, 1, 0)) |>
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lm(formula = count ~ D * I(week - 26)) |>
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summary()
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longer[which(longer$observation_type == "all"),] |>
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select(count, week) |>
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mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
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ggplot(aes(x = week, y = count, color = D)) +
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geom_point() +
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geom_smooth(se = FALSE) +
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geom_vline(xintercept = 26)
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window_num <- 13
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longer <- longer %>%
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filter(week >= (26 - window_num) & week <= (26 + window_num))
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#testing out analysis below
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longer[which(longer$observation_type == "all"),] |>
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ggplot(aes(x = week, y = count)) +
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geom_point() +
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geom_vline(xintercept = 26)
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longer[which(longer$observation_type == "all"),] |>
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mutate(D = ifelse(week >= 26, 1, 0)) |>
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lm(formula = count ~ D * I(week - 26)) |>
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summary()
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longer[which(longer$observation_type == "all"),] |>
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select(count, week) |>
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mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
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ggplot(aes(x = week, y = count, color = D)) +
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geom_point() +
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geom_smooth(se = FALSE) +
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geom_vline(xintercept = 26)
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longer[which(longer$observation_type == "all"),] |>
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select(count, week) |>
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mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
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ggplot(aes(x = week, y = count, color = D)) +
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geom_point() +
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geom_smooth(se = TRUE) +
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geom_vline(xintercept = 26)
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#testing out analysis below
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longer[which(longer$observation_type == "all"),] |>
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ggplot(aes(x = week, y = count)) +
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geom_point() +
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geom_vline(xintercept = 25.5)
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longer[which(longer$observation_type == "all"),] |>
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mutate(D = ifelse(week >= 26, 1, 0)) |>
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lm(formula = count ~ D * I(week - 26)) |>
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summary()
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longer[which(longer$observation_type == "all"),] |>
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select(count, week) |>
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mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
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ggplot(aes(x = week, y = count, color = D)) +
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geom_point() +
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geom_smooth(se = TRUE) +
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geom_vline(xintercept = 25.5)
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#testing out analysis below
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longer[which(longer$observation_type == "all"),] |>
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ggplot(aes(x = week, y = count)) +
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geom_point() +
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geom_vline(xintercept = 26)
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longer[which(longer$observation_type == "all"),] |>
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mutate(D = ifelse(week >= 26, 1, 0)) |>
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lm(formula = count ~ D * I(week - 26)) |>
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summary()
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longer[which(longer$observation_type == "all"),] |>
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select(count, week) |>
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mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
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ggplot(aes(x = week, y = count, color = D)) +
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geom_point() +
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geom_smooth(se = TRUE) +
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geom_vline(xintercept = 26)
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library(rdd-package)
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library(rdd)
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library(rdd)
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
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# }
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# test_two
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#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
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# https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
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new_test <- readme_df[697,]
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longer <- new_test |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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#longer <- longer %>%
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# filter(week >= (26 - window_num) & week <= (26 + window_num))
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IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
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#testing out analysis below
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longer[which(longer$observation_type == "all"),] |>
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ggplot(aes(x = week, y = count)) +
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geom_point() +
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geom_vline(xintercept = 26)
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longer[which(longer$observation_type == "all"),] |>
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mutate(D = ifelse(week >= 26, 1, 0)) |>
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lm(formula = count ~ D * I(week - 26)) |>
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summary()
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longer[which(longer$observation_type == "all"),] |>
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select(count, week) |>
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mutate(D = as.factor(ifelse(week >= 26, 1, 0))) |>
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ggplot(aes(x = week, y = count, color = D)) +
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geom_point() +
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geom_smooth(se = TRUE) +
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geom_vline(xintercept = 26)
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
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# }
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# test_two
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#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
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# https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
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new_test <- readme_df[0,]
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longer <- new_test |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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#longer <- longer %>%
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# filter(week >= (26 - window_num) & week <= (26 + window_num))
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IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
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# }
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# test_two
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#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
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# https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
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new_test <- readme_df[3,]
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longer <- new_test |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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#longer <- longer %>%
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# filter(week >= (26 - window_num) & week <= (26 + window_num))
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IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
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# test_two <- c()
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# iterator <- 0
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# for (entry in test) {
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# readme_df$cnt_before_all[iterator] <- as.numeric(unlist(entry))
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# print(as.numeric(unlist(entry)))
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# iterator <- iterator + 1
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# }
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# test_two
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#Yes, need to expand the dataframe, but again, for the sake of clarity, do not want to until analysis step
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# https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
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new_test <- readme_df[9,]
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longer <- new_test |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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#longer <- longer %>%
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# filter(week >= (26 - window_num) & week <= (26 + window_num))
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IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
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get_optimal_window <- function(project_row) {
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longer <- project_row |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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optimal_bandwidth <- IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
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return(optimal_bandwidth)
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link <- readme_df[i,]$upstream_vcs_link
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age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
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project <- full_df$project_name[full_df$upstream_vcs_link == link]
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ages <- c(ages, age)
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if (length(project) != 1){
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project
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break
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} else {
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projects <- c(projects, project)
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}
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bandwidths <- c()
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}
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#set wd, read in data
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
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full_df <- read_csv("../final_data/deb_full_data.csv")
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#preprocessing for readme_df
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colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
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col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
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ages <- c()
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projects <- c()
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for (i in 1:nrow(readme_df)){
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bandwidths <- c(bandwidths, get_optimal_window(readme_df[i,]))
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link <- readme_df[i,]$upstream_vcs_link
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age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
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project <- full_df$project_name[full_df$upstream_vcs_link == link]
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ages <- c(ages, age)
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if (length(project) != 1){
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project
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break
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} else {
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projects <- c(projects, project)
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}
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bandwidths
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mean(bandwidths)
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median(bandwidths)
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get_optimal_window <- function(project_row) {
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longer <- project_row |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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longer <- longer[which(longer$observation_type == "all"),]
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optimal_bandwidth <- IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
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return(optimal_bandwidth)
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}
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bandwidths <- c()
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#set wd, read in data
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
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full_df <- read_csv("../final_data/deb_full_data.csv")
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#preprocessing for readme_df
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colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
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col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
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ages <- c()
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projects <- c()
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for (i in 1:nrow(readme_df)){
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bandwidths <- c(bandwidths, get_optimal_window(readme_df[i,]))
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link <- readme_df[i,]$upstream_vcs_link
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age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
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project <- full_df$project_name[full_df$upstream_vcs_link == link]
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ages <- c(ages, age)
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if (length(project) != 1){
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project
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break
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} else {
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projects <- c(projects, project)
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}
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mean(bandwidths)
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median(bandwidths)
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bandwidths <- c()
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}
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#set wd, read in data
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
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full_df <- read_csv("../final_data/deb_full_data.csv")
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#preprocessing for readme_df
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colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
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col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
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ages <- c()
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projects <- c()
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for (i in 1:nrow(readme_df)){
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bandwidth <- get_optimal_window(readme_df[i,])
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bandwidths <- c(bandwidths, bandwidth)
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link <- readme_df[i,]$upstream_vcs_link
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age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
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project <- full_df$project_name[full_df$upstream_vcs_link == link]
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ages <- c(ages, age)
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if (length(project) != 1){
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project
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break
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} else {
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projects <- c(projects, project)
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}
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mean(bandwidths)
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median(bandwidths)
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get_optimal_window <- function(project_row) {
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longer <- project_row |>
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pivot_longer(cols = starts_with("ct"),
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names_to = "window",
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values_to = "count") |>
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unnest(count)
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longer$observation_type <- gsub("^.*_", "", longer$window)
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longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
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longer$count <- as.numeric(longer$count)
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#this below line makes the code specific to the all-commits data
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longer <- longer[which(longer$observation_type == "all"),]
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result <- tryCatch({
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optimal_bandwidth <- IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
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return(optimal_bandwidth)
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}, error = function(e){
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return(8)
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})
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}
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bandwidths <- c()
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
bandwidth <- get_optimal_window(readme_df[i,])
|
||||
bandwidths <- c(bandwidths, bandwidth)
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
mean(bandwidths)
|
||||
median(bandwidths)
|
||||
mode(bandwidths)
|
||||
table(bandwidths)
|
||||
mean(bandwidths) #
|
||||
median(bandwidths)
|
||||
# this is the file with the lmer multi-level rddAnalysis
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
length(ages)
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
length(ages)
|
||||
readme_df$age_of_project = full_df$age_of_project[full_df$upstream_vcs_link == readme_df$upstream_vcs_link]
|
||||
View(readme_df)
|
||||
readme_df$age_of_project = ages
|
||||
View(readme_df)
|
||||
write.csv(readme_df, "deb_readme_data_4_19.csv", row.names=FALSE)
|
||||
#preprocessing for readme_df
|
||||
colnames(contributing_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(contributing_df)){
|
||||
link <- readme_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
contributing_df$age_of_project = ages
|
||||
write.csv(contributing_df, "deb_contributing_data_4_19.csv", row.names=FALSE)
|
||||
View(contributing_df)
|
||||
View(contributing_df)
|
||||
View(readme_df)
|
||||
View(contributing_df)
|
||||
View(contributing_df)
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
View(contributing_df)
|
||||
#preprocessing for readme_df
|
||||
colnames(contributing_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(contributing_df)){
|
||||
link <- contributing_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(contributing_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(contributing_df)){
|
||||
link <- contributing_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
#set wd, read in data
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contributing_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
full_df <- read_csv("../final_data/deb_full_data.csv")
|
||||
#preprocessing for readme_df
|
||||
colnames(contributing_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
ages <- c()
|
||||
projects <- c()
|
||||
for (i in 1:nrow(contributing_df)){
|
||||
link <- contributing_df[i,]$upstream_vcs_link
|
||||
age <- full_df$age_of_project[full_df$upstream_vcs_link == link]
|
||||
project <- full_df$project_name[full_df$upstream_vcs_link == link]
|
||||
ages <- c(ages, age)
|
||||
if (length(project) != 1){
|
||||
project
|
||||
break
|
||||
} else {
|
||||
projects <- c(projects, project)
|
||||
}
|
||||
}
|
||||
contributing_df$age_of_project = ages
|
||||
write.csv(contributing_df, "deb_contributing_data_4_19.csv", row.names=FALSE)
|
||||
# 0 loading the readme data in
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
# 0 loading the readme data in
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
View(readme_df)
|
||||
# 1 preprocessing
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
#colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "age_of_project", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
readme_df <- readme_df[,col_order]
|
||||
readme_df$ct_before_all <- str_split(gsub("[][]","", readme_df$before_all_ct), ", ")
|
||||
View(readme_df)
|
||||
View(readme_df)
|
||||
readme_df$ct_after_all <- str_split(gsub("[][]","", readme_df$after_all_ct), ", ")
|
||||
readme_df$ct_before_mrg <- str_split(gsub("[][]","", readme_df$before_mrg_ct), ", ")
|
||||
readme_df$ct_after_mrg <- str_split(gsub("[][]","", readme_df$after_mrg_ct), ", ")
|
||||
drop <- c("before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct")
|
||||
readme_df = readme_df[,!(names(readme_df) %in% drop)]
|
||||
View(readme_df)
|
||||
# 2 some expansion needs to happens for each project
|
||||
expand_timeseries <- function(project_row) {
|
||||
longer <- project_row |>
|
||||
@ -326,131 +380,6 @@ for (i in 2:nrow(readme_df)){
|
||||
expanded_data <- rbind(expanded_data, expand_timeseries(readme_df[i,]))
|
||||
}
|
||||
View(expanded_data)
|
||||
View(expanded_data)
|
||||
View(expanded_data)
|
||||
View(expanded_data)
|
||||
View(expanded_data)
|
||||
get_optimal_window <- function(project_row) {
|
||||
longer <- project_row |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
longer$count <- as.numeric(longer$count)
|
||||
#this below line makes the code specific to the all-commits data
|
||||
longer <- longer[which(longer$observation_type == "all"),]
|
||||
result <- tryCatch({
|
||||
#Imbens-Kalyanaraman Optimal Bandwidth Calculation
|
||||
optimal_bandwidth <- IKbandwidth(longer$week, longer$count, cutpoint = 26, verbose = FALSE, kernel = "triangular")
|
||||
return(optimal_bandwidth)
|
||||
}, error = function(e){
|
||||
return(9)
|
||||
})
|
||||
}
|
||||
#this just gets the optimal bandwith window for each project and then appends to lists
|
||||
bandwidths <- c()
|
||||
for (i in 1:nrow(readme_df)){
|
||||
bandwidth <- get_optimal_window(readme_df[i,])
|
||||
bandwidths <- c(bandwidths, bandwidth)
|
||||
}
|
||||
mean(bandwidths) #8.574233
|
||||
median(bandwidths) #8.363088
|
||||
table(bandwidths)
|
||||
#filter out the timewindows
|
||||
window_num <- 8
|
||||
expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num))
|
||||
expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num))
|
||||
# 3 rdd in lmer analysis
|
||||
library(lme4)
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + upstream_vcs_link, data=expanded_data[which(longer$observation_type == "all"),])
|
||||
expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num)) |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0))
|
||||
# 3 rdd in lmer analysis
|
||||
library(lme4)
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + upstream_vcs_link, data=expanded_data[which(longer$observation_type == "all"),])
|
||||
summary(draft_model)
|
||||
View(expanded_data)
|
||||
#filter out the timewindows
|
||||
window_num <- 8
|
||||
expanded_data <- expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num)) |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0))
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + upstream_vcs_link, data=expanded_data[which(longer$observation_type == "all"),])
|
||||
summary(draft_model)
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + upstream_vcs_link, REML=FALSE, data=expanded_data[which(longer$observation_type == "all"),])
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + upstream_vcs_link, REML=FALSE, data=expanded_data[which(longer$observation_type == "all"),])
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=expanded_data[which(longer$observation_type == "all"),])
|
||||
summary(draft_model)
|
||||
# this is the file with the lmer multi-level rddAnalysis
|
||||
# 0 loading the readme data in
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
# this is the file with the lmer multi-level rddAnalysis
|
||||
library(tidyverse)
|
||||
# 0 loading the readme data in
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
# 1 preprocessing
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
readme_df <- readme_df[,col_order]
|
||||
readme_df$ct_before_all <- str_split(gsub("[][]","", readme_df$before_all_ct), ", ")
|
||||
readme_df$ct_after_all <- str_split(gsub("[][]","", readme_df$after_all_ct), ", ")
|
||||
readme_df$ct_before_mrg <- str_split(gsub("[][]","", readme_df$before_mrg_ct), ", ")
|
||||
readme_df$ct_after_mrg <- str_split(gsub("[][]","", readme_df$after_mrg_ct), ", ")
|
||||
drop <- c("before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct")
|
||||
readme_df = readme_df[,!(names(readme_df) %in% drop)]
|
||||
# 2 some expansion needs to happens for each project
|
||||
expand_timeseries <- function(project_row) {
|
||||
longer <- project_row |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
longer$count <- as.numeric(longer$count)
|
||||
#longer <- longer[which(longer$observation_type == "all"),]
|
||||
return(longer)
|
||||
}
|
||||
expanded_data <- expand_timeseries(readme_df[1,])
|
||||
for (i in 2:nrow(readme_df)){
|
||||
expanded_data <- rbind(expanded_data, expand_timeseries(readme_df[i,]))
|
||||
}
|
||||
library(plyr)
|
||||
# 2 some expansion needs to happens for each project
|
||||
expand_timeseries <- function(project_row) {
|
||||
longer <- project_row |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
longer$count <- as.numeric(longer$count)
|
||||
#longer <- longer[which(longer$observation_type == "all"),]
|
||||
return(longer)
|
||||
}
|
||||
expanded_data <- expand_timeseries(readme_df[1,])
|
||||
for (i in 2:nrow(readme_df)){
|
||||
expanded_data <- rbind(expanded_data, expand_timeseries(readme_df[i,]))
|
||||
}
|
||||
#filter out the timewindows
|
||||
window_num <- 8
|
||||
expanded_data <- expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num)) |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0))
|
||||
# 3 rdd in lmer analysis
|
||||
library(lme4)
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + (1|as.factor(upstream_vcs_link)), REML=FALSE, data=expanded_data[which(longer$observation_type == "all"),])
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + (1|as.factor(upstream_vcs_link)), REML=FALSE, data=expanded_data[which(expanded_data$observation_type == "all"),])
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=expanded_data[which(expanded_data$observation_type == "all"),])
|
||||
summary(draft_model)
|
||||
# this is the file with the lmer multi-level rddAnalysis
|
||||
library(tidyverse)
|
||||
library(plyr)
|
||||
@ -458,8 +387,8 @@ library(plyr)
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
# 1 preprocessing
|
||||
colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
#colnames(readme_df) <- c("upstream_vcs_link", "event_date", "event_hash", "before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct", "before_auth_new", "after_commit_new", "after_auth_new", "before_commit_new")
|
||||
col_order <- c("upstream_vcs_link", "age_of_project", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
readme_df <- readme_df[,col_order]
|
||||
readme_df$ct_before_all <- str_split(gsub("[][]","", readme_df$before_all_ct), ", ")
|
||||
readme_df$ct_after_all <- str_split(gsub("[][]","", readme_df$after_all_ct), ", ")
|
||||
@ -484,29 +413,100 @@ expanded_data <- expand_timeseries(readme_df[1,])
|
||||
for (i in 2:nrow(readme_df)){
|
||||
expanded_data <- rbind(expanded_data, expand_timeseries(readme_df[i,]))
|
||||
}
|
||||
#filter out the timewindows
|
||||
#filter out the windows of time that we're looking at
|
||||
window_num <- 8
|
||||
expanded_data <- expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num)) |>
|
||||
mutate(D = ifelse(week >= 26, 1, 0))
|
||||
# 3 rdd in lmer analysis
|
||||
library(lme4)
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=expanded_data[which(expanded_data$observation_type == "all"),])
|
||||
summary(draft_model)
|
||||
expanded_data <- expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num)) |>
|
||||
mutate(D = ifelse(week > 26, 1, 0))
|
||||
#separate out the cleaning
|
||||
all_actions_data <- expanded_data[which(expanded_data$observation_type == "all"),]
|
||||
mrg_actions_data <- expanded_data[which(expanded_data$observation_type == "mrg"),]
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
# 3 rdd in lmer analysis
|
||||
# rdd: https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
|
||||
# lmer: https://www.youtube.com/watch?v=LzAwEKrn2Mc
|
||||
library(lme4)
|
||||
draft_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=expanded_data[which(expanded_data$observation_type == "all"),])
|
||||
summary(draft_model)
|
||||
View(expanded_data)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=expanded_data[which(expanded_data$observation_type == "all"),])
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_mrg_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=expanded_data[which(expanded_data$observation_type == "mrg"),])
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1|upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
ICC(outcome="count", group="upstream_vcs_link", data=all_actions_data)
|
||||
# need to calculate inter-class correlation coefficient?
|
||||
library(merTools)
|
||||
ICC(outcome="count", group="upstream_vcs_link", data=all_actions_data)
|
||||
ICC(outcome="count", group="week", data=all_actions_data)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + D * I(week - 26) + age_of_project |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
describe(all_actions_data)
|
||||
hist(all_actions_data$count)
|
||||
mean(all_actions_data$count)
|
||||
median(all_actions_data$count)
|
||||
mean(all_actions_data$count)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1+week|upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1+D * I(week - 26)|upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1+ upstream_vcs_link|upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
draft_all_model <- lmer(count ~ (1 | D * I(week - 26) + age_of_project) + (1 |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + I(week - 26) |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + week |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + I(week - 26) |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
draft_mrg_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=mrg_actions_data)
|
||||
summary(draft_mrg_model)
|
||||
draft_all_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=TRUE, data=expanded_data[which(expanded_data$observation_type == "all"),])
|
||||
draft_all_model <- lmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
flat_all_model <- lmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project, REML=FALSE, data=all_actions_data)
|
||||
flat_all_model <- lm(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project, REML=FALSE, data=all_actions_data)
|
||||
summary(flat_all_model)
|
||||
draft_all_model <- lmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(draft_all_model)
|
||||
#find some EDA to identify which types of models might be the best for this
|
||||
mean(all_actions_data$count)
|
||||
median(all_actions_data$count)
|
||||
table(all_actions_data$count)
|
||||
dist(all_actions_data$count)
|
||||
var(all_actions_data$count)
|
||||
sd(all_actions_data$count)
|
||||
qqplot(all_actions_data$count, all_actions_data$week)
|
||||
qqnorm(all_actions_data$count)
|
||||
y <- qunif(ppoints(length(all_actions_data$count)))
|
||||
qqplot(all_actions_data$count, y)
|
||||
qqnorm(all_actions_data$count)
|
||||
qqnorm(log(all_actions_data$count)
|
||||
qqnorm(log(all_actions_data$count))
|
||||
qqnorm(log(all_actions_data$count))
|
||||
qqplot(log(all_actions_data$count), y)
|
||||
qqnorm(all_actions_data$count)
|
||||
qqnorm(root(all_actions_data$count))
|
||||
qqnorm(log(all_actions_data$count))
|
||||
qqplot(log(all_actions_data$count), y)
|
||||
qqplot(all_actions_data$count, y)
|
||||
poisson_all_model <- glmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), data=all_actions_data, family = poisson(link = "log"))
|
||||
summary(poisson_all_model)
|
||||
summary(draft_all_model)
|
||||
# Performance:
|
||||
draft_mrg_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=mrg_actions_data)
|
||||
summary(draft_mrg_model)
|
||||
lmer_residuals <- residuals(lmer_all_model)
|
||||
lmer_all_model <- lmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(lmer_all_model)
|
||||
lmer_residuals <- residuals(lmer_all_model)
|
||||
qqnorm(lmer_residuals)
|
||||
poisson_residuals <- residuals(poisson_all_model)
|
||||
qqnorm(poisson_residuals)
|
||||
summary(poisson_all_model)
|
||||
#if I'm reading the residuals right, the poisson is better?
|
||||
poisson_all_model <- glmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), data=all_actions_data, family = poisson(link = "log"), nAGQ = 100)
|
||||
summary(poisson_all_model)
|
||||
poisson_residuals <- residuals(poisson_all_model)
|
||||
qqnorm(poisson_residuals)
|
||||
|
||||
@ -36,6 +36,8 @@ window_num <- 8
|
||||
expanded_data <- expanded_data |>
|
||||
filter(week >= (26 - window_num) & week <= (26 + window_num)) |>
|
||||
mutate(D = ifelse(week > 26, 1, 0))
|
||||
#scale the age numbers
|
||||
expanded_data$scaled_project_age <- scale(expanded_data$age_of_project)
|
||||
#separate out the cleaning d
|
||||
all_actions_data <- expanded_data[which(expanded_data$observation_type == "all"),]
|
||||
mrg_actions_data <- expanded_data[which(expanded_data$observation_type == "mrg"),]
|
||||
@ -51,19 +53,19 @@ qqplot(all_actions_data$count, y)
|
||||
# rdd: https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
|
||||
# lmer: https://www.youtube.com/watch?v=LzAwEKrn2Mc
|
||||
library(lme4)
|
||||
flat_all_model <- lm(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project, REML=FALSE, data=all_actions_data)
|
||||
flat_all_model <- lm(count ~ D + I(week - 26) + D:I(week - 26) + scaled_project_age, REML=FALSE, data=all_actions_data)
|
||||
summary(flat_all_model)
|
||||
lmer_all_model <- lmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
lmer_all_model <- lmer(count ~ D + I(week - 26) + D:I(week - 26) + scaled_project_age + (1 + D |upstream_vcs_link), REML=FALSE, data=all_actions_data)
|
||||
summary(lmer_all_model)
|
||||
lmer_residuals <- residuals(lmer_all_model)
|
||||
qqnorm(lmer_residuals)
|
||||
#if I'm reading the residuals right, the poisson is better?
|
||||
poisson_all_model <- glmer(count ~ D + I(week - 26) + D:I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), data=all_actions_data, family = poisson(link = "log"), nAGQ = 100)
|
||||
poisson_all_model <- glmer(count ~ D + I(week - 26) + D:I(week - 26) + scaled_project_age + (1 + D |upstream_vcs_link), data=all_actions_data, family = poisson(link = "log"))
|
||||
summary(poisson_all_model)
|
||||
poisson_residuals <- residuals(poisson_all_model)
|
||||
qqnorm(poisson_residuals)
|
||||
# Performance:
|
||||
draft_mrg_model <- lmer(count ~ D * I(week - 26) + age_of_project + (1 + D |upstream_vcs_link), REML=FALSE, data=mrg_actions_data)
|
||||
draft_mrg_model <- lmer(count ~ D * I(week - 26) + scaled_project_age + (1 + D |upstream_vcs_link), REML=FALSE, data=mrg_actions_data)
|
||||
summary(draft_mrg_model)
|
||||
# Performance:
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user