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added random slope

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mjgaughan 2024-04-19 16:04:06 -05:00
parent f9a385b0f5
commit 1dc38fbad9
2 changed files with 9 additions and 8 deletions
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16
R/didAnalysis.R
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@ -5,8 +5,8 @@ library(plyr)
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path))) try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
readme_df <- read_csv("../final_data/deb_readme_did.csv") readme_df <- read_csv("../final_data/deb_readme_did.csv")
# 1 preprocessing # 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") #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") 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 <- readme_df[,col_order]
readme_df$ct_before_all <- str_split(gsub("[][]","", readme_df$before_all_ct), ", ") 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$ct_after_all <- str_split(gsub("[][]","", readme_df$after_all_ct), ", ")
@ -36,19 +36,21 @@ window_num <- 8
expanded_data <- expanded_data |> expanded_data <- expanded_data |>
filter(week >= (26 - window_num) & week <= (26 + window_num)) |> filter(week >= (26 - window_num) & week <= (26 + window_num)) |>
mutate(D = ifelse(week > 26, 1, 0)) mutate(D = ifelse(week > 26, 1, 0))
#separate out the cleaning #separate out the cleaning d
all_actions_data <- expanded_data[which(expanded_data$observation_type == "all"),] all_actions_data <- expanded_data[which(expanded_data$observation_type == "all"),]
mean(all_actions_data$count)
mrg_actions_data <- expanded_data[which(expanded_data$observation_type == "mrg"),] mrg_actions_data <- expanded_data[which(expanded_data$observation_type == "mrg"),]
# 3 rdd in lmer analysis # 3 rdd in lmer analysis
# rdd: https://rpubs.com/phle/r_tutorial_regression_discontinuity_design # rdd: https://rpubs.com/phle/r_tutorial_regression_discontinuity_design
# lmer: https://www.youtube.com/watch?v=LzAwEKrn2Mc # lmer: https://www.youtube.com/watch?v=LzAwEKrn2Mc
library(lme4) library(lme4)
draft_all_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=all_actions_data) 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) summary(draft_all_model)
draft_mrg_model <- lmer(count ~ D * I(week - 26) + (1|upstream_vcs_link), REML=FALSE, data=mrg_actions_data) 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) summary(draft_mrg_model)
# need to calculate inter-class correlation coefficient? # need to calculate inter-class correlation coefficient?
library(merTools) library(merTools)
ICC(outcome="count", group="upstream_vcs_link", data=all_actions_data) ICC(outcome="count", group="week", data=all_actions_data)
#testing for different types of models #testing for different types of models
# anova # BIC
library(flexmix)

1
final_data/.~lock.deb_full_data.csv#
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@ -1 +0,0 @@
Matt Gaughan,mgone,dhcp-10-105-58-199.wireless.northwestern.private,19.04.2024 14:27,file:///Users/mgone/Library/Application%20Support/OpenOffice/4;