running first DSL fit and trying to poke at FELM issue

dsl/dsl.R

@@ -4,51 +4,69 @@ library(dsl)
 dsl_csv <-"111725_DSL_frame.csv"
 dsl_df <- read.csv(dsl_csv, header = TRUE) 
 
-
-power_model <- power_dsl(
-  labeled_size = c(100, 200, 300, 600, 1000),
+base_model <- dsl(
   model = "logit", 
-  formula = dsl_score ~ human_SOL_prop_adac + 
-    median_gerrit_loc_delta + median_gerrit_reviewers + 
-    as.factor(isAuthorWMF) + 
-    as.factor(source) +
-    median_PC3_adac +
-    week_index,
-  predicted_var = "human_SOL_prop_adac",
-  prediction = "olmo_SOL_prop_adac",
+  formula = dsl_score ~ human_EP_prop_adac,
+  predicted_var = "human_EP_prop_adac",
+  prediction = "olmo_EP_prop_adac",
   sample_prob = "sampling_prob",
   data=dsl_df
 )
-summary(power_model)
-plot(power_model, coef_name = "human_SOL_prop_adac")
+summary(base_model)
 
+case_model <- dsl(
+  model = "logit", 
+  formula = dsl_score ~ human_EP_prop_adac + as.factor(source),
+  predicted_var = "human_EP_prop_adac",
+  prediction = "olmo_EP_prop_adac",
+  sample_prob = "sampling_prob",
+  data=dsl_df
+)
+summary(case_model)
 
 trial_model <- dsl(
   model = "logit", 
-  formula = dsl_score ~ human_TSOL_prop_adac + 
-    median_gerrit_loc_delta + median_gerrit_reviewers + 
-    as.factor(isAuthorWMF) + 
-    as.factor(author_closer) + 
-    median_PC4_adac +
-    week_index + n_comments_before,
-  predicted_var = "human_TSOL_prop_adac",
-  prediction = "olmo_TSOL_prop_adac",
+  formula = dsl_score ~ human_EP_prop_adac + human_TSOL_prop_adac + human_RK_prop_adac 
+    + as.factor(source) + week_index + as.factor(isAuthorWMF) + median_PC4_adac + n_comments_before,
+  predicted_var = c("human_EP_prop_adac", "human_TSOL_prop_adac", "human_RK_prop_adac"),
+  prediction = c("olmo_EP_prop_adac", "olmo_TSOL_prop_adac", "olmo_RK_prop_adac"),
   sample_prob = "sampling_prob",
   data=dsl_df
 )
 summary(trial_model)
 
-style_model <- dsl(
-  model = "lm", 
-  formula = human_BE_prop ~ 
-    median_PC1 + median_PC4 + 
-    as.factor(isAuthorWMF) + 
-    as.factor(author_closer) + 
-    median_PC3 +
-    week_index,
-  predicted_var = "human_BE_prop",
-  prediction = "olmo_BE_prop",
+anova(dsl_df$olmo_RK_prop, dsl_df$median_gerrit_reviewers)
+chisq.test(table(dsl_df$isAuthorWMF, dsl_df$author_closer))
+
+c1_df <- dsl_df |>
+  dplyr::filter(source=="c1")
+
+felm_model <- dsl(
+  model = "felm", 
+  formula = TTR ~ human_EP_prop_adac + human_TSOL_prop_adac + human_RK_prop_adac 
+  + week_index + as.factor(isAuthorWMF) + median_PC4_adac + n_comments_before,
+  predicted_var = c("human_EP_prop_adac", "human_TSOL_prop_adac", "human_RK_prop_adac"),
+  prediction = c("olmo_EP_prop_adac", "olmo_TSOL_prop_adac", "olmo_RK_prop_adac"),
   sample_prob = "sampling_prob",
+  fixed_effect = "oneway",
+  index = c("source"),
+  cluster="source",
   data=dsl_df
 )
-summary(style_model)
+summary(felm_model)
+
+#https://github.com/naoki-egami/dsl/blob/537664a54163dda52ee277071fdfd9e8df2572a6/R/estimate_g.R#L39
+felm_df <- dsl_df |>
+  dplyr::mutate(ttr_days = TTR / 24)
+felm_model <- dsl(
+  model = "felm", 
+  formula = ttr_days ~ human_EP_prop_adac,
+  predicted_var = c("human_EP_prop_adac"),
+  prediction = c("olmo_EP_prop_adac"),
+  sample_prob = "sampling_prob",
+  fixed_effect = "oneway",
+  index = c("phase"),
+  cluster="phase",
+  data=felm_df
+)
+summary(felm_model)

mgaughan-rstudio-server_31035935.out

@@ -1,17 +0,0 @@
-1. SSH tunnel from your workstation using the following command:
-
-   ssh -N -L 8787:n3439:35765 mjilg@klone.hyak.uw.edu
-
-   and point your web browser to http://localhost:8787
-
-2. log in to RStudio Server using the following credentials:
-
-   user: mjilg
-   password: QKOjN5O9o8KE4QlK+t4M
-
-When done using RStudio Server, terminate the job by:
-
-1. Exit the RStudio Session ("power" button in the top right corner of the RStudio window)
-2. Issue the following command on the login node:
-
-      scancel -f 31035935