diff --git a/R/final_models/0623_pop_rm_collab_better.rda b/R/final_models/0623_pop_rm_collab_better.rda
new file mode 100644
index 0000000..3fa0f96
Binary files /dev/null and b/R/final_models/0623_pop_rm_collab_better.rda differ
diff --git a/R/popRDDAnalyssis.R b/R/popRDDAnalyssis.R
index 69de691..de104ac 100644
--- a/R/popRDDAnalyssis.R
+++ b/R/popRDDAnalyssis.R
@@ -3,8 +3,26 @@ library(plyr)
 library(stringr)
 try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
 #load in data
+full_df <- read_csv("../final_data/deb_full_data.csv")
 contrib_df <- read_csv("../final_data/deb_contrib_pop_change.csv")
 readme_df <- read_csv("../final_data/deb_readme_pop_change.csv")
+contrib_df <- merge(full_df, contrib_df, by="upstream_vcs_link")
+readme_df <- merge(full_df, readme_df, by="upstream_vcs_link")
+# age is calculated against December 11, 2023
+contrib_df <- contrib_df |>
+  mutate(start_date = as.Date("2023-12-11") - age_of_project) |>
+  mutate(event_date_days = 
+           as.numeric(
+             difftime(as.POSIXct("2024-06-24 00:00:00", format = "%Y-%m-%d %H:%M:%S"),
+                     as.POSIXct(event_date, format = "%Y-%m-%d %H:%M:%S"), 
+                     units = "days"))) 
+readme_df <- readme_df |>
+  mutate(start_date = as.Date("2023-12-11") - age_of_project) |>
+  mutate(event_date_days = 
+           as.numeric(
+             difftime(as.POSIXct("2024-06-24 00:00:00", format = "%Y-%m-%d %H:%M:%S"),
+                      as.POSIXct(event_date, format = "%Y-%m-%d %H:%M:%S"), 
+                      units = "days"))) 
 #some expansion needs to happens for each project 
 expand_timeseries <- function(project_row) {
   longer <- project_row |> 
@@ -40,23 +58,23 @@ library(MASS)
 simple_collab_readme_model <- glm.nb(count ~ as.factor(after_doc), data=collab_pop_readme)
 summary(simple_collab_readme_model)
 qqnorm(residuals(simple_collab_readme_model))
-#
-cor.test(collab_pop_readme$count, collab_pop_readme$after_doc)
 # I don't think MLM is the right one
-collab_readme_model <- glmer.nb(log1pcount ~ as.factor(after_doc) + (after_doc| upstream_vcs_link), data=collab_pop_readme)
+collab_readme_model <- glmer.nb(log1pcount ~ as.factor(after_doc) +  (after_doc| upstream_vcs_link), data=collab_pop_readme)
+collab_readme_model_plus <- glmer.nb(log1pcount ~ as.factor(after_doc) + event_date_days +  (after_doc| upstream_vcs_link), data=collab_pop_readme)
+collab_readme_model <- readRDS("final_models/0623_pop_rm_collab.rda")
 summary(collab_readme_model)
-saveRDS(collab_readme_model, "final_models/0623_pop_rm_collab.rda")
-crm_residuals <- residuals(collab_readme_model)
-qqnorm(crm_residuals)
+saveRDS(collab_readme_model, "final_models/0623_pop_rm_collab_better.rda")
 contrib_readme_model <- glmer.nb(log1pcount ~ after_doc + (after_doc| upstream_vcs_link), data=contrib_pop_readme)
+contrib_readme_model_plus <- glmer.nb(log1pcount ~ after_doc + event_date_days+ (after_doc| upstream_vcs_link), data=contrib_pop_readme)
 summary(contrib_readme_model)
 saveRDS(contrib_readme_model, "final_models/0623_pop_rm_contrib.rda")
-#contrib_readme_model <- load("final_models/0510_pop_rm_contrib.rda")
+contrib_readme_model <- readRDS("final_models/0623_pop_rm_contrib.rda")
 conrm_residuals <- residuals(contrib_readme_model)
 qqnorm(conrm_residuals)
 collab_contrib_model <- glmer.nb(log1pcount ~ after_doc + (after_doc| upstream_vcs_link), data=collab_pop_contrib)
 summary(collab_contrib_model)
 saveRDS(collab_contrib_model, "final_models/0623_pop_contrib_collab.rda")
+contrib_readme_model <- readRDS("final_models/0623_pop_contrib_collab.rda")
 contrib_contrib_model <- glmer.nb(log1pcount ~ after_doc + (after_doc| upstream_vcs_link), data=contrib_pop_contrib)
 summary(contrib_contrib_model)
 saveRDS(contrib_contrib_model, "final_models/0623_pop_contrib_contrib.rda")
@@ -65,7 +83,7 @@ library(texreg)
 
 texreg(list(collab_readme_model, contrib_readme_model), stars=NULL, digits=2,
        custom.model.names=c( 'collab','contrib.'  ), 
-       custom.coef.names=c('(Intercept)', 'after_introduction'), 
+       custom.coef.names=c('(Intercept)', 'after_introduction', 'etc'), 
        use.packages=FALSE, table=FALSE, ci.force = TRUE)
 
 library(ggplot2)