diff --git a/R/0510_log1p_gmodel.rda b/R/0510_log1p_gmodel.rda
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index 0000000..6ff80ae
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diff --git a/R/0510_log1p_nagq_gmodel.rda b/R/0510_log1p_nagq_gmodel.rda
new file mode 100644
index 0000000..89d04e6
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diff --git a/R/0510_log1p_nagq_gmodel_backup.rda b/R/0510_log1p_nagq_gmodel_backup.rda
new file mode 100644
index 0000000..884169b
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diff --git a/R/readmeRDDAnalysis.R b/R/readmeRDDAnalysis.R
index 23082a5..3853d7f 100644
--- a/R/readmeRDDAnalysis.R
+++ b/R/readmeRDDAnalysis.R
@@ -77,18 +77,27 @@ all_standard_errors <- sqrt(diag(vcov(all_model)))[1]
 
 var(all_actions_data$log1p_count) # 1.125429
 mean (all_actions_data$log1p_count) # 0.6426873
+var(all_actions_data$count) # 268.4449
+mean (all_actions_data$count) # 3.757298
+
+summary(all_actions_data$week_offset)
 
 #all_gmodel <- glmer(count ~ D * I(week_offset)+ scaled_project_age + (D * I(week_offset)| upstream_vcs_link), data=all_actions_data, nAGQ=0, family = poisson)
-#all_gmodel <- glmer.nb(count ~ D * I(week_offset)+ scaled_project_age + (D * I(week_offset) | upstream_vcs_link),
-#                       control=glmerControl(optimizer="bobyqa",
-#                                            optCtrl=list(maxfun=2e5)), data=all_actions_data)
-all_log1p_gmodel <- glmer.nb(log1p_count ~ D * I(week_offset)+ scaled_project_age + (D * I(week_offset) | upstream_vcs_link), data=all_actions_data, nAGQ=0,  control=glmerControl(optimizer="bobyqa",
+all_gmodel <- glmer.nb(count ~ D * week_offset + scaled_project_age + (D * week_offset | upstream_vcs_link),
+              control=glmerControl(optimizer="bobyqa",
+                                           optCtrl=list(maxfun=2e5)), data=all_actions_data)
+#all_log1p_gmodel <- glmer.nb(log1p_count ~ D * week_offset+ scaled_project_age + (D * week_offset | upstream_vcs_link), data=all_actions_data, nAGQ=0,  control=glmerControl(optimizer="bobyqa",
+#                           optCtrl=list(maxfun=1e5)))
+all_log1p_gmodel <- glmer.nb(log1p_count ~ D * week_offset+ scaled_project_age + (D * week_offset | upstream_vcs_link), data=all_actions_data, nAGQ=1,  control=glmerControl(optimizer="bobyqa",
                            optCtrl=list(maxfun=1e5)))
 summary(all_log1p_gmodel)
-saveRDS(all_log1p_gmodel, "0509_log1p_gmodel.rda")
-#readRDS(path)
+warnings(all_log1p_gmodel)
+saveRDS(all_log1p_gmodel, "0510_log1p_nagq_gmodel_backup.rda")
+#yesterdays_model <- readRDS("0509_log1p_gmodel.rda")
+all_residuals <- residuals(all_log1p_gmodel)
+qqnorm(all_residuals)
 library(broom.mixed)
-test_condvals <- broom.mixed::tidy(all_gmodel, effects = "ran_vals", conf.int = TRUE)
+test_condvals <- broom.mixed::tidy(all_log1p_gmodel, effects = "ran_vals", conf.int = TRUE)
 test_glmer_ranef_D <- test_condvals [which(test_condvals $term == "D"),]
 has_zero <- function(estimate, low, high){
   return(ifelse((low < 0),ifelse((high > 0), 1, 0), 2))