Update FinalProj.Rmd

FinalProj.Rmd

@@ -197,6 +197,9 @@ round(cor(data[, -c(1, 2, 3, 4, 6)], 3))
 ```
 
 ## Drinks Model(s)
+
+Using the wald-test, liklihood ratio test, and the drop-in-deviance tests, we prefer drinks_mod_2.
+
 ```{r}
 # making models
 drinks_threshold <- mean(data$X30drink)
@@ -210,27 +213,26 @@ summary(fiveDrinks_mod)
 drinks_mod_1 <- glm(drinks_var ~ truth + decision + excite + safe + best.school + grades + Wpdrink, data = data, family = "binomial")
 summary(drinks_mod_1)
 
-# dropped p > 0.1
+# dropped p > 0.1, 
 drinks_mod_2 <- glm(drinks_var ~ truth + decision + excite + safe + best.school + Wpdrink, data = data, family = "binomial")
 summary(drinks_mod_2)
 
 #likelihood ratio test to test whether the observed difference in model fits is statistically significant
 # source: https://www.listendata.com/2016/07/insignificant-levels-of-categorical-variable.html
-
 anova(drinks_total_mod, drinks_mod_1, test="LRT")
+#Not significant, which means we ,ay prefer the smaller model
 anova(drinks_mod_1, drinks_mod_2, test = "LRT")
-#Both of these are not significant, which means dropping the variables we did was not significant. 
+#Significant, which means we may prefer the larger model
 
-# TODO: idk what this does
-anova(drinks_total_mod, drinks_mod_1, test="Chisq")
+# Drop in deviance test
+anova(drinks_mod_2, drinks_mod_1, test="Chisq")
+# The difference in deviance is significantly significant, the drop in dev test prefers the smaller model
 
-#drop in deviance test compares residual deivances from two models
+#drop in deviance test compares residual deviance from two models
 # source: https://bookdown.org/roback/bookdown-BeyondMLR/ch-poissonreg.html#cs-philippines
 # source: https://bookdown.org/roback/bookdown-BeyondMLR/ch-logreg.html
-anova(drinks_mod_1, drinks_mod_2, test = "Chisq")
-
-
 ```
+
 ## Cig model
 
 ```{r}