Rate of drop analysis: Difference between revisions

← Older edit

@@ Line 12: / Line 12: @@
 ==Sample R Code==
-new.data.set <-original.data.set%>%
+models<-ITT.raw.data%>%
-filter(time=="0"| time == "15" | time == "30"| time =="45")
+  filter(time<60)%>%
+  group_by(ID, sex, treatment)%>%
+  mutate(l.glucose = log(glucose))%>%
+  do(fitted.model= lm(l.glucose~ time, data =.))%>%
+  mutate(rate =coef(fitted.model)["time"],
+          max = coef(fitted.model)["(Intercept)"],
+         rsq = summary(fitted.model)$r.squared)%>%
+  mutate(max.exp = exp(max))%>%
+  mutate( slope= max.exp*rate)
-drop.data.lm <- lm (formula = ( glucose ~ time + treatment + time:treatment, data = new.data.set)
-anova(drop.data.lm)
+summary.models<-models%>%
+  group_by(sex,treatment)%>%
+summarise_at(.var ="slope", .funs = funs(mean, se))
-coefficients(drop.data.lm)
+ggplot(summary.models, aes(treatment, mean, fill = treatment))+
+  geom_col(aes(fill = treatment))+
+  facet_grid(.~sex)+
+  geom_errorbar(aes(ymin = mean-se, ymax = mean + se), width = 0.3)+
+  scale_fill_manual(values = color.scheme)+
+  labs(title = "Rate of Drop, ITT",y="mg/dL per minute")
+rate.aov<-aov(slope ~ sex + treatment, data = models)
+anova(rate.aov)%>%kable