Reputation: 425
Helloy everybody,
I plotted a mixed model from "nlme" with "ggplot2" and I would like to consider different variance in my category variable in the model (weights=varIdent(form = ~1 | category)). When I checked the plot I realised that the model prediction in the plot did no include the heteroscedasticity, altough the model does. How can I adjust the predict function, so that includes the heteroscedasticity?
create some data:
no <- 1:20
type <- factor("A","B")
set.seed(1)
baseline <- rnorm(20, 30, 10)
set.seed(2)
event <- rnorm(20, 60, 30)
set.seed(3)
postevent1 <- rnorm(20, 40, 20)
set.seed(4)
postevent2 <- rnorm(20, 30, 10)
set.seed(5)
postevent3 <- rnorm(20, 20, 5)
data <- data.frame(no, baseline, event, postevent1, postevent2, postevent3)
data$type[data$no %% 2 == 0] <- "A"
data$type[data$no %% 2 != 0] <- "B"
data$event[data$type == "A"] <- data$event[data$type == "A"] -2
data$no <- factor(data$no)
data$type <- factor(data$type)
transform the data to the long format
library(dplyr)
long <- data %>% gather(key = category, value = measure, -no, -type)
create the model
library(nlme)
model <- lme(measure ~ category*type, random = ~ 1|no, data= long,
weights=varIdent(form = ~1 | category), method = "REML")
new <- long %>% select(-measure)
long$pred <- predict(model, newdata = new)
plot it
library(ggplot2)
ggplot(long, aes(x=category, y = measure, colour = type,
group=interaction(type,category))) +
geom_point() +
facet_grid(~ type) +
geom_line(aes(y=pred), size=0.8, colour = "black") +
theme(axis.text.x = element_text(angle=30, hjust=1, vjust=1))
Upvotes: 1
Views: 1713
Reputation: 425
This is my solution using the "AICcmodavg" package. If anyone finds a better solution, please let me know.
predicting the values
library(AICcmodavg)
pred <- predictSE.lme(model, newdata = new, print.matrix = TRUE)
pred <- data.frame(pred)
newlong <- data.frame(long, pred)
plotting the mean with the 95% confidence interval from the prediction
ggplot(newlong, aes(x= category, y= measure)) +
geom_point(aes(x = category, y = fit)) +
facet_grid(~ type) +
geom_point(aes(colour = type), alpha = 0.5, size = 3) +
geom_errorbar(aes(ymax=fit + se.fit*1.96, ymin=fit - se.fit*1.96),
position=position_dodge(0.9), width=0.25) +
theme(axis.text.x = element_text(angle=30, hjust=1, vjust=1))
Upvotes: 1