Curve Plot logistic regression-CodePudding

here is my model. Exam_taken is a binary variable (0,1), and social class (1-10 scale) and GDP are continuous variables.

fit<-glm(Exam_taken~Gender Social_class*GDP, data=final, family=binomial(link="probit")
summary(fit)

I need to draw graphs. Goal 1) the relationship between Social_class and Exam_taken; Goal 2) the interaction of Social_class*GDP on Exam_taken.

I encountered two problems.

I used the following code for Goal 1:

#exclude missing values
final=subset(final, final$Social_class!="NA")
final=subset(final, final$Exam_taken!="NA")
#graph
library(popbio)
logi.hist.plot(final$Social_class, final$Exam_taken, boxp=FALSE, type = "hist")

I got an error "Error in seq.default(min(independ),max(independ),len=100):'from' must be a finite number" How to fix it? Thank you so much

I have no idea how to draw the interaction with two continuous variables on a binary outcome. Can anyone provide some directions? Thanks!

CodePudding user response：

You can use the sjPlot package to plot the predicted values from the model. If you save the output of the plot_model() function, you can modify its appearance using ggplot2.

Here is one of many pages that can show you other options with this package:

Data used

Obviously, we don't have your data, but we can make a reasonable replica given clues from your description and code.

set.seed(1)

final <- data.frame(Gender = rep(c("Male", "Female"), 100),
                    Social_class = sample(10, 200, TRUE),
                    GDP = 1000 * sample(20:60, 200, TRUE))

final$Exam_taken <- rbinom(200, 1, 
                           c(0, 0.1)   0.05 * final$Social_class  
                             final$GDP/1e5 - 0.2)