Saturday, January 29, 2022

Ordinal Logistic Regression model

 # Load library

library(haven)

# Read in data

#data input

a <- read.csv(choose.files())


# Load the library

library(MASS)

# Turn the apply variable into a factor

a$KABCO <- factor(a$KABCO)

# Run the ordinal logistic regression model

model <- polr(KABCO~ Covid+ Speed+ Volume+ Drug_Alco, data=a)

summary(model)



#require(modEvA) #for pesudo r square or

require(pscl) #for pesudo r square


#for model fit

#modEvA::RsqGLM(model=model)

#or use 

write.table(pscl::pR2(model),sep="\t")


# Find the p-value for a t-value of 3.9418

pt(3.468, 400-3, lower.tail=FALSE)*2

Std. Errors:

  

stE<- model$Std.Errors

#2 tailed z test

z<- coef(model)/Standard_Error(model)

p<- (1-pnorm(abs(z),0,1))*2

p        #pvalue