basepredict.polr: predicted value

In glm.predict: Predicted Values and Discrete Changes for GLM

predicted value

Description

The function calculates the predicted value with the confidence interval. It can be used for any polr model.

Usage

## S3 method for class 'polr'
basepredict(model, values, sim.count=1000, conf.int=0.95, sigma=NULL, set.seed=NULL,
  type = c("any", "simulation", "bootstrap"), summary = TRUE)

Arguments

model	the model Object generated with polr()
values	the values of the case as vector in the order how they appear in the summary(model) Estimate
sim.count	OPTIONAL numbers of simulations to be done by the function. default: 1000
conf.int	OPTIONAL the confidence interval used by the function. default: 0.95
sigma	OPTIONAL the variance-covariance matrix, can be changed when having for example robust or clustered vcov. default: vcov(model)
set.seed	OPTIONAL set a seed for the random number generator
type	OPTIONAL choose between simulation and bootstrap, "any" chooses between those two according to the number of cases (bootstrap if n < 1000)
summary	OPTIONAL if mean/quantiles should be return or all simulated values (default: TRUE)

Details

The function makes a simulation for the two cases and compares them to each other.

Value

The output is a matrix have in the first column the predicted value, in the second column the lower value of the confidence interval and in the third column the upper value of the confidence interval.

Author(s)

Benjamin Schlegel, [e-mail]

Examples

## Not run: 
data = MASS::survey
data$Smoke = ordered(data$Smoke, levels = c("Never", "Occas", "Regul", "Heavy"))
model1 = polr(Smoke ~ Height + Pulse, data=data)
summary(model1)
# predicted probability of smoking of a person with height 170 and an average pulse
basepredict(model1, c(170,mean(MASS::survey$Pulse,na.rm=TRUE)))

## End(Not run)

glm.predict documentation built on Dec. 2, 2022, 5:12 p.m.