svyolr: Proportional odds and related models

In survey: Analysis of Complex Survey Samples

Proportional odds and related models

Description

Fits cumulative link models: proportional odds, probit, complementary log-log, and cauchit.

Usage

svyolr(formula, design, ...)
## S3 method for class 'survey.design2'
svyolr(formula, design, start, subset=NULL,...,
    na.action = na.omit,method = c("logistic", "probit", "cloglog", "cauchit"))
## S3 method for class 'svyrep.design'
svyolr(formula,design,subset=NULL,...,return.replicates=FALSE, 
    multicore=getOption("survey.multicore"))
## S3 method for class 'svyolr'
predict(object, newdata, type = c("class", "probs"), ...)

Arguments

formula	Formula: the response must be a factor with at least three levels
design	survey design object
subset	subset of the design to use; NULL for all of it
...	dots
start	Optional starting values for optimization
na.action	handling of missing values
multicore	Use multicore package to distribute computation of replicates across multiple processors?
method	Link function
return.replicates	return the individual replicate-weight estimates
object	object of class svyolr
newdata	new data for predictions
type	return vector of most likely class or matrix of probabilities

Value

An object of class svyolr

Author(s)

The code is based closely on polr() from the MASS package of Venables and Ripley.

See Also

svyglm, regTermTest

Examples

data(api)
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
dclus1<-update(dclus1, mealcat=cut(meals,c(0,25,50,75,100)))

m<-svyolr(mealcat~avg.ed+mobility+stype, design=dclus1)
m

## Use regTermTest for testing multiple parameters
regTermTest(m, ~avg.ed+stype, method="LRT")

## predictions
summary(predict(m, newdata=apiclus2))
summary(predict(m, newdata=apiclus2, type="probs"))

survey documentation built on May 29, 2024, 12:05 p.m.