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Fits cumulative link models: proportional odds, probit, complementary log-log, and cauchit.
svyolr(formula, design, ...)
# S3 method for survey.design2
svyolr(formula, design, start, ..., na.action = na.omit, method = c("logistic",
"probit", "cloglog", "cauchit"))
# S3 method for svyrep.design
svyolr(formula,design,...,return.replicates=FALSE,
multicore=getOption("survey.multicore"))
Formula: the response must be a factor with at least three levels
survey design object
dots
Optional starting values for optimization
handling of missing values
Use multicore
package to distribute computation of replicates across multiple
processors?
Link function
return the individual replicate-weight estimates
An object of class svyolr
# NOT RUN {
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")
# }
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