svyolr: Proportional odds and related models

In survey: Analysis of Complex Survey Samples

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, ..., na.action = na.omit, method = c("logistic", 
    "probit", "cloglog", "cauchit"))
## S3 method for class 'svyrep.design'
svyolr(formula,design,...,return.replicates=FALSE, 
    multicore=getOption("survey.multicore"))

Arguments

formula	Formula: the response must be a factor with at least three levels
design	survey design object
...	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

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")

Example output

Loading required package: grid
Loading required package: Matrix
Loading required package: survival

Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

Call:
svyolr(mealcat ~ avg.ed + mobility + stype, design = dclus1)

Coefficients:
    avg.ed   mobility     stypeH     stypeM 
-2.6999217  0.0325042 -1.7574715 -0.6191463 

Intercepts:
  (0,25]|(25,50]  (25,50]|(50,75] (50,75]|(75,100] 
       -8.857919        -6.586464        -4.924938 
Working (Rao-Scott+F) LRT for avg.ed stype
 in svyolr(formula = mealcat ~ avg.ed + mobility + stype, design = dclus1)
Working 2logLR =  1.161069 p= 0.59748 
(scale factors:  2.7 0.22 0.11 );  denominator df= 10

survey documentation built on May 2, 2019, 6:05 a.m.