svyolr: Proportional odds and related models

Description Usage Arguments Value Author(s) See Also Examples

Description

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

Usage

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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

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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.