pln (version 0.2-3)

startalphas: Starting values for polytomous logit-normit model

Description

Computes starting values for estimation of polytomous logit-normit model.

Usage

startalphas(x, ncat, nitem = NULL)
startbetas(x, ncat, nitem = NULL)

Value

A vector of starting values, depending on which function was called.

Arguments

x

A data matrix. Data can be in one of two formats: 1) raw data where the number of rows corresponds to the number of raw cases and each column represents an item, and 2) a matrix of dimensions nrec\(\times\)(nitem+1) where each row corresponds to a response pattern and the last column is the frequency of that response pattern. A data matrix of the second type requires input for nitem and nrec.

ncat

Number of ordinal categories for each item, coded as 0,...,(ncat-1). Currently supported are items that have the same number of categories.

nitem

Number of items. If omitted, it is assumed that x contains a data matrix of the first type (raw data) and the number of columns in x will be selected as the number of items.

Author

Carl F. Falk , Harry Joe

Details

startalphas computes starting values for the (decreasing) cutpoints for the items based on logit transformed probabilities, assuming independent items.

startbetas computes starting values for slopes under the polytomous logit-normit model, using a method based on values that are proportional to the average correlations of each item with all other items. Starting values are currently bounded between -.2 and 1.

See Also

nrmlepln nrmlerasch nrbcpln

Examples

### Raw data
data(item9cat5)

myAlphas<-startalphas(item9cat5, ncat=5)
print(myAlphas)

myBetas<-startbetas(item9cat5, ncat=5)
print(myBetas)

nrbcplnout<-nrbcpln(item9cat5, ncat=5, alphas=myAlphas, betas=myBetas, se=FALSE)
print(nrbcplnout)

## Matrix of response patterns and frequencies
data(item5fr)

myAlphas<-startalphas(item5fr, ncat=3, nitem=5)
print(myAlphas)

myBetas<-startbetas(item5fr, ncat=3, nitem=5)
print(myBetas)

nrbcplnout<-nrbcpln(item5fr, ncat=3, nitem=5, alphas=myAlphas, betas=myBetas, se=FALSE)
print(nrbcplnout)