startalphas {pln} | R Documentation |
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)
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
|
ncat |
Number of ordinal categories for each item, coded as
0,...,( |
nitem |
Number of items. If omitted, it is assumed that |
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.
Value
A vector of starting values, depending on which function was called.
Author(s)
Carl F. Falk cffalk@gmail.com, Harry Joe
See Also
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)