Description Usage Arguments Value Examples
View source: R/theta_estimates.R
The final estimates of the item scale values and the conditional covariance matrix (i.e, Phi.mat) are used to compute values on latent traits for each individual or case. The estimated thetas are the (conditinal) mean values of response patterns. The correlations between the estimated thetas equal the marginal correlations.
1 | theta.estimates(inData, model.fit)
|
inData |
Matrix of response patterns |
model.fit |
Object containing output from running ple.lma |
theta.est A person by trait matrix of values on the latent traits
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | data(dass)
inData <- dass[1:250,c("d1", "d2", "d3", "a1","a2","a3","s1","s2","s3")]
inTraitAdj <- matrix(1, nrow=1, ncol=1)
inItemTraitAdj <- matrix(1, nrow=9, ncol=1)
r1 <- ple.lma(inData, model.type="rasch", inItemTraitAdj, inTraitAdj)
theta.r1 <- theta.estimates(inData, r1)
g1 <- ple.lma(inData, model.type="gpcm", inItemTraitAdj, inTraitAdj)
theta.g1 <- theta.estimates(inData, g1)
n1 <- ple.lma(inData, model.type="nominal", inItemTraitAdj,inTraitAdj)
theta.n1 <- theta.estimates(inData, n1)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.