% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/S3predict.R
\name{predict}
\alias{predict}
\alias{predict.MIRT}
\alias{predict.MGPCM}
\alias{predict.MGGUM}
\alias{predict.FCMIRT}
\alias{predict.FCDCM}
\alias{predict.FCGDINA}
\alias{predict.FCGGUM}
\alias{predict.TIRT}
\title{S3 Methods: predict}
\usage{
\method{predict}{MIRT}(object, newdata = NULL, type = c("probability", "response"), ...)

\method{predict}{MGPCM}(object, newdata = NULL, type = c("probability", "response"), ...)

\method{predict}{MGGUM}(object, newdata = NULL, type = c("probability", "response"), ...)

\method{predict}{FCMIRT}(object, newdata = NULL, type = c("probability", "response"), ...)

\method{predict}{FCDCM}(object, newdata = NULL, type = c("probability", "response"), ...)

\method{predict}{FCGDINA}(object, newdata = NULL, type = c("probability", "response"), ...)

\method{predict}{FCGGUM}(object, newdata = NULL, type = c("probability", "response"), ...)

\method{predict}{TIRT}(object, newdata = NULL, type = c("probability", "response"), ...)
}
\arguments{
\item{object}{A fitted model object of class \code{"MIRT"},
\code{"MGPCM"}, \code{"MGGUM"}, \code{"FCMIRT"}, \code{"FCDCM"},
\code{"FCGDINA"}, \code{"FCGGUM"}, or \code{"TIRT"}.}

\item{newdata}{An optional \eqn{M \times D} matrix of latent trait
values at which to compute predictions. If \code{NULL} (default),
predictions use the estimated \code{object$theta$est}.}

\item{type}{Character; \code{"probability"} (default) returns
response probabilities, \code{"response"} returns expected category
or simulated binary responses (random draws).}

\item{...}{Additional arguments (currently ignored).}
}
\value{
\describe{
\item{\code{type = "probability"}}{For binary models (MIRT, TIRT):
an \eqn{M \times I} matrix of endorsement probabilities. For
polytomous models (MGPCM, MGGUM): an \eqn{M \times \sum K_i}
matrix of stacked category probabilities. For forced-choice
models (FCMIRT, FCGGUM): an \eqn{M \times \sum K_b} matrix of
block-pattern probabilities. For FCDCM: an \eqn{M \times B}
matrix of marginal block-choice probabilities.}
\item{\code{type = "response"}}{For binary models: an
\eqn{M \times I} matrix of simulated 0/1 responses. For
polytomous models: an \eqn{M \times I} matrix of category
indices. For forced-choice models: an \eqn{M \times B} matrix
of chosen pattern indices.}
}
}
\description{
Predict response probabilities from fitted \pkg{ForceChoice} model
objects. Given a fitted model and optionally new person parameter
(latent trait) values, returns the model-implied response probabilities.
When \code{newdata} is not provided, predictions are made at the
estimated latent trait values for each person.
}
\section{Methods (by class)}{
\itemize{
\item \code{predict(MIRT)}: Predict response probabilities or simulated
responses from \code{MIRT} objects.

\item \code{predict(MGPCM)}: Predict response probabilities from \code{MGPCM} objects.

\item \code{predict(MGGUM)}: Predict response probabilities from \code{MGGUM} objects.

\item \code{predict(FCMIRT)}: Predict response probabilities from \code{FCMIRT} objects.

\item \code{predict(FCDCM)}: Predict response probabilities from \code{FCDCM} objects.

\item \code{predict(FCGDINA)}: Predict response probabilities from \code{FCGDINA} objects.
For \code{newdata}, provide either binary alpha profiles or class
probability rows.

\item \code{predict(FCGGUM)}: Predict response probabilities from \code{FCGGUM} objects.

\item \code{predict(TIRT)}: Predict response probabilities from \code{TIRT} objects.

}}
