This function fits a latent regression model \(\bold{\theta}=\bold{Y}
\bold{\beta} + \bold{\varepsilon}\).
Only the individual likelihood evaluated at a
\(\bold{\theta}\) grid is needed as the input. Like in
tam.mml a multivariate normal distribution is posed
on the residual distribution. Plausible values can be drawn by subsequent
application of tam.pv (see Example 1).
tam.latreg(like, theta=NULL, Y=NULL, group=NULL, formulaY=NULL, dataY=NULL,
beta.fixed=FALSE, beta.inits=NULL, variance.fixed=NULL,
variance.inits=NULL, est.variance=TRUE, pweights=NULL, pid=NULL,
userfct.variance=NULL, variance.Npars=NULL, verbose=TRUE, control=list())# S3 method for tam.latreg
summary(object,file=NULL,...)
# S3 method for tam.latreg
print(x,...)
Subset of values of tam.mml. In addition,
means (M_post) and standard deviations (SD_post) are computed.
Individual likelihood. This can be typically extracted from fitted
item response models by making use of IRT.likelihood.
Used \(\bold{\theta}\) grid in the fitted IRT model. If like
is generated by the IRT.likelihood function, then theta
is automatically extracted as an attribute.
A matrix of covariates in latent regression. Note that the intercept is automatically included as the first predictor.
An optional vector of group identifiers
An R formula for latent regression. Transformations of predictors
in \(Y\) (included in dataY) can be easily specified,
e. g. female*race or I(age^2).
An optional data frame with possible covariates \(Y\) in latent regression.
This data frame will be used if an R formula in formulaY
is specified.
A matrix with three columns for fixing regression coefficients.
1st column: Index of \(Y\) value, 2nd column: dimension,
3rd column: fixed \(\beta\) value.
If no constraints should be imposed on \(\beta\), then
set beta.fixed=FALSE (see Example 2, Model 2_4)
which is the default.
A matrix (same format as in beta.fixed)
with initial \(\beta\) values
An optional matrix with three columns for fixing entries in covariance matrix: 1st column: dimension 1, 2nd column: dimension 2, 3rd column: fixed value
Initial covariance matrix in estimation. All matrix entries have to be
specified and this matrix is NOT in the same format like
variance.inits.
Should the covariance matrix be estimated? This argument
applies to estimated item slopes in tam.mml.2pl.
The default is FALSE which means that latent
variables (in the first group) are standardized in 2PL estimation.
An optional vector of person weights
An optional vector of person identifiers
Optional user customized function for variance specification (See Simulated Example 17).
Number of estimated parameters of variance matrix
if a userfct.variance is provided.
Optional logical indicating whether iteration should be displayed.
List of control parameters, see tam.mml fro details.
Object of class tam.latreg
A file name in which the summary output will be written
Object of class tam.latreg
Further arguments to be passed
See also tam.pv for plausible value imputation.