tam.latreg.Rd
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,...)
like | Individual likelihood. This can be typically extracted from fitted
item response models by making use of |
---|---|
theta | Used \(\bold{\theta}\) grid in the fitted IRT model. If |
Y | A matrix of covariates in latent regression. Note that the intercept is automatically included as the first predictor. |
group | An optional vector of group identifiers |
formulaY | An R formula for latent regression. Transformations of predictors
in \(Y\) (included in |
dataY | An optional data frame with possible covariates \(Y\) in latent regression.
This data frame will be used if an R formula in |
beta.fixed | A matrix with three columns for fixing regression coefficients.
1st column: Index of \(Y\) value, 2nd column: dimension,
3rd column: fixed \(\beta\) value. |
beta.inits | A matrix (same format as in |
variance.fixed | An optional matrix with three columns for fixing entries in covariance matrix: 1st column: dimension 1, 2nd column: dimension 2, 3rd column: fixed value |
variance.inits | Initial covariance matrix in estimation. All matrix entries have to be
specified and this matrix is NOT in the same format like
|
est.variance | Should the covariance matrix be estimated? This argument
applies to estimated item slopes in |
pweights | An optional vector of person weights |
pid | An optional vector of person identifiers |
userfct.variance | Optional user customized function for variance specification (See Simulated Example 17). |
variance.Npars | Number of estimated parameters of variance matrix
if a |
verbose | Optional logical indicating whether iteration should be displayed. |
control | List of control parameters, see |
object | Object of class |
file | A file name in which the summary output will be written |
x | Object of class |
... | Further arguments to be passed |
Subset of values of tam.mml
. In addition,
means (M_post
) and standard deviations (SD_post
) are computed.
See also tam.pv
for plausible value imputation.