LRtest {eRm}R Documentation

Likelihood ratio model test

Description

Computation of Andersen's LR-test.

Usage

## S3 method for class 'Rm':
LRtest(object, splitcr = "median", alpha = 0.05, se = TRUE)
## S3 method for class 'LR':
plotGOF(x, beta.subset = "all", xlab = "Beta Group 1", 
ylab = "Beta Group 2", ylim = c(-3, 3), xlim = c(-3, 3), type = "p", ...)
## S3 method for class 'LR':
print(x,...)
## S3 method for class 'LR':
summary(object,...)

Arguments

The parameters for LRtest which returns an object of class LR are:

object Object of class Rm.
splitcr Split criterion for subject raw score splitting. all.r corresponds to a full raw score split, median uses the median as split criterion, mean performs a mean-split. Optionally splitcr can also be a vector which assigns each person to a certain subgroup (e.g., following an external criterion).
alpha Significance level for Chi-square statistic.
se If TRUE, standard errors are computed.
x Object of class LR for visualizing the fit of single items.
beta.subset Either a numeric vector or a character vector indicating the columns of the data matrix which should be plotted. If "all", all items are plotted.
xlab Label of the x-axis.
ylab Label of the y-axis.
xlim Parameter range for group 1.
ylim Parameter range for group 2.
type Type of plot desired. By default points are plotted.
... Additional plot parameters.

Details

Value

LRtest returns an object of class LR containing:

X Data matrix.
X.list List of data matrices for the subgroups.
model Fitted model
LR LR-value.
df Degrees of freedom of the test statistic.
Chisq Chi-square value with corresponding df and alpha.
pvalue P-value of the test.
likgroup Log-likelihood values for the subgroups
betalist List of beta parameters for the subgroups.
etalist List of eta parameters for the subgroups.
selist List of standard errors of the eta parameters.

Note

Author(s)

Patrick Mair, Reinhold Hatzinger

References

Andersen, E. B. (1973). A goodness of fit test for the Rasch model. Psychometrika, 38, 123-140.

Mair, P., and Hatzinger, R. (2007). Extended Rasch modeling: The eRm package for the application of IRT models in R. Journal of Statistical Software, 20(9), 1-20.

See Also

Waldtest

Examples


# LR-test on dichotomous Rasch model with median split
data(raschdat1)
res <- RM(raschdat1)
lrres <- LRtest(res)
print(lrres)
summary(lrres)
plotGOF(lrres)

# LR-test on dichotomous Rasch model with user-specified split
splitvec <- sample(1:3, 100, replace = TRUE)          #3 random subgroups
lrres <- LRtest(res, splitcr = splitvec)
print(lrres)
summary(lrres)
plotGOF(lrres)


[Package eRm version 0.9.1.1 Index]