LRtest {eRm} | R Documentation |
This LR-test is based on subject subgroup splitting.
## S3 method for class 'Rm': LRtest(object, splitcr = "median", se = FALSE) ## S3 method for class 'LR': plotGOF(x, beta.subset = "all", xlab = "Beta Group 1", ylab = "Beta Group 2", tlab = "item", ylim = c(-3, 3), xlim = c(-3, 3), type = "p", pos = "4", ...) ## S3 method for class 'LR': print(x,...) ## S3 method for class 'LR': summary(object,...)
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). |
se |
If TRUE standard errors for beta's are computed. |
x |
Object of class LR for visualizing the fit of single items. |
beta.subset |
If "all" , all items are plotted. Otherwise numeric subset vector can be specified. |
xlab |
Label on x-axis. |
ylab |
Label on y-axis. |
tlab |
Specification of item labels: "item" prints the item names, "number" gives integers
corresponding to order of the beta parameters, if "none" no labels are printed.
"identify" allows for an interactive labelling. Initially no labels are printed, after clicking
close to an item point the corresponding label is added. The identification process is terminated by clicking
the second button and selecting 'Stop' from the menu, or from the 'Stop' menu on the graphics window.
For more information see identify .
|
xlim |
Limits on x-axis. |
ylim |
Limits on y-axis. |
type |
Plotting type.(see plot ) |
pos |
Position of the item label (see text ) |
... |
Additional graphical parameters. |
If the data set contains missing values and mean
or median
is specified as splitcriterion,
means or medians are calculated for each missing value subgroup and consequently used for raw score splitting.
LRtest
returns an object of class LR
containing:
LR |
LR-value. |
df |
Degrees of freedom of the test statistic. |
Chisq |
Chi-square value with corresponding df. |
pvalue |
P-value of the test. |
likgroup |
Log-likelihood values for the subgroups |
betalist |
List of beta parameters for the subgroups. |
selist |
List of standard errors of beta's. |
etalist |
List of eta parameters for the subgroups. |
Patrick Mair, Reinhold Hatzinger
Fischer, G. H., and Molenaar, I. (1995). Rasch Models - Foundations, Recent Developements, and Applications. Springer.
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.
Mair, P., and Hatzinger, R. (2007). CML based estimation of extended Rasch models with the eRm package in R. Psychology Science, 49, 26-43.
# LR-test on dichotomous Rasch model with user-defined split splitvec <- sample(1:3, 100, replace = TRUE) data(raschdat1) res <- RM(raschdat1) lrres <- LRtest(res, splitcr = splitvec) lrres summary(lrres) plotGOF(lrres)