This class contains the results of tests of Measurement Equivalence and Differential Item Functioning (DIF).
# S4 method for permuteMeasEq
show(object)# S4 method for permuteMeasEq
summary(object, alpha = 0.05, nd = 3,
extra = FALSE)
# S4 method for permuteMeasEq
hist(x, ..., AFI, alpha = 0.05, nd = 3,
printLegend = TRUE, legendArgs = list(x = "topleft"))
object of class permuteMeasEq
alpha level used to draw confidence limits in hist and
flag significant statistics in summary output
number of digits to display
logical indicating whether the summary output
should return permutation-based p values for each statistic returned
by the extra function. If FALSE (default), summary
will return permutation-based p values for each modification index.
Additional arguments to pass to hist
character indicating the fit measure whose permutation
distribution should be plotted
logical. If TRUE (default), a legend will
be printed with the histogram
list of arguments passed to the
legend function. The default argument is a list
placing the legend at the top-left of the figure.
The show method prints a summary of the multiparameter
omnibus test results, using the user-specified AFIs. The parametric
(\(\Delta\))\(\chi^2\) test is also displayed.
The summary method prints the same information from the
show method, but when extra = FALSE (the default) it also
provides a table summarizing any requested follow-up tests of DIF using
modification indices in slot MI.obs. The user can also specify an
alpha level for flagging modification indices as significant, as
well as nd (the number of digits displayed). For each modification
index, the p value is displayed using a central \(\chi^2\)
distribution with the df shown in that column. Additionally, a
p value is displayed using the permutation distribution of the
maximum index, which controls the familywise Type I error rate in a manner
similar to Tukey's studentized range test. If any indices are flagged as
significant using the tukey.p.value, then a message is displayed for
each flagged index. The invisibly returned data.frame is the
displayed table of modification indices, unless
permuteMeasEq was called with param = NULL,
in which case the invisibly returned object is object. If
extra = TRUE, the permutation-based p values for each
statistic returned by the extra function are displayed and returned
in a data.frame instead of the modification indices requested in the
param argument.
The hist method returns a list of length == 2,
containing the arguments for the call to hist and the arguments
to the call for legend, respectively. This list may facilitate
creating a customized histogram of AFI.dist, MI.dist, or
extra.dist
PTA data.frame returned by a call to
parTable on the constrained model
modelTypeA character indicating the specified modelType in the
call to permuteMeasEq
ANOVAA numeric vector indicating the results of the observed
(\(\Delta\))\(\chi^2\) test, based on the central \(\chi^2\)
distribution
AFI.obsA vector of observed (changes in) user-selected fit measures
AFI.distThe permutation distribution(s) of user-selected fit measures.
A data.frame with n.Permutations rows and one column for each
AFI.obs.
AFI.pvalA vector of p values (one for each element in slot
AFI.obs) calculated using slot AFI.dist, indicating the
probability of observing a change at least as extreme as AFI.obs
if the null hypothesis were true
MI.obsA data.frame of observed Lagrange Multipliers
(modification indices) associated with the equality constraints or fixed
parameters specified in the param argument. This is a subset of the
output returned by a call to lavTestScore on the
constrained model.
MI.distThe permutation distribution of the maximum modification index
(among those seen in slot MI.obs$X2) at each permutation of group
assignment or of covariates
extra.obsIf permuteMeasEq was called with an extra
function, the output when applied to the original data is concatenated
into this vector
extra.distA data.frame, each column of which contains the
permutation distribution of the corresponding statistic in slot
extra.obs
n.PermutationsAn integer indicating the number of permutations
requested by the user
n.ConvergedAn integer indicating the number of permuation
iterations which yielded a converged solution
n.nonConvergedAn integer vector of length
n.Permutations indicating how many times group assignment was
randomly permuted (at each iteration) before converging on a solution
n.SparseOnly relevant with ordered indicators when
modelType == "mgcfa". An integer vector of length
n.Permutations indicating how many times group assignment was
randomly permuted (at each iteration) before obtaining a sample with all
categories observed in all groups.
oldSeedAn integer vector storing the value of
.Random.seed before running permuteMeasEq. Only relevant
when using a parallel/multicore option and the original
RNGkind() != "L'Ecuyer-CMRG". This enables users to restore their
previous .Random.seed state, if desired, by running:
.Random.seed[-1] <- permutedResults@oldSeed[-1]
Objects can be created via the
permuteMeasEq function.
# NOT RUN {
# See the example from the permuteMeasEq function
# }
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