Performs a permutation test for testing the hypothesis that model parameter are independent of a moderator variable (see Hildebrandt, Wilhelm, & Robitzsch, 2009; Hildebrandt, Luedtke, Robitzsch, Sommer, & Wilhelm, 2016).
lsem.permutationTest(lsem.object, B=1000, residualize=TRUE, verbose=TRUE,
n.core=1, cl.type="PSOCK")# S3 method for lsem.permutationTest
summary(object, file=NULL, digits=3, ...)
# S3 method for lsem.permutationTest
plot(x, type="global", stattype="SD",
parindex=NULL, sig_add=TRUE, sig_level=0.05, sig_pch=17, nonsig_pch=2,
sig_cex=1, sig_lab="p value", stat_lab="Test statistic",
moderator_lab=NULL, digits=3, title=NULL, parlabels=NULL,
ask=TRUE, ...)
List with following entries
Data frame with global test statistics. The statistics
are SD
, MAD
and lin_slo
with their corresponding
p values.
Data frame with pointwise test statistics.
Original parameters.
Parameters in permutation samples.
Original parameter summary.
Mean of each parameter in permutation sample.
Standard deviation (SD) statistic in permutation slope.
Mean absolute deviation (MAD) statistic in permutation sample.
Linear slope parameter in permutation sample.
Percentage of permuted dataset in which a LSEM model did not converge
Fitted object of class lsem
with lsem.estimate
Number of permutation samples
Optional logical indicating whether residualization of the moderator should be performed for each permutation sample.
Optional logical printing information about computation progress.
A scalar indicating the number of cores that should be used.
The cluster type.
Default value is "PSOCK"
. Posix machines (Linux, Mac) generally benefit
from much faster cluster computation if type is set to type="FORK"
.
Object of class lsem
A file name in which the summary output will be written.
Number of digits.
Further arguments to be passed.
Object of class lsem
Type of the statistic to be plotted. If type="global"
, a global
test will be displayed. If type="pointwise"
for each value at the
focal point (defined in moderator.grid
) are calculated.
Type of test statistics. Can be MAD
(mean absolute deviation),
SD
(standard deviation) or lin_slo
(linear slope).
Vector of indices of selected parameters.
Logical indicating whether significance values (p values) should be displayed.
Significance level.
Point symbol for significant values.
Point symbol for non-significant values.
Point size for graphic displaying p values
Label for significance value (p value).
Label of y axis for graphic with pointwise test statistic
Label of the moderator.
Title of the plot. Can be a vector.
Labels of the parameters. Can be a vector.
A logical which asks for changing the graphic for each parameter.
Alexander Robitzsch, Oliver Luedtke, Andrea Hildebrandt
Hildebrandt, A., Luedtke, O., Robitzsch, A., Sommer, C., & Wilhelm, O. (2016). Exploring factor model parameters across continuous variables with local structural equation models. Multivariate Behavioral Research, 51(2-3), 257-278. tools:::Rd_expr_doi("10.1080/00273171.2016.1142856")
Hildebrandt, A., Wilhelm, O., & Robitzsch, A. (2009). Complementary and competing factor analytic approaches for the investigation of measurement invariance. Review of Psychology, 16, 87-102.
For Examples see lsem.estimate
.