aov.b() for performing between-subject
analysis of variance including Tukey HSD post hoc test for multiple
comparison.as.na() is also applicable to arraysplot and arguments for various
graphical parameters for plotting results to the functions
test.levene(), test.t(),
test.welch(), and test.z().write for writing results into an
Excel file to the functions cor.matrix(),
crosstab(), descript(), freq(),
item.alpha(), item.cfa(),
item.omega(), multilevel.cor(),
multilevel.descript(), na.coverage(),
na.descript(), and na.pattern()posthoc for conducting Games-Howell
post hoc test for multiple comparison to the functions
test.welch().item.cfa() for conducting confirmatory
factor analysis using the R package lavaan.write.result() can also write results based on
the return object of the item.cfa() function.exclude of the function freq()
can also be set to FALSE.multilevel.cor() to
make it consistent with the output of the function
item.cfa().na.omit in the functions
multilevel.cor() to missing to make it
consistent with the arguments of the function
item.cfa().estimator
in the functions multilevel.cor() to ML, so
that full information maximum likelihood method is used for dealing with
missing data.multilevel.cor(), function
did not use Huber-White robust standard errors, but conventional
standard errors when specifying estimator = "MLR".multilevel.r2() for computing R-squared
measures for multilevel and linear mixed effects models.write.xlsx() for writing Excel files
(.xlsx).write.result() for writing results of a
misty object into an Excel file.multilevel.descript().round to the function
freq() for rounding numeric variables.na.test() function when
running into numerical problems.sig in the
functions cor.matrix() and multilevel.cor() to
FALSE.collin.diag() function.print.misty.object(),
function did not print the result object of the the function
crosstab() correctly when requesting percentages.multilevel.cor() for computing the
within-group and between-group correlation matrix using the lavaan
package.na.test() for performing Little’s missing
completely at random (MCAR) test.indirect() for computing confidence
intervals for the indirect effect using the asymptotic normal method,
the distribution of the product method, and the Monte Carlo method.multilevel.indirect() for computing
confidence intervals for the indirect effect in a 1-1-1 multilevel
mediation model using the Monte Carlo method.cor.matrix() highlights statistically
significant correlation coefficients in boldface.cor.matrix() shows the results in a table when
computing a correlation coefficient for two variables.stat) and degrees of freedom
(df) to the argument print in the function
cor.matrix().continuity for continuity correction
to the function cor.matrix() for testing Spearman’s
rank-order correlation coefficient and Kendall’s Tau-b correlation.cor.matrix() when computing Spearman’s rank-order
correlation coefficient or Kendall’s Tau-b correlation.group in the functions
center(), group.scores(),
multilevel.descript(), multilevel.icc(), and
rwg.lindell() to cluster.group.scores() to
cluster.scores().cor.matrix(), function did
not print sample sizes when specifying a grouping variable and using
listwise deletion.write.mplus() writes a Mplus input template
with variables names specified in the DATA command along with the
tab-delimited data file by default.Removed the argument print() in the
write.mplus() function.
Changed the default setting of the argument weighted
in the test.welch() function into FALSE
following the recommendation by Delacre et al. (2021).
Fixed a bug in the function cohens.d(), function
printed warning messages of the pt() function.
Fixed a bug in the function cohens.d(), function
could not deal with more than one variable in a one-sample
design.
New function test.t() for performing one-sample,
two-sample, and paired-sample t-tests including Cohen’s d effect size
measure.
New function test.welch() for performing Welch’s
t-test including Cohen’s d effect size measure and Welch’s ANOVA
including \(\eta^2\) and \(\omega^2\) effect size measures.
Added standard error of the mean to the argument
print in the function descript().
Added the arguments format, label,
labels, missing to the function
read.sav() to remove variable formats, variable labels,
value labels, value labels for user-defined missings, and widths from
attributes of the variable.
Function item.reverse() can also be applied to to
items with non-integer values.
Return object of the function cor.matrix() when
specifying a grouping variable comprises the combined results of both
groups in the matrices.
Function read.mplus() can also deal with consecutive
variables (e.g., x1-x5).
Added group and split arguments to the
function cohens.d().
Added Cohen’s d effect size measure to the output of the
test.z function.
Function cohens.d() computes various kinds of
Cohen’s d, Hedges’ d, and Glass’s \(\Delta\) including confidence intervals,
e.g., weighted and unweighted pooled standard deviation in a two-sample
design, with and without controlling for the correlation between the two
sets of measurement in a paired-sample design, or with and without the
small-sample correction factor.
Renamed following functions: alpha.coef() to
item.alpha(), cont.coef() to
cor.cont(), cramers.v() to
cor.cramer(), levenes.test() to
test.levene(), mgsub() to
chr.gsub(), omega.coef() to
item.omega(), reverse.item() to
item.reverse(), phi.coef() to
cor.phi(), poly.cor() to
cor.poly(), scores() to
item.scores(), stromit() to
chr.omit(), trim() to chr.trim(),
z.test() to test.z(),
Changed the argument use in the
cor.matrix() function into na.omit.
Changed the default setting of the argument method
in the functions multilevel.descript() and
multilevel.icc() to "lme4"; if the lme4
package is not installed, "aov" will be used.
Changed the output of the functions ci.mean.diff()
and ci.mean.prop() when computing confidence intervals in
two-sample designs, i.e., results are divided in two rows according to
the grouping variable.
Changed the output of the functions ci.mean.diff()
and ci.mean.prop() when computing confidence intervals in
paired-sample designs, i.e., output reports the number of missing data
pairs (nNA), instead of number of missing values for each
variable separately (nNA1 and nNA2).
Changed the output of the functions descript() when
specifying the argument levenes.test(), i.e., duplicated
labels in the column group or variable are not
shown.
Changed the functions cohens.d() into a generic
function with the methods cohens.d.default() and
cohens.d.formula().
Added arguments hypo and descript to
the functions test.levene() and
test.z().
Added titles to the output of the freq,
descript, and crosstab function.
Changed the argument as.na in the
as.na() function into na.
Fixed a bug in the function center() which caused an
error message in case of groups with only one observation when trying to
apply group mean centering.
Fixed a bug in the function center() which caused an
error message when trying to apply grand mean centering of a Level 1
predictor.
Fixed a bug in the function cohens.d(), an error
message was printed in the between subject design whenever specifying a
grouping variable with missing values.
Fixed a bug in the function cor.matrix(), which
caused an error when using listwise deletion for missing data while
specifying a grouping variable.
Fixed a bug in the function descript(), which caused
an error message when selection only one or two argument statistical
measures using the argument print.
Fixed a bug in the function freq(), where the
argument split was broken.
Fixed a bug in the function test.zz(), where the
alternative hypothesis was displayed wrong when specifying
alternative = "greater" or
alternative = "less".
New function collin.diag() for collinearity
diagnostics including tolerance, (generalized) standard error inflation
factor, (generalized) variance inflation factor, eigenvalues,
conditional indices, and variance proportions for linear, generalized
linear, and mixed-effects models.
New function std.coef() for computing standardized
coefficients (StdX, StdY, and StdYX) for linear models estimated by
using the lm() function.
New function mgsub() for multiple pattern matching
and replacements, i.e., gsub() function for matching and
replacing a vector of character strings.
New functions df.duplicated() and
df.unique() extracting duplicated or unique rows of a
matrix or data frame.
read.xlsx(), default
setting of the argument progress was wrong.print.misty.object().z.test() for performing one sample, two
sample, and paired sample z-test.omega.coef() does not access internal slots of
a fitted lavaan object anymore (requested by Yves Rosseel).Added descriptive statistics and confidence intervals to the
function levenes.test().
Changed the output of the functions size.mean(),
size.prop(), and size.cor() to include greek
letters.
Changed the argument theta in the
size.mean() function into delta.
New functions ci.mean(),
ci.mean.diff(), ci.median(),
ci.prop(), ci.prop.diff(),
ci.sd(), ci.var() for computing confidence
interval for the arithmetic mean, the difference in arithmetic means,
the median, the proportion, the difference in proportions, the variance,
and the standard deviation.
New function levenes.test() for conducting Levene’s
test for homogeneity of variance.
New function omega.coef() for computing coefficient
omega (McDonald, 1978), hierarchical omega (Kelley &
Pornprasertmanit, 2016), and categorical omega (Green & Yang,
2009).
New function read.xlsx() for reading Excel files
(.xlsx).
Added ordinal coefficient alpha to the function
coef.alpha().
Added Kendall-Stuart’s Tau-c correlation coefficient to the
function cor.matrix().
Function as.na() can also replace user-specified
values with missing values in lists.
Changed the argument use in the
alpha.coef() function into a logical argument
na.omit.
Changed the argument pval.digits in the
cor.matrix() function into p.digits.
Merged print functions print.cont.coef(),
print.cramers.v(), print.na.auxiliary(),
print.na.coverage(), print.phi.coef(), and
print.poly.cor() into
print.square.matrix()
Fixed a bug in several function, where is.vector()
function was used to test if an object is a vector. Instead
is.atomic() function is used to test if an object is a
vector.
Fixed a bug in the function as.na(), function
converted strings in data frames to factors.
trim() for removing whitespace from start
and/or end of a string. Note that this function is equivalent to the
function trimws() in the base package.
However, the trimws() function fails to remove whitespace
in some instances.Fixed a bug in the function cohens.d(), function
returned NA for Cohen’s d in within-subject design in the
presence of missing values
Fixed a bug in the function alpha.coef(), function
did not provide any item statistics irrespective of the argument
print
Fixed a bug in the function as.na(), function always
generated a warning message irrespective of the argument
as.na