- New functions
`na.satcor()`

,`cfa.satcor()`

,`sem.satcor()`

,`growth.satcor()`

, and`lavaan.satcor()`

to estimate a confirmatory factor analysis model, structural equation model, growth curve model, or latent variable model in the`lavaan`

package using full information maximum likelihood (FIML) method to handle missing data while automatically specifying a saturated correlates model to incorporate auxiliary variables into a substantive model. - New function
`read.data()`

to read data files in CSV, DAT, TXT, SPSS, Excel, or Stata DTA format.

- Changed the default setting of the argument
`print`

in the functions`na.test`

, to`little`

.

- Fixed a bug in the function
`mplus.plot()`

, which caused an error message when requesting a loop plot by specifying`plot = "loop"`

. - Fixed a bug in the function
`mplus.print()`

, which caused an error message when printing a Mplus output for an automatic testing of measurement invariance.

- The functions
`mplus`

and`blimp`

do not require the`...;`

specification in the`VARIABLES`

section anymore when specifying variable names with the argument`data`

. - Added the argument
`labels`

in the function`blimp.plot()`

to show parameter labels in the facet labels.

- The function
`na.auxiliary()`

does not print full`NA`

rows of the Cohen’s d matrix anymore. - The function
`na.indicator()`

creates a missing data indicator matrix with`0 = observed`

and`1 = missing`

. - Added the arguments
`na`

,`append`

and`name`

to the function`na.indicator()`

.

- Fixed a bug in the function
`mplus.print()`

, function did not the print input result when specifying`print = "all"`

. - Fixed a bug in the function
`blimp()`

, which caused an error message when specifying a`posterior = TRUE`

and saving the posterior distribution failed. - Fixed a bug in the function
`blimp.print()`

, which caused an error message when specifying a`misty.object`

for the argument`x`

. - Fixed a bug in the function
`blimp.plot()`

, function did not save and plots regardless of the setting of the argument`saveplot`

.

- New function
`mplus.plot()`

to read a Mplus GH5 file to display trace plots, posterior distribution plots, autocorrelation plots, posterior predictive check plots, and loop plots. - New function
`blimp.run()`

to run a group of Blimp models located within a single directory or nested within subdirectories. - New function
`blimp.print()`

to print a Blimp output file on the R console. - New function
`blimp.plot()`

to read the posterior distribution for all parameters to display trace plots and posterior distribution plots. - New function
`blimp()`

to create and run a Blimp input to print the output on - New function
`blimp.update()`

to update specific input command sections of a`misty.object`

of type`blimp`

to create an updated Blimp input file, run the updated input file, and print the updated Blimp output. - New function
`mplus.bayes()`

to read a Mplus GH5 file and`blimp.bayes()`

to read the posterior distribution for all parameters to compute point estimates, measures of dispersion, measures of shape, credible intervals, convergence and efficiency diagnostics, probability of direction, and probability of being in the ROPE for the posterior distribution for each parameter. - The
`na.test`

function provides Jamshidian and Jalalꞌs approach for testing the missing completely at random (MCAR) assumption. - New function
`clear()`

to clear the console equivalent to`Ctrl + L`

in RStudio. - New function
`chr.color()`

to add color and style to output texts on terminals that support ‘ANSI’ color and highlight codes.

- Added the option
`default`

to the argument`print`

of the`descript`

function. - Added the argument
`comment`

to the`mplus`

function. - The function
`na.test`

performs Little’s MCAR test using the`mlest`

function from the`mvnmle`

package that can handle up to 50 variables instead of using the`prelim.norm`

function in the`norm`

package that can only handle about 30 variables. - The function
`na.pattern`

plots the missing data pattern when specifying`plot = TRUE`

and runs faster. - The function
`na.auxiliary`

computes semi-partial correlations of an outcome variable conditional on the predictor variables of a substantive model with a set of candidate auxiliary variables to identify correlates of an incomplete outcome variable as suggested by Raykov and West (2016)..

- Changed the default setting of the argument
`print`

in the functions`mplus.print`

, to`result`

. - The function
`mplus.print`

does not print the section`MODEL FIT INFORMATION`

if the degrees of freedom is zero. - Renamed the argument
`run.mplus`

in the function`mplus.lca()`

to`mplus.run`

. - Changed the default setting of the argument
`ls.fit`

in the function`multilevel.cfa()`

to`FALSE`

.

- Fixed a bug in the function
`mplus.update()`

, which caused an error message when specifying`output = FALSE`

. - Fixed a bug in the function
`mplus.lca()`

, which caused an error message when checking the input for the argument`processors`

. - Fixed a bug in the functions
`item.cfa()`

and`multilevel.cfa()`

, functions did not allow specifying more than two residual covariances (thanks to Lydia Laninga-Wijnen). - Fixed a bug in the function
`multilevel.descript()`

, average, minimum, and maximum cluster size at Level 3 were calculated incorrectly. - Fixed a bug in the function
`item.omega()`

, function did not provide item statistics regardless of the`print`

argument setting (thanks to Ainhoa Coloma Carmona).

- Updated the function
`mplus.run()`

according to the latest version of the function`runModels()`

in the MplusAutomation package.

- Fixed a bug in the function
`mplus.print()`

, function did not print result of a misty.object of type mplus.

- New function
`mplus.print()`

for printing a Mplus output file on the R console. - New function
`mplus()`

to create and run a Mplus input to print the output on the console. - New function
`update.mplus()`

to update specific Mplus input command sections in the`mplus`

object, run the updated input file, and print the output on the console. - New functions
`chr.grep()`

and`chr.grepl()`

for multiple pattern matching, i.e.,`grep()`

and`grepl()`

functions for matching a vector of character strings.

- The function
`write.mplus()`

is not restricted to variable names with up to 8 characters anymore. - Renamed the function
`run.mplus()`

to`mplus.run()`

. - Changed the default setting of the argument
`posthoc`

in the functions`aov.b()`

,`aov.w()`

and`test.welch()`

to`FALSE`

. - Changed the option of the argument
`replace`

from`modifiedDate`

to`modified`

in the functions`mplus.lca()`

and`mplus.run()`

. - Changed the arguments
`showOutput`

into`show.out`

and`replaceOutfile`

into`replace.out`

in the function`mplus.run()`

. - Added the argument
`message`

to the function`mplus.run()`

.

- Fixed a bug in the function
`test.welch()`

, function did not print post hoc tests when specifying`posthoc = TRUE`

.

- Fixed a bug in the function
`result.lca()`

, function excluded all outputs which involved the word`ERROR`

even though results were available (thanks to Michael Weber). - Fixed a bug in the function
`multilevel.fit()`

, function used the number of observations at the Within level instead of the Between level for computing RMSEA at the Between Level (thanks to Maurizio Sicorello). - Fixed a bug in the function
`descript()`

which caused an error message when specifying a split variable. - Fixed a bug in the function
`robust.coef()`

which caused an error message in the presence of missing data on predictor variables. - Fixed a bug in the functions
`multilevel.icc()`

and`multilevel.descript()`

which caused an error message in when specifying a tibble instead of a data frame (thanks to Tanja Held).

- In the function
`mplus.lca()`

, the argument`processors`

allows to specify the number of processors and threads separately. - In the function
`item.omega()`

, residual covariances can be specified when`type = "categ"`

.

- Fixed a bug related to variable selection using the operators
`.`

,`+`

,`-`

,`~`

,`:`

,`::`

, functions which caused an warning message. - Fixed a bug in the functions
`center()`

,`multilevel.icc()`

, and`multilevel.descript()`

which caused an error message in three-level data with ambiguously coded cluster variables common in longitudinal data.

- Revised the function
`multilevel.descript()`

to take into account missing values, e.g.,`No. of cases`

and`No. of clusters`

show the number observations and clusters after excluding missing values. - Variable attributes in the function
`write.sav()`

do not require specifying all three columns`label`

,`values`

, and`missing`

anymore.

- Added the argument
`na`

to the function`read.mplus()`

.

- Removed the Fortran implementation of the polychoric correlation coefficient because it causes problems when loading the package on Mac computers.

- Fixed a bug in the function
`freq()`

, function did not provide an output.

- New function
`df.subset()`

for subsetting data frames using the operators`.`

,`+`

,`-`

,`~`

,`:`

,`::`

, and`!`

similar to functions from the R package`tidyselect`

. - New function
`lagged()`

to compute lagged values of variables. - New function
`df.move()`

to move variable(s) in a data frame. - New functions
`read.dta()`

and`write.dta()`

to read and write Stata DTA files. - New function
`coding()`

to code categorical variables, i.e., dummy, simple, unweighted and weighted effect, repeated, forward Helmert, reverse Helmert, and orthogonal polynomial coding. - New function
`effsize()`

to compute effect sizes for categorical variables, i.e., (adjusted) phi coefficient, (bias-corrected) Cramer’s V, (bias-corrected) Tschuprow’s T, (adjusted) Pearson’s contingency coefficient, Cohen’s w, and Fei. - New function
`script.copy()`

to save a copy of the current script in RStudio with the current date and time.

- Functions
`as.na()`

,`na.as()``center()`

,`ci.mean()`

,`ci.mean.w()`

,`ci.median()`

,`ci.prop()`

,`ci.var()`

,`ci.sd()`

,`cluster.scores()`

,`cor.matrix()`

,`crosstab()`

,`descript()`

,`freq()`

,`item.alpha()`

,`item.cfa()`

,`item.invar()`

,`item.omega()`

,`item.reverse()`

,`item.scores()`

,`multilevel.cfa()`

,`multilevel.cor()`

,`multilevel.descript()`

,`multilevel.fit()`

,`multilevel.icc()`

,`multilevel.invar()`

,`multilevel.omega()`

,`na.auxiliary()`

,`na.coverage()`

,`na.descript()`

,`na.indicator()`

,`na.pattern()`

,`na.prop()`

,`na.test()`

`rec()`

,`rwg.lindell()`

,`skewness()`

, and`kurtosis()`

provide the argument`...`

instead of the argument`x`

to specify variables from the data frame specified in`data`

using the operators`.`

,`+`

,`-`

,`~`

,`:`

,`::`

. - Function
`multilevel.icc()`

computes intraclass correlation coefficients in three-level data. - Function
`multilevel.descript()`

computes multilevel descriptive statistics in three-level data. - Function
`center()`

centers predictor variables in three-level data. - Function
`na.descript()`

provides descriptive statistics for missing data in two-level and three-level data. - Function
`cor.matrix()`

computes tetrachoric and polychoric correlation coefficients. - Added the arguments
`write`

and`append`

to all functions providing a print function to save the print output into a text file.

- Changed the default setting of the argument
`names`

in the function`rec()`

to`.e`

. - Changed the default setting of the arguments
`label`

and`labels`

in the`read.sav`

function to`FALSE`

. - Changed the argument
`value`

in the function`na.as()`

to`na`

to make it consistent with the arguments of the function`as.na()`

. - Changed the argument
`resid.cov`

in the function`item.omega()`

to`resocv`

to make it consistent with the arguments of the functions`item.cfa()`

and`multilevel.cfa()`

. - Changed the argument
`names`

in the functions`center`

,`cluster.scores`

,`item.reverse`

, and`rec`

to`name`

to make it consistent with the arguments of the functions`item.scores()`

,`na.prop()`

, and`lwg.lindell()`

. - Changed the argument
`x`

and`...`

in the functions`df.duplicated()`

and`df.unique()`

to`...`

and`data`

to make it consistent with all other functions using the`...`

argument. - Merged help pages for the functions
`as.na`

and`na.as`

into one help page. - Merged help pages for the functions
`script.open`

,`script.close`

, and`script.save`

into one help page. - Merged help pages for the functions
`skewness`

and`kurtosis`

into one help page. - Merged help pages for the functions
`ci.mean`

and`ci.median`

into one help page. - Merged help pages for the functions
`ci.var`

and`ci.sd`

into one help page. - Removed the function
`shift()`

and replaced it by the function`lagged()`

. - Removed the function
`dummy.c()`

and replaced it by the function`coding()`

- Removed the functions
`cor.phi()`

,`cor.cont()`

,`cor.cramer()`

, and`eta.sq()`

and replaced them by the function`effsize()`

. - Removed the function
`cor.poly()`

and integrated polychoric correlation coefficient into the function`cor.matrix()`

.

- Fixed a bug in the function
`multilevel.descript()`

, function led to a node stack overflow.

- New function
`shift()`

to compute lagged or leading values of a vector.

- Fixed a bug in the function
`libraries()`

, version of the packages were not correctly displayed.

- Fixed a bug in the function
`test.welch()`

, to remove errors for r-devel from a recent change in r-devel.

- Added the argument
`group.ind`

to the function`result.lca()`

to specify. latent class indicators as grouping variable in the bar charts.

- Function
`mplus.lca()`

can be used to conduct latent class analysis with count, unordered categorical, and ordered categorical indicator variables. - Function
`result.lca()`

can be used to save bar charts with error bars for confidence intervals for each of the latent class solutions.

- Fixed a bug in the function
`dominance.manual()`

, function provided the wrong rank ordering.

- Renamed the functions
`mplus.lpa()`

and`results.lpa()`

to`mplus.lca()`

and`results.lca()`

.

- New function
`item.invar()`

for evaluating configural, metric, scalar, and strict between-group or longitudinal (partial) measurement invariance. - New function
`robust.coef()`

for computing heteroscedasticity-consistent standard errors and significance values for linear models estimated by using the`lm()`

function and generalized linear models estimated by using the`glm()`

function. - New function
`dominance()`

for linear models estimated by using the`lm()`

function and`dominance.manual()`

to conduct dominance analysis based on a (model-implied) correlation matrix of the manifest or latent variables. - New function
`check.resid()`

for performing residual diagnostics to detect nonlinearity (partial residual or component-plus-residual plots), nonconstant error variance (predicted values vs. residuals plot), and non-normality of residuals (Q-Q plot and histogram with density plot). - New function
`mplus.lpa()`

for writing Mplus input files for conducting latent profile analysis based on six different variance-covariance structures. - New function
`result.lpa()`

for creating a summary result table for latent profile analysis from multiple Mplus output files within subfolders.

- Added the argument
`order`

to the function`multilevel.cor()`

to order variables in the output table so that variables specified in the argument`between`

are shown first. - Added modification indices for parameter constraints to the function
`multilevel.cfa()`

and`multilevel.invar()`

. - Added residual correlation matrix to the function
`item.cfa()`

,`multilevel.cfa()`

, and`multilevel.invar()`

. - Function
`write.result()`

can also write results based on the return object of the`std.coef`

function.

- Renamed the argument
`min.value`

in the function`item.cfa()`

,`multilevel.cfa()`

, and`multilevel.invar()`

to`mod.minval`

and changed the default setting to`6.63`

.

- Removed the R package
`r2mlm`

from the`Imports`

field in the`DESCRIPTION`

due to dependencies issues.

- Function
`multilevel.descript()`

can also deal with between-cluster variables by reporting means and standard deviations at the cluster level. - Added the argument
`print`

to the function`multilevel.descript()`

to request standard deviation of the variance components.

- New function
`multilevel.fit()`

for computing simultaneous and level-specific model fit information for a fitted multilevel model containing no cross-level constraints from the R package lavaan. - New function
`multilevel.cfa()`

for conducting multilevel confirmatory factor analysis using the R package lavaan to investigate four types of constructs, i.e., within-cluster, shared, configural, and simultaneous shared and configural cluster constructs. - New function
`multilevel.invar()`

for evaluating configural, metric, and scalar cross-level measurement invariance using multilevel confirmatory factor analysis. - New function
`multilevel.omega()`

for computing point estimate and Monte Carlo confidence interval for the multilevel composite reliability defined by Lai (2021) for a within-cluster construct, shared cluster-level construct, and configural cluster construct.

- Added convergence checks to the function
`multilevel.cor()`

, e.g., warning message is printed when absolute correlations are greater than 1. - Argument
`cluster`

in the function`multilevel.cor()`

,`multilevel.descript()`

, and`multilevel.icc()`

can also be specified using the variable name of the cluster variable in`x`

.

- Revised the output of the
`item.cfa()`

function, e.g., loglikelihood and information criteria are shown above chi-square test of model fit and label`Ad Hoc`

changed to`Scaled`

.

- Fixed a bug in the function
`multilevel.cor()`

, which caused an error message (thanks to Richard Janzen).

- New function
`libraries()`

to load and attach multiple add-on packages at once. - New function
`check.outlier()`

computes statistical measures for leverage, distance, and influence for linear models estimated by using the`lm()`

function

- When using function
`write.result()`

, result tables are in line with the arguments`print`

,`tri`

,`digits`

,`p.digits`

, and`icc.digits`

specified in the object`x`

(thanks to Stefan Kulakow). - Function
`crosstab()`

displays marginal row-wise, column-wise, and total percentages in the output (thanks to Joachim Fritz Punter and Lisa Bucher). Note that the function now also returns the crosstable in the list element`result$crosstab`

of the return object .

- Revised the
`Value`

sections in the documentation of the functions. - Changed the default setting of the argument
`weighted`

in the`test.t`

and the`na.auxiliary`

function to`FALSE`

in line with the recommendation by Delacre et al. (2021). - Renamed the function
`collin.diag()`

to`check.collin()`

.

- Fixed a bug in the function
`read.mplus()`

, an error message was printed if comments in the Mplus input file contains special characters (e.g., ä, ü, ö). - Fixed a bug in the function
`std.coef()`

, the function was not applicable to predictors specified as character vector or factor.

- New functions
`script.close()`

,`script.new()`

,`script.open()`

, and`script.save()`

to close, open, and save R scripts in RStudio. - New function
`setsource()`

to set the working directory to the source file location in RStudio equivalent to using the menu item`Session - Set Working Directory - To Source File Location`

. - New function
`restart()`

to restart the RStudio session equivalent to using the menu item`Session - Restart R`

. - New function
`multilevel.r2.manual()`

to compute R-squared measures by Rights and Sterba (2019) for multilevel and linear mixed effects models by manually inputting parameter estimates.

- Functions
`center()`

,`cluster.scores()`

,`rec()`

, and`item.reverse()`

can be applied to more than one variable at once.

- New function
`aov.w()`

for performing repeated measures analysis of variance (within-subject ANOVA) including paired-samples t-tests for multiple comparison, descriptive statistics, effect size measures, and a plot showing error bars for within-subject confidence intervals. - New function
`ci.mean.w()`

for computing difference-adjusted Cousineau-Morey within-subject confidence intervals.

- Function
`ci.mean.diff()`

computes the confidence interval for the difference for an arithmetic mean in a one-sample design. - Functions
`aov.b()`

,`test.t()`

,`test.welch()`

, and`test.z()`

plot difference-adjusted confidence intervals in two-sample design by default. - Added the argument
`jitter.height`

to the functions`aov.b()`

,`test.levene()`

,`test.t()`

,`aov.welch()`

, and`test.z()`

. - Added the argument
`adjust`

to the function`ci.mean()`

, to apply difference-adjustment for the confidence interval.

- Function
`test.t()`

displays the confidence interval for the mean difference in the one-sample t-test.

- Fixed a bug in the function
`test.t()`

, result table provided by the function did not display the confidence interval correctly.

- New function
`aov.b()`

for performing between-subject analysis of variance including Tukey HSD post hoc test for multiple comparison.

- Function
`as.na()`

is also applicable to arrays - Added the argument
`plot`

and arguments for various graphical parameters for plotting results to the functions`test.levene()`

,`test.t()`

,`test.welch()`

, and`test.z()`

. - Added the argument
`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()`

- Added the argument
`posthoc`

for conducting Games-Howell post hoc test for multiple comparison to the functions`test.welch()`

.

- New function
`item.cfa()`

for conducting confirmatory factor analysis using the R package lavaan.

- Function
`write.result()`

can also write results based on the return object of the`item.cfa()`

function. - Argument
`exclude`

of the function`freq()`

can also be set to`FALSE`

.

- Revised the output of the function
`multilevel.cor()`

to make it consistent with the output of the function`item.cfa()`

. - Changed the argument
`na.omit`

in the function`multilevel.cor()`

to`missing`

to make it consistent with the arguments of the function`item.cfa()`

. - Changed the default setting of the argument
`estimator`

in the function`multilevel.cor()`

to`ML`

, so that full information maximum likelihood method is used for dealing with missing data.

- Fixed a bug in the function
`multilevel.cor()`

, function did not use Huber-White robust standard errors, but conventional standard errors when specifying`estimator = "MLR"`

.

- New function
`multilevel.r2()`

for computing R-squared measures for multilevel and linear mixed effects models. - New function
`write.xlsx()`

for writing Excel files (.xlsx). - New function
`write.result()`

for writing results of a misty object into an Excel file.

- Added mean and variance components to the output of the function
`multilevel.descript()`

. - Added the argument
`round`

to the function`freq()`

for rounding numeric variables.

- Added a warning message in the
`na.test()`

function when running into numerical problems. - Changed the default setting of the argument
`sig`

in the functions`cor.matrix()`

and`multilevel.cor()`

to`FALSE`

.

- Examples added to the documentation of the
`collin.diag()`

function.

- Fixed a bug in the function
`print.misty.object()`

, function did not print the result object of the the function`crosstab()`

correctly when requesting percentages.

- New function
`multilevel.cor()`

for computing the within-group and between-group correlation matrix using the lavaan package. - New function
`na.test()`

for performing Little’s missing completely at random (MCAR) test. - New function
`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. - New function
`multilevel.indirect()`

for computing confidence intervals for the indirect effect in a 1-1-1 multilevel mediation model using the Monte Carlo method.

- Function
`cor.matrix()`

highlights statistically significant correlation coefficients in boldface. - Function
`cor.matrix()`

shows the results in a table when computing a correlation coefficient for two variables. - Added test statistic (
`stat`

) and degrees of freedom (`df`

) to the argument`print`

in the function`cor.matrix()`

. - Added the argument
`continuity`

for continuity correction to the function`cor.matrix()`

for testing Spearman’s rank-order correlation coefficient and Kendall’s Tau-b correlation. - Substantial speed improvement for the function
`cor.matrix()`

when computing Spearman’s rank-order correlation coefficient or Kendall’s Tau-b correlation.

- Changed the argument
`group`

in the functions`center()`

,`group.scores()`

,`multilevel.descript()`

,`multilevel.icc()`

, and`rwg.lindell()`

to`cluster`

. - Renamed the function
`group.scores()`

to`cluster.scores()`

.

- Fixed a bug in the function
`cor.matrix()`

, function did not print sample sizes when specifying a grouping variable and using listwise deletion.

- Function
`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.

- Fixed a bug in the function
`read.xlsx()`

, default setting of the argument`progress`

was wrong.

- Merged all print functions to a single print function called
`print.misty.object()`

.

- New function
`z.test()`

for performing one sample, two sample, and paired sample z-test.

- Function
`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.

- New function
`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`

.