                 Changes in version 0.8.4 (2026-10-14)                  

New features

  - New function test.linear() for performing tests for linearity in a
    linear model, i.e., RESET test, Harvey-Collier test, and Rainbow
    test.
  - New function test.homo() for performing tests for homoscedasticity
    in a linear model, i.e., Breusch-Pagan test, White's test,
    Evans-King Generalized Least Squares test, and Verbyla's test.
  - New function test.norm() for performing tests for univariate
    normality (i.e., Lilliefors test, Shapiro-Wilk test,
    Anderson–Darling, and Cramer-von Mises test), and multivariate
    normality (i.e., Henze-Zirkler test, Henze-Wagner test, and Royston
    test).
  - New function test.bm() for performing the two-sample and paired
    (Permuted) Brunner-Munzel test for stochastic equality.

Minor features and improvements

  - Revised the function check.outlier(), i.e., the function performs
    outlier and influential observations diagnostics by plotting
    statistical measures for leverage, distance, and influence for liner
    models.
  - The functions test.t.formula and test.welch can conduct multiple
    two-sample t-tests or Welch tests with multiple outcome variables.
  - Added the arguments plot, geom, filename, width, height, and dpi to
    the functions cor.matrix() and multilevel.cor() to draw and save a
    correlation heat map.

User-visible changes

  - Added the argument horiz to the function print.misty.object() after
    removing the argument in the previous version
  - Removed the argument sort.var from the function
    print.misty.object().
  - Removed the arguments cor and ref from the function test.t() and
    test.welch().
  - Added the argument geom to the functions aov.b(), aov.w(),
    test.levene(), test.t(), test.welch(), and test.z() and removed the
    arguments bar, point, box, ci, line, and jitter.
  - Added the argument data to the functions cohens.d.default,
    ci.mean.diff.default, ci.prop.diff.default, test.t.default, and
    test.z.default.
  - Added the argument na.omit to the functions test.t.formula and
    test.welch.
  - Changed the default setting of the argument sample in the functions
    skewness and kurtosis to FALSE.
  - Removed the arguments square, rotate, color, tile.alpha,
    plot.margin, legend.box.margin, legend.key.size, legend.text.size,
    and units from the function na.pattern, and added the argument geom
    to the function na.pattern.
  - Removed the plot arguments from the function multilevel.r2, and
    added the argument ... to the function multilevel.r2.
  - Removed the plot arguments from the function check.resid, and added
    the argument ... to the function multilevel.r2.
  - Added and renamed several plot arguments to the plot.misty.object
    and changed the default setting for all arguments to NULL.

                 Changes in version 0.8.3 (2026-08-02)                  

New features

  - New function multilevel.alpha() for computing point estimate and
    Monte Carlo confidence interval for multilevel coefficient alpha
    defined by Lai (2021).
  - New function item.stats() for conducting item analysis for
    dichotomous, polytomous, and continuous items.
  - New function item.distract() for conducting distractor analysis for
    multiple-choice items.
  - Added the data set data.items, Multiple-Choice, Dichotomous, and
    Polytomous Item Data, to the package.
  - Added the option opdyke to the functions item.cfa(), item.invar(),
    multilevel.cfa(), multilevel.invar()to compute the discrepancy
    between model-implied and observed correlation expressed in terms of
    the relative percentile of an Opdyke distribution (McNeish, 2025).

Minor features and improvements

  - Added the arguments test and se to the functions item.cfa() and
    multilevel.cfa().
  - Added the arguments se to the function multilevel.omega() to save
    computation time by specifying se = "none".
  - The function df.subset() can subset rows based on variables that
    were not selected, e.g., df.subset(iris, Sepal.Length, subset =
    Species == "setosa").
  - Added 'Details' in the help page of the functions multilevel.cfa()
    and multilevel.omega().
  - Added the argument r.digits to the functions item.alpha(),
    item.omega(), and multilevel.omega()
  - Added the argument exact, ml, color, and style to the function
    cor.matrix().
  - The function cor.matrix computes p-values also for the tetrachoric
    and polychoric correlation coefficient.
  - Added the character summary to the argument print in the function
    multilevel.cor()
  - Added the new goodness-of-fit index (GFI, Maydeu-Olivares et
    al. 2024) to the output of the function item.cfa(), item.invar(),
    modcomp(), multilevel.cfa(), and multilevel.invar()
  - Added the options "WLSMVS" and "ULSMV" to the argument estimator in
    the function item.cfa() item.invar(), and item.noninvar().
  - Added the options "mean.var.adjusted.corrected" and
    "scaled.shifted.corrected" to the argument test in the function
    item.cfa().

User-visible changes

  - Changed the default setting of the argument print in the function
    multilevel.omega to omega.
  - Changed the default setting of the argument print in the function
    multilevel.cor to cor.
  - Renamed Yuan-Bentler to Asymptotic Yuan-Bentler in the summary table
    of the functions item.cfa() and multilevel.cfa() when specifying
    test = yuan.bentler.mplus, i.e., default when specifying estimator =
    MLR.
  - Renamed the argument R in the functions boot.bs, ci.cor, ci.mean,
    ci.median, ci.prop, ci.var, ci.sd, mplus.lca, and summa to nrep.
  - Revised the help pages for the functions item.alpha, item.omega,
    item.reverse, and item.score.
  - Removed the arguments type and added the argument ordered in the
    function item.alpha.
  - Removed the argument sig from the function multilevel.cor() and
    multilevel.cor() and added the arguments color, and style.
  - Added the arguments color, and style to the function item.cfa(),
    item.invar() multilevel.cfa(), and multilevel.invar().
  - Removed the arguments print, freq, hypo, descript, epsilon, effsize,
    posthoc, order, split, tri, table, and horiz from the function
    print.misty.object().
  - Removed the arguments write and tri from the function
    write.result().
  - Added a note about the sample size when using pairwise deletion and
    residual covariances to the output of the item.alpha() and
    item.omega() function.

                 Changes in version 0.8.2 (2026-05-16)                  

New features

  - New function modcomp() for model comparison by providing a table
    with fit indices for lavaan model objects, information criteria, and
    likelihood ratio or F-test for various model objects, e.g., from the
    lm(), lme(), nlme(), lmer(), and glmer() function. .
  - New function boot.bs() for perfoming Bollen-Stine bootstrapping with
    incomplete data.
  - New function sim.lavaan() for generating simulated data from a
    lavaan model syntax with unstandardized and standardized parameters.
  - New function item.dfi() for computing simulation-based dynamic fit
    index cutoffs for evaluating confirmatory factor models based on
    multivariate normal, multivariate non-normal, likert-type, and
    categorical data.

Minor features and improvements

  - The function write.result() supports result objects from the
    functions aov.b(), test.levene(), test.welch().

User-visible changes

  - Removed the option aov from the method argument in the
    multilevel.icc() and multilevel.descript() function.
  - Moved the package data.table from Suggests to Imports.
  - Changed the default setting of the argument hypo and descript in the
    functions aov.b, test.levene, test.welch, test.t, test.z to FALSE.
  - Changed the default setting of the argument weighted in the
    functions aov.b and test.t to TRUE.
  - Changed the default setting of the argument epsilon in the function
    aov.w to FALSE.
  - Removed the numerous plotting arguments from the functions aov.b,
    aov.w, ci.cor, ci.mean, ci.median, ci.var, ci.sd, test.levene,
    test.t, test.welch, amd test.z.
  - Renamed columns in the output of the functions aov.b, aov.w,
    test.levene from Df, Sum Sq, Mean Sq, F value, and Pr(>F) to df, SS,
    MSS, F, and p.

                 Changes in version 0.8.1 (2026-03-06)                  

New features

  - New function item.noninvar() for computing the effect size measure
    dMACS by Nye and Drasgow (2011) and signed dMACS by Nye et al.
    (2019) for evaluating the magnitude and the direction of
    between-group and longitudinal measurement non-invariance for
    continuous and ordered categorical items.
  - New function difftest.chibarsq() for perfoming the chi-bar-square
    difference test to compare the random intercept cross-lagged panel
    model (RI-CLPM) and traditional cross-lagged panel model (CLPM) as
    discussed in Hamaker et al. (2015).

Minor features and improvements

  - Added the characters randeff and varcor to the argument print of the
    function summa().
  - The function coef.robust() computes cluster-robust standard errors
    for multilevel and linear mixed-effects models estimated by using
    the lme() function from the nlme package.
  - The function summa() prints a summary of the result object returned
    by the function lme() from the nlme package.

User-visible changes

  - Added the arguments write to the function write.result().
  - Added the arguments horiz to the function print.misty.object().

                 Changes in version 0.8.0 (2026-01-18)                  

New features

  - The function item.invar() evaluates between-group and longitudinal
    measurement invariance for measurement models with ordered
    categorical indicators utilizing the Wu and Estabrook (2016)
    approach to model identification.

Minor features and improvements

  - The function center provides a two-step latent mean centering
    approach.
  - The summary result tables created by the function mplus.lca.summa
    also provides the approximate weight of evidence criterion (AWE),
    approximate correct model probability (cmP), approximate Bayes
    factors (aBF), average posterior class probability (AvePP), odds of
    correct classification ratio (OCC), and Cohen's d to quantify class
    separation.
  - The function mplus.lca.summa also provides class-specific item
    response probabilities of the indicator variables and plots for LCA
    with ordered or unordered categorical indicator variables.
  - The argument partial in the function item.invar was modified to
    enable freeing parameters in specific groups when evaluating
    between-group measurement invariance based on more than two groups.
  - Added the arguments boot and R for requesting (bias-corrected)
    bootstrap confidence intervals to the function mplus.lca.
  - Added the argument constr.var to impose inequality constraints for
    the variance parameters at the between level to the function
    multilevel.cor.
  - Added the argument lavaan.run to the function item.invar.

Bug fix

  - Fixed a bug in the function center(), which caused an error message
    when centering a L2 predictor in three-level data within L3
    clusters.

User-visible changes

  - Added a horizontal line under the table header of output providing
    tables.
  - Revised the help page of the center() function.
  - The function multilevel.icc() rounds ICCs smaller than
    .Machine$double.eps^0.5 to 0.
  - Changed the default setting of the argument digits in the function
    mplus.lca.summa to 0.
  - Changed the default setting of the argument missing in the function
    item.alpha to listwise.
  - Rearranged the order of the arguments for the function mplus.lca,
    changed the default setting of the argument sort.p to FALSE, and the
    default setting of the argument output to c("SVALUES", "CINTERVAL",
    "TECH11").
  - Removed the argument width in the function mplus.lca.summa()and
    added the arguments width.ind, width.nclass, and height.categ.
  - Removed the argument within in the function multilevel.cor(), i.e.,
    the function automatically identifies variables that are measured at
    the within level and modeled only at the within level.
  - Removed the argument sig in the function cor.matrix and
    multilevel.cor, and added the arguments color and style.

                 Changes in version 0.7.6 (2025-10-27)                  

User-visible changes

  - Renamed the function result.lca() to mplus.lca.summa().
  - Changed the default setting of the argument print in the function
    indirect to mc.
  - Removed the argument between in the function multilevel.cor(), i.e.,
    the function automatically identifies variables that are measured at
    the between level.

Bug fix

  - Function item.cfa() and multilevel.cfa() adapted to the recent
    changes in the lavaan package (requested by Yves Rosseel).

                 Changes in version 0.7.5 (2025-09-06)                  

New features

  - New function robust.lmer() to estimate a multilevel and linear
    mixed-effects model based on a robust estimation method using the
    rlmer() function from the robustlmm package.

Minor features and improvements

  - The function summa supports result objects from the rlmer() function
    from the robustlmm package.
  - The function summa computes confidence intervals based on
    heteroscedasticity-consistent standard errors when specifying robust
    = TRUE.
  - The function summa computes cluster-robust standard errors for
    multilevel and linear mixed-effects model when specifying robust =
    TRUE.
  - The function coeff.robust computes cluster-robust standard errors
    for (generalized) linear models that are robust to the violation of
    the observation independence due to clustering.
  - The function coeff.robust computes cluster-robust standard errors
    for multilevel and linear mixed-effects model that are robust to the
    violation of the homoscedasticity assumption.

User-visible changes

  - Changed the column names of the coefficient table in the function
    coeff.std and coeff.robust from Std. Error, z value, t value ,
    Pr(>|z|), and Pr(>|t|) to Std. Error, z, t , p, and p.
  - Changed the default setting of the argument digits in the function
    coeff.robust to 2.
  - Removed the argument adjust from the function mplus.lca.summa.

                 Changes in version 0.7.4 (2025-08-18)                  

New features

  - New function write.data() and write.data1() to write data files in
    CSV, DAT, TXT, SPSS, Excel, or Stata DTA format.
  - New functions df.long() and df.wide() to reshape data frames between
    'wide' and 'long' format.
  - New function summa() for printing a summary output of the object
    returned by the functions lm() and lmer() from the lme4 package.

Minor features and improvements

  - The function descript prints the number of unique elements nUQ after
    omitting missing values.
  - Added the arguments write, append and output to the function uniq.
  - Added the arguments categ and adjust to the function na.auxiliary
    that allows specifying categorical variables to compute Phi
    coefficient and Cramer's V.
  - Added the argument optim.switch to the function multilevel.cor.
  - The function multilevel.cor computes the within-group correlation
    (or between-group correlation) in the presence of only one
    between-group (or within-group) variable.
  - The function check.resid performs residual diagnostics for linear
    mixed-effects models estimated by using the lmer() function.

Bug fix

  - Fixed a bug in the function multilevel.icc(), computation of the
    ICC(2) was wrong (thanks to Ammar Ansari and Tetsuhiro Yamada).

User-visible changes

  - Changed the column name pNA to %NA in the output of the functions
    ci.cor, ci.mean, ci.median, ci.mean.w, ci.prop, ci.var, ci.sd,
    descript, item.alpha, item.cfa, item.omega, multilevel.cfa,
    multilevel.omega, and na.descript.
  - Changed the column names nObs and %Obs to nOb and %Ob in the
    frequency table of the na.descript() function.
  - Functions descript(), item.alpha(), item.cfa, item.omega(),
    multilevel.cfa, and multilevel.omega print the column %NA with zero
    digits if all variables have no missing values.
  - Changed the column names from SD.x and SD.y to SDx and SDyin the
    output of the std.coef() function.
  - Changed the default setting of the argument digits in the function
    std.coef to 2.
  - Changed the column name pval to p in the output of the functions
    aov.b, aov.w, na.test, test.t, test.welch, and test.z.
  - Renamed the functions robust.coef(), std.coef(), and rwg.lindell()
    to coeff.robust(), coeff.std() and cluster.rwg().
  - Removed the . (dot) operator from the function df.subset().

                 Changes in version 0.7.3 (2025-07-07)                  

Minor features and improvements

  - The function descript prints the percentage of observations at the
    minimum (%Min) and at the maximum (%Max).

User-visible changes

  - The function multilevel.cor estimates the model without standard
    errors to speed up model estimation when specifying sig = FALSE
    (default setting).

Bug fix

  - Fixed a bug in the function plot.misty.object() for plotting results
    of the na.pattern() function (thanks Teun van den Brand).

                 Changes in version 0.7.2 (2025-05-20)                  

New features

  - New function uniq for extracting unique elements in a vector,
    matrix, or data frame and function uniq.n for counting the number of
    unique elements in a vector or for each column in a matrix or data
    frame.

Minor features and improvements

  - The function std.coef computes standardized coefficients for
    multilevel and linear mixed-effects models estimated by using the
    lmer or lme function from the lme4 or nlme package.
  - The function item.alpha computes coefficient alpha by estimating an
    essentially tau-equivalent measurement model allowing full
    information maximum likelihood (FIML) method for missing data
    handling by specifying missing = "fiml" along with estimator = "ML".
  - Added the argument rescov to the function item.alpha for specifying
    residual covariances when computing coefficient alpha.

Bug fix

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

User-visible changes

  - Changed the default setting of the argument print in the functions
    item.alpha and item.omega to alpha and omega.
  - Removed the argument na.omit in the function item.omega and added
    the arguments estimator and missing.

                 Changes in version 0.7.1 (2025-03-10)                  

New features

  - New function plot.misty.object() for plotting a misty object.

Minor features and improvements

  - Added the argument factor.labels to the function df.head and
    df.tail.

  - Added the arguments filename, width, height, units, and dpi to the
    functions aov.b, aov.w, multilevel.r2, multilevel.r2.manual,
    na.pattern, test.levene, test.t, test.welch, and test.z.

  - The function df.rename can rename columns in a matrix or variables
    in a data frame using old_name = new_name and using the functions
    toupper, tolower, gsub, and sub similar to the rename function in
    the dplyr package.

Bug fix

  - Fixed a bug in the function multilevel.icc(), computation of the
    ICC(1) at Level 2 was wrong in case of a three-level data when
    specifying type = "1b" (thanks to David S. DeGarmo).
  - Fixed a bug in the function center(), within-cluster centering of a
    Level-2 predictor variable in three-level was wrong (thanks to
    Stefanos Mastrotheodoros).
  - Fixed a bug in the functions df.head() and df.tail(), function could
    not handle date and times.

User-visible changes

  - The argument subset in the function df.subset is specified without
    quotation marks in line with the argument subset in the function
    subset function.
  - Moved the argument data in the functions as.na, na.as, center,
    ci.cor, ci.cor, ci.mean, ci.median, ci.mean.w, ci.var, ci.sd,
    cluster.scores, coding, cor.matrix, crosstab, descript,
    df.duplicated, df.unique, df.move, df.subset, effsize, freq,
    item.alpha, item.cfa, item.invar, item.omega, item.reverse,
    item.scores, lagged, multilevel.cfa, multilevel.cor,
    multilevel.descript, multilevel.icc, multilevel.invar,
    multilevel.omega, na.auxiliary, na.coverage, na.descript,
    na.indicator, na.pattern, na.prop, na.test, rec, rwg.lindell,
    skewness to the first position.
  - Renamed the argument x in the functions df.check, df.head,
    df.rename, df.sort to data.
  - Renamed the argument x in the function multilevel.fit to model.
  - Renamed the arguments alpha, ci.plot, plot.point, saveplot in the
    functions ci.cor, ci.mean, ci.median, ci.prop, ci.var, and ci.sd to
    hist.alpha, confint, point and filename.
  - Renamed the argument fill.col in the functions na.pattern to color.
  - Renamed the argument file in the functions blimp.plot, mplus.plot,
    and na.pattern to filename.
  - Removed the argument saveplot from the functions na.pattern.
  - Changed the default setting of the argument na in the functions
    na.indicator(), to 1.

                 Changes in version 0.7.0 (2025-02-02)                  

New features

  - New function ci.cor() for computing and potting Fisher z' confidence
    interval for the Pearson product-moment correlation coefficient
    adjusted via sample joint moments method or via approximate
    distribution method (Bishara et al., 2018), Spearman's rank-order
    correlation coefficient with Fieller et al. (1957) standard error,
    Bonett and Wright (2000) standard error or rank-based inverse normal
    (RIN) transformation, and Kendall's Tau-b, and Kendall-Stuart's
    Tau-c. The function also supports five types of bootstrap confidence
    intervals
  - New function chr.trunc() for truncating a character vector, so that
    the number of characters of each element of the character vector is
    always less than or equal to the specified width.
  - New function df.head() and df.tail() for printing the first or last
    rows of a data frame and displaying only as many columns as fit on
    the console.
  - New function df.check() which is a wrapper function around the
    functions dim(), names(), df.head(), and df.tail().

Minor features and improvements

  - The functions skewness and kurtosis can also compute Mardia's
    multivariate skewness and kurtosis.
  - The functions ci.mean, ci.median, ci.prop, ci.var, and ci.sd can
    also compute and plot bootstrap confidence intervals.
  - Added the argument sample to the function descript.
  - Added the argument append to the function check.outlier.
  - Added the arguments sep and dec to the function read.data.
  - Added the options gray1, gray2, and gray3 to the argument color of
    the function chr.color.

Bug fix

  - Fixed a bug in the function blimp.print(), function printed error
    messages.
  - Fixed bugs in functions that could not handle a tibble as input
    (thanks to David S. DeGarmo).

User-visible changes

  - Changed the arguments nrow, ncol and scales into facet.nrow,
    facet.ncol and facet.scales in the functions blimp.plot() and
    mplus.plot().
  - Changed the argument error.width into errorbar.width in the
    functions aov.b(), aov.w(), result.lca(), test.t() and test.z().
  - Changed the argument line.size and line.type into linewidth and
    linetype in the functions test.t() and test.z().
  - Changed the arguments line.color1, line.color2, line.type1,
    line.type2, line.width1, line.width2, bar.color, axis.size,
    strip.size, xlimits, and ylimits into line.col1, line.col2,
    linetype1, linetype2, linewidth1, linewidth2, bar.col,
    axis.text.size, strip.text.size, xlim, and ylim in the function
    check.resid().
  - Changed the default setting of the argument line in the functions
    aov.w(), to FALSE.
  - Merged help pages for the functions size.mean, size.prop and
    size.cor into one help page.
  - Changed the default setting of the argument missing in the functions
    multilevel.cfa(), to "fiml".
  - Changed the default setting of the argument estimator in the
    functions multilevel.cor(), to "MLR".
  - Changed the default setting of the argument na in the functions
    na.indicator(), to 1.

                 Changes in version 0.6.8 (2024-10-24)                  

New features

  - 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 missing data
    handling 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.

User-visible changes

  - Changed the default setting of the argument print in the functions
    na.test(), to little.

Bug fix

  - 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.

                 Changes in version 0.6.7 (2024-09-18)                  

Minor features and improvements

  - 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.

User-visible changes

  - 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().

Bug fix

  - 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.

                 Changes in version 0.6.6 (2024-08-25)                  

New features

  - 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 functionblimp.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.

Minor features and improvements

  - 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)..

User-visible changes

  - 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.

Bug fix

  - 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).

                 Changes in version 0.6.5 (2024-06-29)                  

Minor features and improvements

  - Updated the function mplus.run() according to the latest version of
    the function runModels() in the MplusAutomation package.

Bug fix

  - Fixed a bug in the function mplus.print(), function did not print
    result of a misty.object of type mplus.

                 Changes in version 0.6.4 (2024-06-26)                  

New features

  - 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.

User-visible changes

  - 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().

Bug fix

  - Fixed a bug in the function test.welch(), function did not print
    post hoc tests when specifying posthoc = TRUE.

                 Changes in version 0.6.3 (2024-05-14)                  

Bug fix

  - 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).

Minor features and improvements

  - 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".

                 Changes in version 0.6.2 (2024-02-05)                  

Bug fix

  - 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.

User-visible changes

  - 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.

Minor features and improvements

  - Added the argument na to the function read.mplus().

                 Changes in version 0.6.1 (2024-01-19)                  

User-visible changes

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

Bug fix

  - Fixed a bug in the function freq(), function did not provide an
    output.

                 Changes in version 0.6.0 (2024-01-12)                  

New features

  - 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.

Minor features and improvements

  - 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.

User-visible changes

  - 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().

Bug fix

  - Fixed a bug in the function multilevel.descript(), function led to a
    node stack overflow.

                 Changes in version 0.5.4 (2023-11-14)                  

New features

  - New function shift() to compute lagged or leading values of a
    vector.

Bug fix

  - Fixed a bug in the function libraries(), version of the packages
    were not correctly displayed.

                 Changes in version 0.5.3 (2023-09-17)                  

Bug fix

  - Fixed a bug in the function test.welch(), to remove errors for
    r-devel from a recent change in r-devel.

                 Changes in version 0.5.2 (2023-08-24)                  

Minor features and improvements

  - Added the argument group.ind to the function result.lca() to
    specify. latent class indicators as grouping variable in the bar
    charts.

                 Changes in version 0.5.1 (2023-08-22)                  

Minor features and improvements

  - 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.

Bug fix

  - Fixed a bug in the function dominance.manual(), function provided
    the wrong rank ordering.

User-visible changes

  - Renamed the functions mplus.lpa() and results.lpa() to mplus.lca()
    and results.lca().

                 Changes in version 0.5.0 (2023-08-07)                  

New features

  - 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.

Minor features and improvements

  - 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.

User-visible changes

  - 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.

                 Changes in version 0.4.12 (2023-07-08)                 

User-visible changes

  - Removed the R package r2mlm from the Imports field in the
    DESCRIPTION due to dependencies issues.

Minor features and improvements

  - 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.

                 Changes in version 0.4.11 (2023-06-10)                 

New features

  - 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.

Minor features and improvements

  - 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.

User-visible changes

  - 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.

                 Changes in version 0.4.10 (2023-05-18)                 

Bug fix

  - Fixed a bug in the function multilevel.cor(), which caused an error
    message (thanks to Richard Janzen).

                 Changes in version 0.4.9 (2023-05-02)                  

New features

  - 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

Minor features and improvements

  - 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 .

User-visible changes

  - 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().

Bug fix

  - 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.

                 Changes in version 0.4.8 (2023-03-10)                  

New features

  - 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.

Minor features and improvements

  - Functions center(), cluster.scores(), rec(), and item.reverse() can
    be applied to more than one variable at once.

                 Changes in version 0.4.7 (2023-01-06)                  

New features

  - 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.

Minor features and improvements

  - 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.

User-visible changes

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

Bug fix

  - Fixed a bug in the function test.t(), result table provided by the
    function did not display the confidence interval correctly.

                 Changes in version 0.4.6 (2022-06-08)                  

New features

  - New function aov.b() for performing between-subject analysis of
    variance including Tukey HSD post hoc test for multiple comparison.

Minor features and improvements

  - 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().

                 Changes in version 0.4.5 (2022-04-29)                  

New features

  - New function item.cfa() for conducting confirmatory factor analysis
    using the R package lavaan.

Minor features and improvements

  - 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.

User-visible changes

  - 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 missing data handling.

Bug fix

  - 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".

                 Changes in version 0.4.4 (2022-02-24)                  

New features

  - 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.

Minor features and improvements

  - 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.

User-visible changes

  - 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.

Bug fix

                 Changes in version 0.4.3 (2021-09-30)                  

User-visible changes

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

Bug fix

  - 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.

                 Changes in version 0.4.2 (2021-08-19)                  

New features

  - 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.

Minor features and improvements

  - 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.

User-visible changes

  - 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().

Bug fix

  - Fixed a bug in the function cor.matrix(), function did not print
    sample sizes when specifying a grouping variable and using listwise
    deletion.

                 Changes in version 0.4.1 (2021-06-07)                  

Minor features and improvements

  - 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.

User-visible changes

  - 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).

Bug fix

  - 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.

                 Changes in version 0.4.0 (2021-05-13)                  

New features

  - 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.

Minor features and improvements

  - 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.

User-visible changes

  - 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.

Bug fix

  - 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".

                 Changes in version 0.3.2 (2020-06-08)                  

New features

  - 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.

Bug fix

  - Fixed a bug in the function read.xlsx(), default setting of the
    argument progress was wrong.

User-visible changes

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

                 Changes in version 0.3.1 (2020-04-25)                  

New features

  - New function z.test() for performing one sample, two sample, and
    paired sample z-test.

Bug fix

  - Function omega.coef() does not access internal slots of a fitted
    lavaan object anymore (requested by Yves Rosseel).

User-visible changes

  - 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.

                 Changes in version 0.3.0 (2020-04-06)                  

New features

  - 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).

Minor features and improvements

  - 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.

User-visible changes

  - 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()

Bug fix

  - 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.

                 Changes in version 0.2.2 (2020-02-26)                  

New features

  - 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.

Bug fix

  - 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.
