| aov.b | Between-Subject Analysis of Variance |
| aov.w | Repeated Measures Analysis of Variance (Within-Subject ANOVA) |
| as.na | Replace User-Specified Values With Missing Values or Missing Values With User-Specified Values |
| center | Centering Predictor Variables in Single-Level and Multilevel Data |
| check.collin | Collinearity Diagnostics |
| check.outlier | Statistical Measures for Leverage, Distance, and Influence |
| check.resid | Residual Diagnostics |
| chr.gsub | Multiple Pattern Matching And Replacements |
| chr.omit | Omit Strings |
| chr.trim | Trim Whitespace from String |
| ci.mean | Confidence Interval for the Arithmetic Mean and Median |
| ci.mean.diff | Confidence Interval for the Difference in Arithmetic Means |
| ci.mean.diff.default | Confidence Interval for the Difference in Arithmetic Means |
| ci.mean.diff.formula | Confidence Interval for the Difference in Arithmetic Means |
| ci.mean.w | Within-Subject Confidence Interval for the Arithmetic Mean |
| ci.median | Confidence Interval for the Arithmetic Mean and Median |
| ci.prop | Confidence Interval for Proportions |
| ci.prop.diff | Confidence Interval for the Difference in Proportions |
| ci.prop.diff.default | Confidence Interval for the Difference in Proportions |
| ci.prop.diff.formula | Confidence Interval for the Difference in Proportions |
| ci.sd | Confidence Interval for the Variance and Standard Deviation |
| ci.var | Confidence Interval for the Variance and Standard Deviation |
| cluster.scores | Cluster Scores |
| coding | Coding Categorical Variables |
| cohens.d | Cohen's d |
| cohens.d.default | Cohen's d |
| cohens.d.formula | Cohen's d |
| cor.matrix | Correlation Matrix |
| crosstab | Cross Tabulation |
| descript | Descriptive Statistics |
| df.duplicated | Extract Duplicated or Unique Rows |
| df.merge | Merge Multiple Data Frames |
| df.move | Move Variable(s) in a Data Frame |
| df.rbind | Combine Data Frames by Rows, Filling in Missing Columns |
| df.rename | Rename Columns in a Matrix or Variables in a Data Frame |
| df.sort | Data Frame Sorting |
| df.subset | Subsetting Data Frames |
| df.unique | Extract Duplicated or Unique Rows |
| dominance | Dominance Analysis |
| dominance.manual | Dominance Analysis, Manually Inputting a Correlation Matrix |
| effsize | Effect Sizes for Categorical Variables |
| freq | Frequency Table |
| indirect | Confidence Intervals for the Indirect Effect |
| item.alpha | Coefficient Alpha and Item Statistics |
| item.cfa | Confirmatory Factor Analysis |
| item.invar | Between-Group and Longitudinal Measurement Invariance Evaluation |
| item.omega | Coefficient Omega, Hierarchical Omega, and Categorical Omega |
| item.reverse | Reverse Code Scale Item |
| item.scores | Compute Scale Scores |
| kurtosis | Skewness and Kurtosis |
| lagged | Create Lagged Variables |
| libraries | Load and Attach Multiple Packages |
| mplus.lca | Mplus Model Specification for Latent Class Analysis |
| multilevel.cfa | Multilevel Confirmatory Factor Analysis |
| multilevel.cor | Within-Group and Between-Group Correlation Matrix |
| multilevel.descript | Multilevel Descriptive Statistics for Two-Level and Three-Level Data |
| multilevel.fit | Simultaneous and Level-Specific Multilevel Model Fit Information |
| multilevel.icc | Intraclass Correlation Coefficient, ICC(1) and ICC(2) |
| multilevel.indirect | Confidence Interval for the Indirect Effect in a 1-1-1 Multilevel Mediation Model |
| multilevel.invar | Cross-Level Measurement Invariance Evaluation |
| multilevel.omega | Multilevel Composite Reliability |
| multilevel.r2 | R-Squared Measures for Multilevel and Linear Mixed Effects Models |
| multilevel.r2.manual | R-Squared Measures for Multilevel and Linear Mixed Effects Models by Rights and Sterba (2019), Manually Inputting Parameter Estimates |
| na.as | Replace User-Specified Values With Missing Values or Missing Values With User-Specified Values |
| na.auxiliary | Auxiliary variables analysis |
| na.coverage | Variance-Covariance Coverage |
| na.descript | Descriptive Statistics for Missing Data in Single-Level, Two-Level and Three-Level Data |
| na.indicator | Missing Data Indicator Matrix |
| na.pattern | Missing Data Pattern |
| na.prop | Proportion of Missing Data for Each Case |
| na.test | Little's Missing Completely at Random (MCAR) Test |
| print.misty.object | Print misty.object object |
| read.dta | Read Stata DTA File |
| read.mplus | Read Mplus Data File and Variable Names |
| read.sav | Read SPSS File |
| read.xlsx | Read Excel File |
| rec | Recode Variable |
| restart | Restart R Session |
| result.lca | Summary Result Table and Grouped Bar Charts for Latent Class Analysis Estimated in Mplus |
| robust.coef | Unstandardized Coefficients with Heteroscedasticity-Consistent Standard Errors |
| run.mplus | Run Mplus Models |
| rwg.lindell | Lindell, Brandt and Whitney (1999) r*wg(j) Within-Group Agreement Index for Multi-Item Scales |
| script.close | Open, Close and Save R Script in RStudio |
| script.copy | Save Copy of the Current Script in RStudio |
| script.new | Open new R Script, R Markdown script, or SQL Script in RStudio |
| script.open | Open, Close and Save R Script in RStudio |
| script.save | Open, Close and Save R Script in RStudio |
| setsource | Set Working Directory to the Source File Location |
| size.cor | Sample Size Determination for Testing Pearson's Correlation Coefficient |
| size.mean | Sample Size Determination for Testing Arithmetic Means |
| size.prop | Sample Size Determination for Testing Proportions |
| skewness | Skewness and Kurtosis |
| std.coef | Standardized Coefficients |
| test.levene | Levene's Test for Homogeneity of Variance |
| test.t | t-Test |
| test.t.default | t-Test |
| test.t.formula | t-Test |
| test.welch | Welch's Test |
| test.z | z-Test |
| test.z.default | z-Test |
| test.z.formula | z-Test |
| write.dta | Write Stata DTA File |
| write.mplus | Write Mplus Data File |
| write.result | Write Results of a misty Object into an Excel file |
| write.sav | Write SPSS File |
| write.xlsx | Write Excel File |