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misty (version 0.6.5)

Miscellaneous Functions 'T. Yanagida'

Description

Miscellaneous functions for (1) data management (e.g., grand-mean and group-mean centering, coding variables and reverse coding items, scale and cluster scores, reading and writing Excel and SPSS files), (2) descriptive statistics (e.g., frequency table, cross tabulation, effect size measures), (3) missing data (e.g., descriptive statistics for missing data, missing data pattern, Little's test of Missing Completely at Random, and auxiliary variable analysis), (4) multilevel data (e.g., multilevel descriptive statistics, within-group and between-group correlation matrix, multilevel confirmatory factor analysis, level-specific fit indices, cross-level measurement equivalence evaluation, multilevel composite reliability, and multilevel R-squared measures), (5) item analysis (e.g., confirmatory factor analysis, coefficient alpha and omega, between-group and longitudinal measurement equivalence evaluation), and (6) statistical analysis (e.g., confidence intervals, collinearity and residual diagnostics, dominance analysis, between- and within-subject analysis of variance, latent class analysis, t-test, z-test, sample size determination).

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Version

Install

install.packages('misty')

Monthly Downloads

2,326

Version

0.6.5

License

MIT + file LICENSE

Maintainer

Takuya Yanagida

Last Published

June 29th, 2024

Functions in misty (0.6.5)

Multiple Pattern Matching And Replacements

Between-Subject Analysis of Variance

Centering Predictor Variables in Single-Level and Multilevel Data

Statistical Measures for Leverage, Distance, and Influence

Residual Diagnostics

Replace User-Specified Values With Missing Values or Missing Values With User-Specified Values

Collinearity Diagnostics

Repeated Measures Analysis of Variance (Within-Subject ANOVA)

Multiple Pattern Matching

Confidence Interval for the Variance and Standard Deviation

Confidence Interval for the Arithmetic Mean and Median

Coding Categorical Variables

Trim Whitespace from String

Within-Subject Confidence Interval for the Arithmetic Mean

Confidence Interval for the Difference in Arithmetic Means

Confidence Interval for Proportions

Confidence Interval for the Difference in Proportions

Combine Data Frames by Rows, Filling in Missing Columns

Rename Columns in a Matrix or Variables in a Data Frame

Merge Multiple Data Frames

Descriptive Statistics

Extract Duplicated or Unique Rows

Correlation Matrix

Cross Tabulation

Move Variable(s) in a Data Frame

Data Frame Sorting

Subsetting Data Frames

Confidence Intervals for the Indirect Effect

Coefficient Omega, Hierarchical Omega, and Categorical Omega

Reverse Code Scale Item

dominance.manual

Dominance Analysis, Manually Inputting a Correlation Matrix

Effect Sizes for Categorical Variables

Dominance Analysis

Coefficient Alpha and Item Statistics

Confirmatory Factor Analysis

Between-Group and Longitudinal Measurement Invariance Evaluation

Frequency Table

Multilevel Confirmatory Factor Analysis

Create Lagged Variables

Create, Run, and Print Mplus Models

Within-Group and Between-Group Correlation Matrix

Compute Scale Scores

Mplus Model Specification for Latent Class Analysis

Run Mplus Models

Print Mplus Output

Load and Attach Multiple Packages

Mplus Input Updating

Intraclass Correlation Coefficient, ICC(1) and ICC(2)

Auxiliary variables analysis

Simultaneous and Level-Specific Multilevel Model Fit Information

multilevel.indirect

Confidence Interval for the Indirect Effect in a 1-1-1 Multilevel Mediation Model

multilevel.descript

Multilevel Descriptive Statistics for Two-Level and Three-Level Data

Variance-Covariance Coverage

multilevel.r2.manual

R-Squared Measures for Multilevel and Linear Mixed Effects Models by Rights and Sterba (2019), Manually Inputting Parameter Estimates

R-Squared Measures for Multilevel and Linear Mixed Effects Models

multilevel.omega

Multilevel Composite Reliability

multilevel.invar

Cross-Level Measurement Invariance Evaluation

Missing Data Pattern

Read Excel File

Descriptive Statistics for Missing Data in Single-Level, Two-Level and Three-Level Data

Read Stata DTA File

Little's Missing Completely at Random (MCAR) Test

Missing Data Indicator Matrix

Read Mplus Data File and Variable Names

print.misty.object

Print misty.object object

Proportion of Missing Data for Each Case

Summary Result Table and Grouped Bar Charts for Latent Class Analysis Estimated in Mplus

Open new R Script, R Markdown script, or SQL Script in RStudio

Lindell, Brandt and Whitney (1999) r*wg(j) Within-Group Agreement Index for Multi-Item Scales

Set Working Directory to the Source File Location

Open, Close and Save R Script in RStudio

Save Copy of the Current Script in RStudio

Recode Variable

Sample Size Determination for Testing Pearson's Correlation Coefficient

Restart R Session

Unstandardized Coefficients with Heteroscedasticity-Consistent Standard Errors

Write Stata DTA File

Sample Size Determination for Testing Arithmetic Means

Sample Size Determination for Testing Proportions

Standardized Coefficients

Levene's Test for Homogeneity of Variance

Write Mplus Data File

Skewness and Kurtosis

Write Results of a misty Object into an Excel file

Write SPSS File

Write Excel File