Learn R Programming
⚠️There's a newer version (0.7.6) of this package.Take me there.

misty (version 0.7.5)

Miscellaneous Functions 'T. Yanagida'

Description

Miscellaneous functions for (1) data handling (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), (6) statistical analysis (e.g., bootstrap 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), and (7) functions to interact with 'Blimp' and 'Mplus'.

Copy Link

Version

Install

install.packages('misty')

Monthly Downloads

3,091

Version

0.7.5

License

MIT + file LICENSE

Maintainer

Takuya Yanagida

Last Published

September 6th, 2025

Functions in misty (0.7.5)

blimp

Create, Run, and Print Blimp Models
blimp.run

Run Blimp Models
check.collin

Collinearity Diagnostics
blimp.print

Print Blimp Output
center

Centering Predictor Variables in Single-Level and Multilevel Data
aov.w

Repeated Measures Analysis of Variance (Within-Subject ANOVA)
blimp.update

Blimp Input Updating
blimp.bayes

Blimp Summary Measures, Convergence and Efficiency Diagnostics
blimp.plot

Blimp Trace Plots and Posterior Distribution Plots
aov.b

Between-Subject Analysis of Variance
chr.grep

Multiple Pattern Matching
check.resid

Residual Diagnostics for Linear, Multilevel and Mixed-Effects Models
check.outlier

Statistical Measures for Leverage, Distance, and Influence
ci.mean

(Bootstrap) Confidence Intervals for Arithmetic Means and Medians
chr.omit

Omit Strings
chr.gsub

Multiple Pattern Matching And Replacements
ci.cor

(Bootstrap) Confidence Intervals for Correlation Coefficients
chr.trunc

Truncate a Character Vector to a Maximum Width
chr.trim

Trim Whitespace from String
chr.color

Colored and Styled Terminal Output Text
cluster.rwg

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

Within-Subject Confidence Interval for the Arithmetic Mean
ci.prop

(Bootstrap) Confidence Intervals for Proportions
ci.mean.diff

Confidence Interval for the Difference in Arithmetic Means
cluster.scores

Cluster Scores
coeff.robust

Heteroscedasticity-Consistent and Cluster-Robust Standard Errors
coding

Coding Categorical Variables
ci.prop.diff

Confidence Interval for the Difference in Proportions
ci.var

(Bootstrap) Confidence Intervals for Variances and Standard Deviations
clear

Clear Console in RStudio
df.head

Print the First and Last Rows of a Data Frame
descript

Descriptive Statistics
df.duplicated

Extract Duplicated or Unique Rows
cohens.d

Cohen's d
df.check

Data Check
df.long

Converting Data Frames Between 'Wide' and 'Long' Format
crosstab

Cross Tabulation
cor.matrix

Correlation Matrix
coeff.std

Standardized Coefficients for Linear, Multilevel and Mixed-Effects Models
df.merge

Merge Multiple Data Frames
df.sort

Data Frame Sorting
freq

Frequency Table
df.subset

Subsetting Data Frames
effsize

Effect Sizes for Categorical Variables
df.rbind

Combine Data Frames by Rows, Filling in Missing Columns
df.rename

Rename Columns in a Matrix or Variables in a Data Frame
dominance

Dominance Analysis
dominance.manual

Dominance Analysis, Manually Inputting a Correlation Matrix
df.move

Move Variable(s) in a Data Frame
indirect

Confidence Intervals for the Indirect Effect
libraries

Load and Attach Multiple Packages
item.scores

Scale Scores
mplus

Create, Run, and Print Mplus Models
item.cfa

Confirmatory Factor Analysis
item.omega

Coefficient Omega, Hierarchical Omega, and Categorical Omega
mplus.bayes

Mplus Summary Measures, Convergence and Efficiency Diagnostics
item.invar

Between-Group and Longitudinal Measurement Invariance Evaluation
lagged

Create Lagged Variables
item.alpha

Coefficient Alpha, Hierarchical Alpha, and Ordinal Alpha
item.reverse

Reverse Code Scale Item
mplus.run

Run Mplus Models
multilevel.cfa

Multilevel Confirmatory Factor Analysis
mplus.update

Mplus Input Updating
multilevel.descript

Multilevel Descriptive Statistics for Two-Level and Three-Level Data
mplus.print

Print Mplus Output
mplus.lca

Mplus Model Specification for Latent Class Analysis
multilevel.icc

Intraclass Correlation Coefficient, ICC(1) and ICC(2)
multilevel.fit

Simultaneous and Level-Specific Multilevel Model Fit Information
mplus.plot

Plot Mplus GH5 File
multilevel.cor

Within-Group and Between-Group Correlation Matrix
na.as

Replace Missing Values With User-Specified Values or User-Specified Values With Missing Values
multilevel.r2

R-Squared Measures for Multilevel and Linear Mixed Effects Models
na.coverage

Variance-Covariance Coverage
multilevel.indirect

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

Cross-Level Measurement Invariance Evaluation
na.indicator

Missing Data Indicator Matrix
na.descript

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

Multilevel Composite Reliability
na.auxiliary

Auxiliary Variables Analysis
multilevel.r2.manual

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

Print misty.object object
na.prop

Proportion of Missing Data for Each Case
na.test

Missing Completely at Random (MCAR) Test
read.dta

Read Stata DTA File
read.mplus

Read Mplus Data File and Variable Names
plot.misty.object

Plots misty.object object
na.pattern

Missing Data Pattern
read.sav

Read SPSS File
read.data

Read Data File in Table Format, SPSS, Excel, or Stata DTA File
na.satcor

Fit a Saturated Correlates Model
restart

Restart R Session
setsource

Set Working Directory to the Source File Location
read.xlsx

Read Excel File
script.open

Open, Close and Save R Script in RStudio
result.lca

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

Save Copy of the Current Script in RStudio
size.mean

Sample Size Determination
script.new

Open new R Script, R Markdown script, or SQL Script in RStudio
robust.lmer

Robust Estimation of Multilevel and Linear Mixed-Effects Models
rec

Recode Variable
test.t

t-Test
test.levene

Levene's Test for Homogeneity of Variance
summa

Print Summary Output
test.welch

Welch's Test
write.mplus

Write Mplus Data File
skewness

Univariate and Multivariate Skewness and Kurtosis
write.data

Write Data File in Table Format, SPSS, Excel, or Stata DTA File
uniq

Extract Unique Elements and Count Number of Unique Elements
test.z

z-Test
write.dta

Write Stata DTA File
write.xlsx

Write Excel File
write.result

Write Results of a misty Object into an Excel file
write.sav

Write SPSS File