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misty (version 0.7.6)

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'.

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Version

Install

install.packages('misty')

Monthly Downloads

2,558

Version

0.7.6

License

MIT + file LICENSE

Maintainer

Takuya Yanagida

Last Published

October 27th, 2025

Functions in misty (0.7.6)

blimp.print

Print Blimp Output
blimp.run

Run Blimp Models
aov.b

Between-Subject Analysis of Variance
blimp.bayes

Blimp Summary Measures, Convergence and Efficiency Diagnostics
check.collin

Collinearity Diagnostics
center

Centering Predictor Variables in Single-Level and Multilevel Data
blimp

Create, Run, and Print Blimp Models
aov.w

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

Blimp Trace Plots and Posterior Distribution Plots
blimp.update

Blimp Input Updating
chr.trunc

Truncate a Character Vector to a Maximum Width
check.resid

Residual Diagnostics for Linear, Multilevel and Mixed-Effects Models
chr.color

Colored and Styled Terminal Output Text
check.outlier

Statistical Measures for Leverage, Distance, and Influence
chr.grep

Multiple Pattern Matching
chr.trim

Trim Whitespace from String
chr.gsub

Multiple Pattern Matching And Replacements
ci.cor

(Bootstrap) Confidence Intervals for Correlation Coefficients
chr.omit

Omit Strings
ci.mean

(Bootstrap) Confidence Intervals for Arithmetic Means and Medians
cluster.rwg

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

Cluster Scores
ci.mean.w

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

(Bootstrap) Confidence Intervals for Proportions
coeff.robust

Heteroscedasticity-Consistent and Cluster-Robust Standard Errors
ci.var

(Bootstrap) Confidence Intervals for Variances and Standard Deviations
clear

Clear Console in RStudio
ci.prop.diff

Confidence Interval for the Difference in Proportions
coding

Coding Categorical Variables
ci.mean.diff

Confidence Interval for the Difference in Arithmetic Means
df.check

Data Check
cor.matrix

Correlation Matrix
df.merge

Merge Multiple Data Frames
cohens.d

Cohen's d
df.head

Print the First and Last Rows of a Data Frame
coeff.std

Standardized Coefficients for Linear, Multilevel and Mixed-Effects Models
crosstab

Cross Tabulation
df.long

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

Descriptive Statistics
df.duplicated

Extract Duplicated or Unique Rows
df.move

Move Variable(s) in a Data Frame
dominance

Dominance Analysis
df.rbind

Combine Data Frames by Rows, Filling in Missing Columns
effsize

Effect Sizes for Categorical Variables
df.subset

Subsetting Data Frames
dominance.manual

Dominance Analysis, Manually Inputting a Correlation Matrix
freq

Frequency Table
df.rename

Rename Columns in a Matrix or Variables in a Data Frame
df.sort

Data Frame Sorting
indirect

Confidence Intervals for the Indirect Effect
item.scores

Scale Scores
libraries

Load and Attach Multiple Packages
item.reverse

Reverse Code Scale Item
item.cfa

Confirmatory Factor Analysis
mplus.bayes

Mplus Summary Measures, Convergence and Efficiency Diagnostics
item.alpha

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

Between-Group and Longitudinal Measurement Invariance Evaluation
item.omega

Coefficient Omega, Hierarchical Omega, and Categorical Omega
lagged

Create Lagged Variables
mplus

Create, Run, and Print Mplus Models
mplus.print

Print Mplus Output
multilevel.fit

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

Mplus Input Updating
mplus.run

Run Mplus Models
mplus.lca

Mplus Model Specification for Latent Class Analysis
multilevel.cor

Within-Group and Between-Group Correlation Matrix
multilevel.cfa

Multilevel Confirmatory Factor Analysis
mplus.plot

Plot Mplus GH5 File
multilevel.descript

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

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

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

Intraclass Correlation Coefficient, ICC(1) and ICC(2)
na.descript

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

Auxiliary Variables Analysis
multilevel.indirect

Confidence Interval for the Indirect Effect in a 1-1-1 Multilevel Mediation Model
multilevel.r2

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

Variance-Covariance Coverage
multilevel.omega

Multilevel Composite Reliability
multilevel.r2.manual

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

Cross-Level Measurement Invariance Evaluation
read.mplus

Read Mplus Data File and Variable Names
na.satcor

Fit a Saturated Correlates Model
na.pattern

Missing Data Pattern
read.data

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

Missing Data Indicator Matrix
plot.misty.object

Plots misty.object object
na.prop

Proportion of Missing Data for Each Case
read.dta

Read Stata DTA File
print.misty.object

Print misty.object object
na.test

Missing Completely at Random (MCAR) Test
read.sav

Read SPSS File
script.copy

Save Copy of the Current Script in RStudio
script.new

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

Restart R Session
script.open

Open, Close and Save R Script in RStudio
size.mean

Sample Size Determination
read.xlsx

Read Excel File
setsource

Set Working Directory to the Source File Location
robust.lmer

Robust Estimation of Multilevel and Linear Mixed-Effects Models
rec

Recode Variable
summa

Print Summary Output
write.dta

Write Stata DTA File
skewness

Univariate and Multivariate Skewness and Kurtosis
test.welch

Welch's Test
write.mplus

Write Mplus Data File
test.t

t-Test
uniq

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

z-Test
test.levene

Levene's Test for Homogeneity of Variance
write.data

Write Data File in Table Format, SPSS, Excel, or Stata DTA File
write.xlsx

Write Excel File
write.sav

Write SPSS File
write.result

Write Results of a misty Object into an Excel file