Package index • JWileymisc

All functions

APAStyler(): A generic function for pretty printing in (semi) APA Style

APAStyler(<SEMSummary>): A generic function for pretty printing in (semi) APA Style

APAStyler(<list>): APAStyler method for lists

APAStyler(<lm>): APAStyler method for linear models

APAStyler(<mira>): A generic function for pretty printing in (semi) APA Style

APAStyler(<modelTest.lm>): APAStyler method for model tests from a linear model

APAStyler(<modelTest.vglm>): APAStyler method for model tests from a vglm multinomial model

R2(): Calculate R2 Values

SEMSummary(): Summary Statistics for a SEM Analysis

SEMSummary.fit(): Summary Statistics for a SEM Analysis

TukeyHSDgg(): Tukey HSD Plot

VAConverter(): Visual Acuity Converter

show(<VAObject>) `[`(<VAObject>,<ANY>,<ANY>,<ANY>) print(<VAObject>) summary(<VAObject>): An S4 class to hold visual acuity data

show(<VASummaryObject>) plot(<VASummaryObject>,<missing>): An S4 class to hold visual acuity summary data

aces_daily: Multilevel Daily Data Example

as.na(): Coerces vectors to missing

cd(): Change directory

compareIVs(): Compares the effects of various independent variables on dependent variables

saveRDSfst() readRDSfst(): Save and read RDS functions for using multithreaded “ZSTD” or “LZ4” compression

cor2cov(): Convert a correlation matrix and standard deviations to a covariance matrix

corOK(): Return a non-missing correlation matrix

corplot(): Heatmap of a Correlation Matrix

cramerV(): Calculate Phi or Cramer's V effect size

density_inversion(): KDE-based Inverse CDF Sampling for Synthetic Data

diffCircular(): Calculate the Circular Difference

.fround(): Function to round and format a number

.quantilePercentiles(): Internal Function to Calculate Quantiles

egltable(): Function makes nice tables

empirical_pvalue(): Calculates an empirical p-value based on the data

findSigRegions(): Function to find significant regions from an interaction

formatHtest(): Function to format the reuslts of a hypothesis test as text

formatMedIQR(): Function to format the median and IQR of a variable

formatPval(): Function to simplify formatting p-values for easy viewing / publication

geom_tufterange(): Tufte Range

gglikert(): Creates a plot for likert scale

hashDataset(): Create a character vector or file hash of a dataset and each variable

intSigRegGraph(): Function to find significant regions from an interaction

is.naz(): Is a variable missing, non finite or zero length character?

lagk(): Create a lagged variable

lm2(): Modified lm() to use a specified design matrix

meanCircular(): Calculate a Circular Mean

modelCompare() as.modelCompare() is.modelCompare(): Compare Two Models

modelDiagnostics() as.modelDiagnostics() is.modelDiagnostics(): Model Diagnostics Functions

modelPerformance() as.modelPerformance() is.modelPerformance(): Return Indices of Model Performance

modelTest() is.modelTest() as.modelTest(): Detailed Tests on Models

moments(): Estimate the first and second moments

naz.omit(): Missing and Zero Character Omit

param_summary(): Calculates summaries for a parameter

param_summary_format(): Format a data frame of summary statistics

plot(<SEMSummary>): Plots SEMSummary object

plot(<SEMSummary.list>): Plots SEMSummary.list object

plot(<modelDiagnostics.lm>): Plot Diagnostics for an lm model

plot(<residualDiagnostics>): Plot Residual Diagnostics Default Method

plot(<testDistribution>): Plot method for testDistribution objects

residualDiagnostics() as.residualDiagnostics() is.residualDiagnostics(): Residual Diagnostics Functions

roundedfivenum(): Calculate a rounded five number summary

smd(): Calculate Standardized Mean Difference (SMD)

star(): Function to simplify converting p-values to asterisks

testDistribution() as.testDistribution() is.testDistribution(): Test the distribution of a variable against a specific distribution

theme_tufte(): Tufte Inspired Theme

timeshift(): Shift a time variable to have a new center (zero point)

winsorizor(): Winsorize at specified percentiles