All functions

aces_daily

Multilevel Daily Data Example

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

APAStyler()

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

APAStyler(<SEMSummary>)

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

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

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

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

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(<modelDiagnostics.lm>)

Plot Diagnostics for an lm model

plot(<residualDiagnostics>)

Plot Residual Diagnostics Default Method

plot(<SEMSummary.list>)

Plots SEMSummary.list object

plot(<SEMSummary>)

Plots SEMSummary object

plot(<testDistribution>)

Plot method for testDistribution objects

R2()

Calculate R2 Values

residualDiagnostics() as.residualDiagnostics() is.residualDiagnostics()

Residual Diagnostics Functions

roundedfivenum()

Calculate a rounded five number summary

SEMSummary.fit()

Summary Statistics for a SEM Analysis

SEMSummary()

Summary Statistics for a SEM Analysis

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

timeshift()

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

TukeyHSDgg()

Tukey HSD Plot

VAConverter()

Visual Acuity Converter

`[`(<VAObject>,<ANY>,<ANY>,<ANY>) print(<VAObject>) show(<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

winsorizor()

Winsorize at specified percentiles