wsMed1.0.2 package

Append significance stars based on CI

Conditional Indirect Effects with a Continuous Moderator

Apply Standardization to Parameter Definitions

Average Relative Increase in Variance

Assert a scalar (whole-number) integer with optional bounds

Bootstrap Standard Deviations for Standardization

Build Unstandardized Parameter Definitions

Build Standardization Maps PATH

Build Standardization Maps

Basic Contrasts for Indirect Effects and Pre/Post Path Coefficients

Debug printer with indentation (internal)

Clean all CI column names into the standard form

Fit SEM and run Monte-Carlo draws

Make CI column names like "2.5%CI.Lo / 97.5%CI.Up"

Create moderation output for wsMed

Verbose message wrapper (internal)

Evaluate Unstandardized Monte Carlo Definitions

Evaluate Standardized Monte Carlo Expressions

Extract All Parameters and Definitions

Fix legacy CI column names in a data.frame

Fix % characters mangled by make.names()

Generate Monte Carlo Samples

Generate Chained Mediation Model

Generate Combined Parallel and Chained Mediation Model

Generate Parallel Mediation Model

Generate Parallel and Chained Mediation Model

Extract All Variables Needed for Standardization

Parse All Possible Indirect Paths from Column Names

Get safe number of CPUs for parallel processing

Extract Target Variables for Standardization

Impute Missing Data Using Multiple Imputation

Convert Lavaan Model to RAM Matrices

make_contrasts

Compute Monte Carlo Estimates, Standard Errors, and CIs (with Percent ...

Process Monte Carlo Samples for Defined Parameters in SEM

Monte Carlo Confidence Intervals for Multiple Imputation SEM Models

Monte Carlo Summary for Standardized Estimates

Wrapper for Internal Multiple Imputation Combining Function

Null-coalescing operator

Plot moderation curves with Johnson-Neyman highlights

Prepare Data for Two-Condition Within-Subject Mediation (WsMed)

Prepare Data with Missing Values for Mediation Analysis

Print Method for wsMed Objects

Print Formatted SEM Model Syntax

Convert Standardized RAM Back to Lavaan Matrices

Generate Random Variates from the Gaussian Distribution (Singular Valu...

Resolve Dependencies of Defined Parameters

Run Monte Carlo-Based Mediation Inference

Monte Carlo SEM with Multiple Imputation (WsMed Workflow)

Sort Parameters for Printing in SEM Output

Standardize Parameter Estimates in a Lavaan Model

Standardize RAM Matrices

Summarize Monte Carlo Simulation Results

Test for a Positive Definite Matrix

Monte Carlo Sampling for Parameter Estimates

Compute Updated Parameter Estimates for SEM Models

Adjusted Total Sampling Covariance Matrix

Apply PrepareData to Imputed Datasets and Return New MIDS Object

Validate user inputs for wsMed()

Within-Subject Mediation Analysis (Two-Condition)