Using printGM() with WsMed() | Using printGM() with GenerateModel*()

introduction | parallel mediation | MEMORE 3.0 Analysis Report | wsMed Analysis Report | chained/serial mediation

Introduction | Mediator numbering | Preparing example data | [M_ | Specifying a custom model | Indirect effects | GenerateModelCustom() identifies every directed path from a mediator to Y.The model above contains three indirect effects:[\mathtt | [\mathtt | [\mathtt | Parameter labels | Fitting the complete model with wsMed | Input requirements | Summary

Introduction | Quick start | Step 1: Specify the repeated-measures variables | Step 2: Choose the mediation structure | Predefined models | User-defined models | Step 3: Choose the estimation options | Missing data and confidence intervals | Standardized effects | Step 4: Add optional model components | Moderators | Covariates | Step 5: Inspect the results | Step 6: Interpret the printed results | Example 1: A model without an external moderator | Variables and analysis sample | Model fit | Total, direct, and indirect effects | [\text | Level-component paths and condition-specific coefficients | Contrasts between indirect effects | Regression paths, intercepts, and variances | Standardized results | Inspecting and extracting Example 1 | Example 2: A model with a continuous moderator | Moderated coefficients | Conditional effects | Significance markers and confidence intervals | Visualizing conditional effects | What to report | Further model details | Summary

Overview | Example | Basic Usage: Default Settings | Reference(s)

Overview | Arguments | Value | Example | References

Function Syntax | Arguments | Example | Data and Model | Basic usage: default settings | parameterEstimates_boot(): Different Options | print(): Options | Reference(s)

Overview | Example: Simple Mediation Model | Fit the Model with Bootstrapping | Form Bootstrap CIs for Standardized Coefficients | Form Bootstrap CIs for Unstandardized Coefficients | Visualize Bootstrap Estimates | Histogram and QQ Plot: hist_qq_boot() | Scatterplot Matrix: scatter_boot() | Reference(s)

Function Syntax | Arguments | Example | Data and Model | Basic Usage: Default Settings | standardizedSolution_boot(): Different Options | print(): Options | Reference(s)

Introduction | 1. Difference Model Description | 1.1 Regression for ( Y_{\text{diff}} ) and ( M_{\text{diff}} ) | 2. Indirect Effects | 2.1 Examples of Indirect Effects | 3. Total Effect | 4. Comparison of Indirect Effects | 4.1 Comparing Indirect Effects | Interpretation: | 4.2 Example: Three Mediators ( M_1, M_2, M_3 ) | Indirect Effects | Comparisons | The indirect effects are compared as follows:[CI_{1\text{vs}2} = \text{indirect}1 - \text{indirect}2][CI{1\text{vs}3} = \text{indirect}1 - \text{indirect}3][CI{2\text{vs}3} = \text{indirect}2 - \text{indirect}3][CI{1\text{vs}12} = \text{indirect}1 - \text{indirect}{12}][CI{1\text{vs}23} = \text{indirect}1 - \text{indirect}{23}][CI{1\text{vs}123} = \text{indirect}1 - \text{indirect}{123}][CI{2\text{vs}12} = \text{indirect}2 - \text{indirect}{12}][CI_{2\text{vs}23} = \text{indirect}2 - \text{indirect}{23}][CI_{2\text{vs}123} = \text{indirect}2 - \text{indirect}{123}][CI_{3\text{vs}12} = \text{indirect}3 - \text{indirect}{12}][CI_{3\text{vs}23} = \text{indirect}3 - \text{indirect}{23}][CI_{3\text{vs}123} = \text{indirect}3 - \text{indirect}{123}][CI_{12\text{vs}23} = \text{indirect}{12} - \text{indirect}{23}][CI_{12\text{vs}123} = \text{indirect}{12} - \text{indirect}{123}][CI_{23\text{vs}123} = \text{indirect}{23} - \text{indirect}{123}] | 5. C1 and C2 Coefficients | 6. Summary of Regression Equations

Introduction | 1. Model Description | 1.1 Regression for ( Y_{\text{diff}} ) and ( M_{\text{diff}} ) | 2. Indirect Effects | 3. Total Effect | 4. Comparison of Indirect Effects | 4.1 Example: Three Mediators (( M_1, M_2, M_3 )) | 5. C1 and C2 Coefficients | Definitions | 5.1 Example: Three Mediators (( M_1, M_2, M_3 )) | 6. Summary of Regression Equations

Introduction | 1. Difference Model Description | 1.1 Regression for ( Y_1 ) and ( Y_2 ) | 1.2 Difference Model for ( Y_{\text{diff}} ) | 1.3 Regression for ( M_{\text{diff}} ) | 2. Indirect Effects | 3. Total Effect | 4. Comparison of Indirect Effects | 4.1 Indirect Effect Definition | 4.2 Comparing Indirect Effects | Interpretation | 5. C1- and C2-Measurement Coefficients | 5.1 Difference Model with Two Mediators | 5.2 C2-Measurement Coefficients | 5.3 C1-Measurement Coefficients | 6. Summary of Regression Equations | 6.1 Difference Model | 6.2 Defined parameters | Summary

Introduction | 1. Model Description | 1.1 Regression for ( Y_{\text{diff}} ) and ( M_{\text{diff}} ) | 2. Indirect Effects | 3. Total Effect | 4. Comparison of Indirect Effects | 4.1 Example: Three Mediators (( M_1, M_2, M_3 )) | 5. C1- and C2-Measurement Coefficients | Definitions | 5.1 Example: Three Mediators (( M_1, M_2, M_3 )) | 6. Summary of Regression Equations