The following guides have been developed by students and personnel at CRMDA to provide brief overviews on a wide range of topics in methodology. We do our best to keep them updated. Feel free to send us a note if there's a topic you would like covered and don't see here. For Spanish versions, please see our Guías KUant page.
1: LISREL 8.80 Syntax Guide: An introduction to LISREL 8.80 syntax
2: Reading Data Into LISREL: Using PRELIS, sufficient statistics, or text files to get your data into LISREL
3: Interpreting LISREL Output: A guide to understanding LISREL output files
4: Starting Values in LISREL: How to provide start values for individual parameters or whole matrices. This guide also includes a list of start value tips and tricks
5: What to Report: Information that should be provided when reporting the results from a CFA. Based on Brown (2006)
6: The Satorra-Bentler Chi Square: Implementing the Satorra-Bentler correction for non-normal data using LISREL
7: Bootstrapping: Bootstrapping data using PRELIS
8: Multiple Imputation: How to perform multiple imputation (MI) using SAS, PRELIS or AMELIA
9: LISREL'S RP Option: Using LISREL’s RP option to run a single syntax file on multiple data sets. This is especially important when using multiple imputations or bootstrapped data
10: Alternative Parameters: Using the AP and PA to calculate additional parameters. This is especially useful for mediation models
11: Imputation With Large Data Sets: Imputing data in datasets too large for standard multiple imputation procedures
12: Monte Carlo Simulation In Mplus: A brief guide to Monte Carlo simulation using Mplus. This guide also explains how to calculate power with Monte Carlo simulation
13: Mplus 5.0 Syntax Guide: An introduction to Mplus 5.0 syntax
14: SAS Data Conversion: How to convert data to/from SAS. File types include: SPSS, Excel, Access, STATA
15: Longitudinal Mediation within SEM: Using LISREL and MPLUS to analyze mediation within longitudinal panel models
16: Latent Variable Moderation: Three techniques to estimate interactions between latent variables using LISREL and MPLUS
17: Using PROC CALIS in SAS 9.22 to Evaluate Between-Group Differences in Latent Variable Means
19: Parcels explains the covariance algebra of using parcels with structural equation modeling (SEM)
20: Intro to R A guide for the complete beginner: R installation, programming, and data handling
21: Lavaan Syntax Guide A guide introducing the R package lavaan for structural equation modeling
22: Factorial Invariance Guide A guide describing how to establish factorial invariance for multiple-group confirmatory factor analysis.
23: Planned Missingness Survey This guide illustrates through an example how to design a three-form planned missingness survey with a common portion. The introduction includes a brief summary of why a planned missingness study design works, the basic design approach, and the benefits of such designs.
24. Tracing Rules in Structural Equation Modeling This guide provides general rules and graphical representations of the tracing rules used to recreate a model-implied covariance matrix from structural equation modeling pathway estimates. Examples include dual loadings, correlated residuals, and tracing rules for means.