- Working paper
- Replication materials available here

- Manuscript forthcoming in Multivariate Behavioral Research.
- Replication materials available on github

- Manuscript published in Psychometrika 84(3), 802-829.
- Replication materials:
- Helper functions for obtaining conditional and marginal information criteria from CFA and IRT models.
- Stan code for model estimation in the IRT example.
- Replication script containing code to estimate models and obtain results from the paper, using the above files.

- Manuscript published in Journal of Statistical Software 87(c01), 1-16.
- Replication materials:
- merDeriv package for installation from CRAN.
- estfun method for obtaining scores from models of class lmerMod.
- vcov method for obtaining covariance matrix of all parameters (including random effect parameters) from models of class lmerMod.
- bread function for using the above code in tandem with package sandwich.
- Replication script containing code to run and summarize results from the paper, using the above files.

- Manuscript published in Psychometrika 83(1), 132-155.
- Replication materials:
- Simulation functions for data generation, power evaluation, and power summaries.
- lavaan extensions containing
`estfun()`method for lavaan objects estimated via PML and code to simplify model estimation (note: this code relies on lavaan 0.5-17). - Code to obtain scores from specific ltm objects and mirt objects.
- Data from application section
- Replication script containing code to run and summarize the application and simulations, using the above files.

- Manuscript published in Psychological Methods 21(2), 151-163.
- Replication materials:
- Simulation functions for data generation, power evaluation, and power summaries.
- Burnout data for application.
- Replication script containing code to run and summarize the application and simulations, using the above files.
- Relies on R packages
*nonnest2*to carry out the tests and*lavaan 0.5-17*for model estimation.

- Manuscript published in Psychonomic Bulletin & Review 25(1), 256-270.
- Replication materials:
- JAGS models used in the paper (this file writes JAGS model files when it is sourced in R).
- Peters & Levin (2008) data, used in the application.
- Helper code for computing Bayes factors via the Laplace approximation.
- Replication script containing code to estimate and summarize the analyses, using the above files.

- Manuscript published in Frontiers in Psychology 5(438), 1-11.
- Replication materials:
- Model estimation functions for simulations.
- Simulation functions for data generation, power evaluation, and power summaries.
- Replication script containing code to run and summarize the tutorial and simulations, using the above files. (Note: strucchange 1.5-0 and lavaan 0.5-14 contain code necessary to carry out the tests for general SEMs.)

- Manuscript published in Psychometrika 79(4), 569-584.
- Replication materials:
- lavaan extensions containing
`estfun()`method for lavaan objects (note: this code has been incorporated into lavaan and is no longer necessary). - strucchange extensions containing
`efpFunctional`s for ordinal measurement invariance tests. - Artificial example functions for lavaan model estimation, along with score extraction.
- Simulation functions for data generation, power evaluation, and power summaries.
- Replication script containing code to run and summarize the examples and simulations, using the above files.

- lavaan extensions containing

- Manuscript published in Psychometrika 78(1), 58-82.
- Psychoco 2012 presentation
- Replication materials:
- lavaan extensions containing
`estfun()`method for lavaan objects (note: this code has been incorporated into lavaan and is no longer necessary). - Artificial example functions for lavaan or OpenMx model estimation, along with score extraction.
- Simulation functions for data generation, power evaluation, and power summaries.
- Replication script containing code to run and summarize the examples and simulations, using the above files.

- lavaan extensions containing

This material is based upon work supported by the U.S. National Science Foundation under Grants SES-1061334 and 1460719. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation (NSF).

The **project summary page** resides **here**.