Copyright(or -left) Notice:

The programs provided on this webpage are free software; you can redistribute and/or modify them under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

The programs are distributed in the hope that they will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
  1. SAS macro implementing the alternative multiple imputation estimator as described in:

    Lee, T., & Cai, L. (2012). Alternative multiple imputation inference for mean and covariance structure modeling. Journal of Educational and Behavioral Statistics, 37, 675-702.

  2. SAS macro implementing the Supplemented EM based procedure for testing mean and covariance structure models under missing data as described in:

    Cai, L. (2008). SEM of another flavour: Two new applications of the supplemented EM algorithm. British Journal of Mathematical and Statistical Psychology, 61, 309 329.

    Cai, L. & Lee, T. (2009). Covariance model fit testing under missing data: An application of the supplemented EM algorithm. Multivariate Behavioral Research, 44, 281304.

  3. Gradient projection algorithm for rotation in factor analysis. This is a GAUSS implementation of Bernaards and Jennrich's method.  For details, please refer to:

    Bernaards, C.A. & Jennrich, R.I. (2005). Gradient Projection Algorithms and Software for Arbitrary Rotation Criteria in Factor Analysis. Educational and Psychological Measurement, 65, 676-696.

  4. Multi-response Permutation Procedure (MRPP): implementation in SPSS.  The macros implementing the Multiresponse Permutation Procedure can be downloaded from here.  The output can be downloaded from here.  Here is an accompanying white paper that explains the macros.  The correct way to cite the macros is:

    Cai, L. (2006). Multi-response permutation procedure as an alternative to the analysis of variance: An SPSS implementation. Behavior Research Methods, 38, 51-59.

  5. Heteroscedasticity-Consistent (HC) Covariance Matrix Estimators implementation in SPSS as a macro program using the Matrix Language computing environment.  This is an on-going collaborative work with Dr. Andrew Hayes at the Ohio State University.   The macro can be downloaded from here.  Please go to Dr. Hayes's website for more information on HC methods.

  6. Assessing co-termination between coders in unitizing textual data: A Multi-response Randomized Blocks Permutation approach. Paper presented at the 2003 Convention of the Association for Education in Journalism and Mass Communication, Kansas City, MO.   To download the paper and the accompanying GAUSS code in PDF format, click here.  For a fuller treatment of this topic, you may also wish to download a copy of my thesis for your evaluation.