The products of our work are distributed freely over the Internet as a series of computer programs developed under the direction of Don Hedeker in collaboration with Dave Patterson and his colleagues at Discerning Systems in Vancouver. The site is widely utilized by applied researchers and statisticians around the world, with over 4,000 unique visits per month.
For CHS faculty members, if you have a new computer program that needs to be added, or a newer version available, please use this form to request an update.
DRUGStat
DRUGStat is an easy to use system for determining which drugs are potentially harmful or protective relative to all other drugs in the specific class of drugs of interest.
MVPreg
The MVPreg program computes a general multivariate probit regression model for the analysis of multivariate binary data. Correlations between multiple binary measures are modeled as a factor analytic process. In the context of mental health service utilization data MVPREG can estimate the effects of design variables (e.g., changes in the health care delivery system) and case mix variables (e.g., age, sex, and race) on multivariate service utilization patterns.
Gibbons R.D., Hedeker D.R. Charles S.C., & Frisch P. A random-effects probit model for predicting medical malpractice claims. Journal of the American Statistical Association, 89, 760-767, 1994
Bock R.D. & Gibbons R.D. High dimensional multivariate probit analysis. Biometrics, 52, 1183-1194, 1996.
Gibbons R.D. & Lavigne J.V. Emergence of childhood psychiatric disorders: A multivariate probit analysis. Statistics in Medicine, 17, 2487-2499, 1998.
MIXZIP
MIXZIP provides the maximum marginal likelihood estimates of mixed-effects Zero-Inflated Poisson (ZIP) regression models.
Authors list: Kwan Hur, Robert D. Gibbons and Kush Kapur
Graphical user interface by Dave Patterson
RMASS
The RMASS web application computes sample size for three-level mixed-effects linear regression models for the analysis of clustered longitudinal data. Three-level designs are used in many areas, but in particular, multi-center randomized longitudinal clinical trials in medical or health-related research. In this case, level 1 represents measurement occasion, level 2 represents subject, and level 3 represents center.
The model allows for random-effects of the time trends at both the subject-level and the center-level. The sample size determinations in RMASS are based on the requirements for a test of treatment by time interaction(s) for designs based on either subject-level or cluster-level randomization.
The approach is general with respect to sampling proportions and number of groups, and it allows for differential attrition rates over time. The general methodology is discussed in Sample Size Determination for Hierarchical Longitudinal Designs with Differential Attrition Rates.
Authors list: Anindya Roy, Dulal K. Bhaumik, Subhash Aryal and Robert D. Gibbons
Web interface by Monica Jercan
BIFACTOR
The BIFACTOR program estimates the bifactor model for ordinal and dichotomous data. The bifactor model can be used to represent factorial structures for many types of psychological and educational tests, since they can exhibit a general factor and one or more group or method factors. The bifactor structure results from the constraint that each item has a nonzero loading on the primary dimension and, at most, one of the group factors.
Gibbons R.D., & Hedeker D.R. Full-information item bi-factor analysis. Psychometrika, 57, 423-436, 1992.
Gibbons R.D., Bock R.D., Hedeker D., Weiss D., Segawa E., Bhaumik D.K., Kupfer D., Frank E., Grochocinski V., Stover A. Full-Information Item Bi-Factor Analysis of Graded Response Data. Applied Psychological Measurement, 31, 4-19, 2007.
Authors list: Robert D. Gibbons and Donald Hedeker
SuperMix
SuperMix extends the functionality available in the Mixed-Up Suite by providing advanced data handling, the ability to reference columns by name, sophisticated import and export capability, visualization of data and results, increased analysis speed and additional statistical engine functions.
SuperMix has been developed by Scientific Software International under an SBIR Phase II contract N44MH32056. The application will fit models with continuous, count, ordinal, nominal, and survival outcome variables with nested data, allowing for up to three levels of nesting. For a more in-depth look at SuperMix and to download a free fully functional 15-day trial edition visit the SSI SuperMix homepage.
Nonparametric Prediction Interval for Analysis of Microarray Data
The statistical methodology implemented in this applet is based on a nonparametric prediction interval described in Sequential Prediction Bounds for Identifying Differentially Expressed Genes in Replicated Microarray Experiments by Robert D. Gibbons, Dulal K. Bhaumik, David R. Cox, Dennis R. Grayson, John M. Davis, and Rajiv P. Sharma.
Hakan’s R Packages
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.
1) BinNor: An R package for simultaneous generation of binary and normal data
2) OrdNor: An R package for concurrent generation of ordinal and normal data
3) PoisNor: An R package for simultaneous generation of count and normal data
4) MultiOrd: An R package for generation of multivariate ordinal variates
Authors: Anup Amatya and Hakan Demirtas