Projects 

DRUGStat  MVPreg  MIXZIP  RMASS  BIFACTOR SuperMix  MixedUp
Suite  NPPL  LPL  Hakan 


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 
MVPreg computes a general multivariate probit
regression model for the analysis of multivariate binary data.



MIXZIP 
MIXZIP provides the maximum marginal likelihood
estimates of mixedeffects ZeroInflated Poisson
(ZIP) regression models.


Authors list: 
Kwan
Hur, Robert
D. Gibbons and Kush
Kapur 
Graphical user interface by Dave
Patterson 


RMASS 
The RMASS program computes sample size for threelevel
mixedeffects linear regression models for
the analysis of clustered longitudinal data.
Threelevel designs are used in many areas, but
in particular, multicenter randomized longitudinal
clinical trials in medical or healthrelated
research. In this case, level 1 represents
measurement occasion, level 2 represents subject,
and level 3 represents center.
The model allows for randomeffects of the time trends at both
the subjectlevel and the centerlevel. The sample size determinations
in this program are based on the requirements for a test of treatment
by time interaction(s) for designs based on either subjectlevel
or clusterlevel 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.


Authors list: 
Robert D. Gibbons and Donald Hedeker 


SuperMix 
SuperMix extends the
functionality available in the MixedUp 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
indepth look at SuperMix and to download
a free fully functional 15day trial edition
vist the SSI
SuperMix homepage. 


The MixedUp Suite 
The Mixedup Suite provides mixedeffects
regression functionality not available anywhere
else — at
any price. MIXOR, MIXREG, MIXNO and MIXPREG
are based on the collaborative effort of
Drs. Donald Hedeker and Robert D. Gibbons
of the University of Illinois at Chicago
and University of Chicago, respectively.
Discerning Systems Inc. produced the user interfaces
around the computer programs written by Don
Hedeker.
The work was
supported by the National Institute of Mental
Health and the MacArthur Foundation, and
the programs are available free of charge for download
from the MIXOR/MIXREG homepage located at the University of Illinois at Chicago. 


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.



Lognormal Prediction Limit
for the Arithmetic Mean of n future samples 
This program computes the 95% lognormal prediction
limit for a future mean of n samples based on a historical set of
m samples.



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 welldesigned publicationquality 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 list: 
Anup
Amatya and Hakan
Demirtas 
