• The R package miCoPTCM, written by Aurelie Bertrand for the analysis of cure models in survival analysis, implements the programs used in (a) Bertrand A., Legrand C., LĂ©onard D. and Van Keilegom I. (2017). Robustness of estimation methods in a survival cure model with mismeasured covariates Computational Statistics and Data Analysis 2017, in press; and (b)
    Bertrand, A., Legrand, C., Carroll, R. J., de Meester, C. and Van Keilegom, I. (2017). Inference in a survival cure model with mismeasured covariates using a SIMEX approach. Biometrika, to appear.

  • R code for implementing the misclassification analysis in the paper Cook, S. J., Blas, B., Carroll, R. J. and Sinha, S. (2017). Two wrongs make a right: addressing underreporting in binary data from multiple sources. Political Analysis, to appear

  • Matlab and R code for implementing the dietary patterns methodology in the paper
    Ma, S., Ma, Y. Wang, Y., Kravitz, E. S. and Carroll, R. J. (2017). A semiparametric single-index risk score across populations. Journal of the American Statistical Association, to appear.

  • BayesME: an R package for nonparametric density deconvolution and nonparametric regression (not yet implemented) allowing for heteroscadastic measurement error and heteroscedastic regression error .Based on Sarkar, A., Mallick, B. K., Staudenmayer, J., Pati, D. and Carroll, R. J. (2014). Bayesian semiparametric density deconvolution in the presence of conditionally heteroscedastic measurement errors. Journal of Computational and Graphical Statistics, 25, 1101-1125 and Sarkar, A., Mallick, B. K. and Carroll, R. J. (2014). Bayesian semiparametric regression in the presence of conditionally heteroscedastic measurement and regression errors. Biometrics, 70, 823-834. Packages mvtnorm and msm are required.

  • Programs for the method of secondary linear regression analysis of case-control studies. The paper, Semiparametric Estimation in the Secondary Analysis of Case-Control Studies by Yanyuan Ma and Raymond J. Carroll, will appear in the Journal of the
    Royal Statistical Society, Series B, in 2015. There is a README file and an example data set to use as a test.

  • CGEN, an R packages based on my work with Nilanjan Chatterjee and Yi-Hau Chen for analyzing genetic data on case-control samples, with particular emphasis on novel methods for detecting Gene-Gene and Gene-Environment interactions.

  • SAS Macro and Demonstrations For Estimating Usual Intake Distributions of Food and Associated Individual-Level Predictors for Diet-Disease Relationships

    This site is based on our work involving the estimation of the usual intake distributyion for nutrients and episodically consumed foods. In addition, we estimate individual-level usual intake for use in regression calibration analysis of diet-disease relationships.

  • SAS Macro for Haplotype Analysis

    The SAS macro HapReg implements the haplotype-based genetic association
    analysis for case-control studies, using a flexible model for gene-environment
    association allowing haplotypes to be potentially related with environmental
    exposures. The novel methodology is proposed by Chen, Chatterjee, and Carroll
    (2007, Retrospective Analysis of Haplotype-Based Case-Control Studies Under a
    Flexible Model for Gene-Environment Association, under revision).

  • Wavelet-Based Functional Mixed Model Methodology, Windows

    These are programs based upon the work of Jeffrey Morris and Raymond Carroll, 2006, Journal of the Royal Statistical Society, Series B, 68, 179-199

  • MatLab and R Programs for Mixtures of Berkson and Classical Measurement Errors in the Nevada Test Site Study

    These are programs based upon the work of Yehua Li, Annamaria Guolo, F. Owen Hoffman and Raymond J. Carroll. There are Bayesian and Monte-Carlo EM programs for the analysis of these important radiation data.

  • Programs called in the Measurement Error Short Course at ENAR, 2008

    These are Stata, R2WinBUGS and some SAS Code for our measurement error short course.

  • MatLab

    The following programs are in zipped directories. The various utility directories need to be unzipped since some of the functions call them.

  • R programs

    The R programs are basically translations of the MATLAB Programs. They are all in one directory.

  • CatReg

  • XploRe