studying factors; affecting the health and illness of populations, and serves as the foundation

and logic of interventions made in the interest of public health and preventive medicine.

The research is geared to develop novel statistical techniques for handling measurement

error in the major variable of interest, and to handle subjects with partially missing information.

The developed statistical techniques rely on parametric, semiparametric, and nonparametric

Bayesian or classical approaches for flexible and robust modeling.

Research interest keywords: Bayesian methods, Errors-in-covariates, Missing data, and Survival analysis.

Publications:

Sinha, S., Mukherjee, B., and Ghosh, M. (2004), Bayesian semiparametric modeling for

matched case-control studies with multiple disease states, Biometrics, 60, 41--49. [pdf]

Sinha, S., Mukherjee, B., Ghosh, M., Mallick, B. K., Carroll, R. J. (2005), Semiparametric Bayesian

analysis of matched case-control studies with missing exposure,

Journal of the American Statistical Association, 100, 591--601. [pdf] [code]

Mukherjee, B., Sinha, S., and Ghosh, M. (2005), Bayesian

analysis for case-control studies: A review article, Handbook of Statistics, 25. [pdf]

Sinha, S., and Mukherjee, B. (2006), A score test for

determining sample size in matched case-control studies with

categorical exposure, Biometrical Journal, 48, 35--53. [pdf] [code]

Mukherjee, B., Zhang, L., Ghosh, M., and Sinha, S. (2007),

Semiparameteric Bayesian analysis of case-control data under gene-environment independence

and population stratification, Biometrics. [pdf]

Sinha, S. (2007), Bayesian methods for case-control studies: Annoted bibliography,

ISBA Bulletin, 16, 5-8. Complete bulletin.

Mukherjee, B., Liu, I., and Sinha, S. (2007), Analyzing

matched case-control data with multiple ordered disease states, possible choices,

and comparisons, Statistics in Medicine. [pdf]

Sinha, S. and Maiti, T. (2007), Analysis of matched

case-control data in presence of nonignorable missing data,

Biometrics. [pdf] [codes 1, 2]

Sinha, S., Mukherjee, B., and Ghosh, M.

(2007), Modelling Association Among Bivariate Exposures In

Matched Case-Control Studies, Sankhya, 69, 379--404. [pdf]

Sinha, S., Gruber, S. B., Mukherjee, B., and Rennert, G. (2008). Inference of

haplotype effects in matched case-control studies using unphased genotype

Sinha, S., and Wang, S. (2009). A new semiparametric procedure for matched case-control

studies with missing covariates. Journal of Nonparametric Statistics. [pdf]

Sun, J., Sinha, S., Wang, S., and Maiti, T. Bias corrected inference for the conditional

logistic regression. To appear in Statistics in Medicine. [pdf] Computer codes for bias corrected estimator. Readme.txt, R-code.

Sinha, S., Mallick, B. K., Kipnis, V., and Carroll, R. J. Semiparametric Bayesian

analysis of nutritional epidemiology data in the presence of measurement

error. Readme.txt, R-code, Fortran-subroutine. Appeared in Biometrics. [pdf]

Chatterjee, N., Sinha, S., Diver, W. R., Feigelson, H. S. Analysis of cohort studies with multivariate,

partially observed disease classification data. To appear in Biometrika. [pdf] [supplementary material]

Here is the computer code. Readme.txt, File1, File2

Windows binary: EE_0.0.1.zip

Osterstock, J., Sinha, S., Seabury, C.M., and Cohen, N. D. (2010). Effects of classifying disease states

in genetic association studies for paratuborculosis. To appear in Preventive Veterinary Medicine. [pdf]

Sinha, S. (2010). An estimated-score approach for dealing with missing covariate data in matched

case-control studies. The Canadian Journal of Statistics, 38, No 2.[pdf]

Ahn, J., Mukherjee, B., Gruber, S. B., and Sinha, S. (2011). Missing exposure data in

stereotype regression model: application to matched case-control study with disease

subclassification.

Kuskie, K. R., Smith, J. L., Sinha, S., Carter, C. N., Chaffin, M. K., Slovis, N. M., Brown, S. E.,

Stepusin, R. S., Takai, S., Cohen, N. D. (2011). Associations between the exposure to airborne

virulent rhodococcus equi and the incidence of R equi pneumonia among individual foals.

Dass, S. C., Maiti, T., Ren, H., and Sinha, S. (2012). Confidence interval estimation of small

area parameters shrinking both means and variances.

Sinha, S. (2012). A functional method for conditional logistic regression

with errors-in-covariates. To appear in

Sinha, S. and Yoo, S. (2012). Score tests in the presence of errors in covariates in matched

case-control studies. Accepted to

Maiti, T., Ren, H., and Sinha, S. Prediction error of small area predictors with shrinking both

means and variances. To appear in the

Sinha, S. and Ma, Y. Semiparametric analysis of linear transformation models with covariate

measurement errors. To appear in

Package Source: mesub_1.0.tar.gz

Windows binary: mesub_1.0.zip

Reference Manual: manual_mesub.pdf

Sinha, S., Saha, S. K., and Wang, S. Semiparametric approach for non-monotone missing covariates

in a parametric regression model. To appear in

Miao, J., Sinha, S., Wang, S., Diver, RW. and Gapstur, S. M. Analysis of multivariate disease classification

data in the presence of partially missing disease traits.

Sinha, S. and Wang, S. Semiparametric Bayesian analysis of censored linear regression with

errors-in-covariates. Accepted in the

Package Source: smmrbayes_1.0.tar.gz

Reference Manual: SMMR_description_of_package.pdf

Sinha, S. and Ma, Y. Analysis of proportional odds models with censoring and errors-in-covariates.

Accepted in the

Maiti, T., Sinha, S. and Zhong, P-S. Functional mixed effects model for small area estimation.

Accepted in the

Zhang, Z., Sinha, S., Maiti, T., and Shipp, E. Bayesian variable selection in the AFT model with an application

to the SEER breast cancer data. Accepted in the

[Matlab code in a zip file], Matlab code as html files: [example.html], [AFT_Bayes_LASSO.html].

Lee, D., Carroll, R. J., and Sinha, S. Frequentist standard errors of Bayes estimators.

Accepted in

Cook, S., Blas, B., Carroll, R. J., and Sinha, S. Two wrongs make a right: Addressing underreporting in binary

data from multiple sources. Accepted in the

R package: [Linux], [Windows], [Reference manual]

Mandal, S., Wang, S., and Sinha, S. Analysis of linear transformation models

with covariate measurement error and interval censoring.

R package

Curriculum Vitae

Some Useful Links:

A
very
short note on B-spline

Two related files for B-spline: file 1
and
file 2

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Datasets
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__Kent Ridge
Bio-Medical Dataset Repository
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