Yi, Z., Strigari, L. E., Jin, L. and Sinha, S. Detection of astrophysical neutrinos at prospective locations of dark matter detectors. Physical Review D. https://arxiv.org/abs/2307.13792.
Huang, W., Page, R. L., Morris, T., Ayres, S., Ferdinand, A. O. and Sinha, S. Maternal exposure to SSRIs or SNRIs and the risk of congenital abnormalities in offspring: A systematic review and meta-analysis. PLoS ONE. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0294996.
Related data and code [data and code]
Nault, R., Saha, S., Bhattacharya, S., Sinha, S., Maiti, T., and Zacharewski, T. Single cell transcriptomics shows dose-dependent disruption of hepatic zonation by TCDD in mice. Toxicological Sciences.
https://www.biorxiv.org/content/10.1101/2022.06.15.496321v1.full
Rivera-Velez, A., Huber, L., Sinha, S. and Cohen, N. D. (2022). Fitness cost conferred by the novel erm(51) and rpoB mutation on environmental multidrug resistant-Rhodococcus equi. Veterinary Microbiology. https://www.sciencedirect.com/science/article/pii/S0378113522002012, supplementary material [pdf]
Wang, T., He, K., Ma, W., Bandyopadhyay, D. and Sinha, S. Minorize-maximize algorithm for the generalized odds rate model for clustered current status data. Canadian Journal of Statistics.
http://doi.org/10.1002/cjs.11733 Supplementary material [pdf], The R package MMGOR
is available at https://github.com/laozaoer/MMGOR. Package [manual]
Nault, R., Saha, S., Bhattacharya, S., Dodson, J., Sinha, S., Maiti, T. and Zacharewski, T. Benchmarking of a Bayesian single cell RNAseq differential gene expression test for dose-response study designs. To appear in the journal of Nucleic Acids Research. scBT (code for the proposed Bayesian hypothesis testing method) https://github.com/satabdisaha1288/scBT, spattdr (simulation code) https://github.com/zacharewskilab/splattdr
Manuel, C., Sinha, S. and Wang, S. Reduction of bias due to misclassified exposures using instrumental variables. Accepted to the Canadian Journal of Statistics.
[R code] for methods M1 and M2. The code for approach M3 using the variational inference is given in the [Supplementary Materials]. [R package] and its [manual] for the MCMC based analysis of method M3.
Hu, L., Mandal, S. and Sinha, S. A comparative study of two-sample tests for interval-censored data. Journal of Statistical Computation and Simulation. https://www.tandfonline.com/doi/full/10.1080/00949655.2021.1955884
Karmakar, M., Lai, P-C., Sinha, S., Glaser, S. and Chakraborty, S. Identification of miR-203a, mir-10a, and miR-194 as predictors for risk of lymphovascular invasion in head and neck cancers. https://doi.org/10.18632/oncotarget.28022
Dutta, B., Lang, R.F., Liao, S., Sinha, S., Strigari, L. and Thompson, A. A global analysis strategy to resolve neutrino NSI degeneracies with scattering and oscillation data. To appear in The Jouranl of High Energy Physics. https://arxiv.org/abs/2002.03066
Singh, S., Venkatasamy, L., White, T., Sinha, S., Glaser, S., Safe, SS., and Chakraborty, S. CXCL11/CXCR3 mediates tumor lymphatic crosstalk and inflammation induced tumor promoting mechanisms in head and neck cancers. Accepted to the American Journal of Pathology. https://www.ncbi.nlm.nih.gov/pubmed/32035061
Lee, D., Lahiri, S. N. and Sinha, S. A test of homogeneity of distributions when observations are subject to measurement errors. Accepted to Biometrics. [pdf],[Supplementary Materials]
For this project an R package, named MEtest, has been created and is available from CRAN https://cran.r-project.org/web/packages/MEtest/index.html
This [html file] contains illustrative examples on how to use the package for different scenarios.
Dutta, B., Liao, S., Sinha, S. and Strigari, LE. Searching for Beyond the Standard Model Physics with COHERENT energy and timing data. Physical Review Letters. [pdf]
Manuel, C. M., Sinha, S. and Wang, S. Matched case-control data with a misclassified exposure: What can be done with instrumental variables? Biostatistics. [pdf], [Supplementary Materials]
Code is available at GitHub https://github.com/ronsami/Istrumental-variables-for-misclassification
For this project an R package, named mccmeiv, has been created and is available from CRAN https://CRAN.R-project.org/package=mccmeiv
Lee, D. and Sinha, S. Identifiability and bias reduction in the skewprobit model for a binary response. Journal of Statistical Computation and Simulation. [pdf], [Supplementary materials]
For this project an R package, named SPreg, has been created and is available from CRAN https://cran.r-project.org/package=SPreg
Wei, Y., Ma, Y., Garcia, T. P., and Sinha, S. Consistent estimator for logistic mixed effect models. Canadian Journal of Statistics. [pdf], [Supplementary materials]
Mandal, S., Wang, S., and Sinha, S. Analysis of linear transformation models with covariate measurement error and interval censoring. Statistics in Medicine. [pdf], [Supplementary Materials]
For this project an R package, named icemelt, has been created and is available from CRAN https://cran.r-project.org/web/packages/icemelt/index.html
This [html file] contains illustrative examples on how to use the package for different scenarios.
Cook, S., Blas, B., Carroll, R. J., and Sinha, S. Two wrongs make a right: Addressing underreporting in binary data from multiple sources. Political Analysis. [pdf]
R package: [Linux], [Windows], [Reference manual]
Lee, D., Carroll, R. J., and Sinha, S. Frequentist standard errors of Bayes estimators. Computational Statistics. [pdf]
Here is the code [R code in a zip file]
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. Statistical Methods in Medical Research, 27, 971-990. [pdf], [Supplementary Materials]
[Matlab code in a zip file],
Matlab code as html files: [example.html],
[AFT_Bayes_LASSO.html]
This [html file] contains illustrative examples on how to use a number of variable selection techniques with the objects generated from the survival package, while the generalized F distribution is considered in
this [html file].
Maiti, T., Sinha, S. and Zhong, P-S. (2016). Functional mixed effects model for small area estimation. Scandinavian Journal of Statistics, 43, 886-903. [pdf]
[Supplementary materials]
Sinha, S. and Ma, Y. Analysis of proportional odds models with censoring and errors-in-covariates. Journal of the American Statistical Association. 111, 1301–1312.
[pdf]
[Supplementary materials]
Sinha, S. and Wang, S. Semiparametric Bayesian analysis of censored linear regression with
errors-in-covariates. Statistical Methods in Medical Research, 26, 1389–1415.
[pdf]
Package Source: [smmrbayes_1.0.tar.gz]
Reference Manual: [SMMR_description_of_package.pdf]
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. Journal of
Biometrics and Biostatistics. [pdf]
Sinha, S., Saha, S. K., and Wang, S. (2014). Semiparametric approach for non-monotone missing covariates in a parametric regression model. Biometrics, 70, 299-311.
[pdf], [Supplementary Materials]
Sinha, S. and Ma, Y. (2014). Semiparametric analysis of linear transformation models with covariate
measurement errors. Biometrics. [pdf],
[Supplementary Materials]
Package Source: [mesub_1.0.tar.gz]
Windows binary: [mesub_1.0.zip]
Reference Manual: [manual_mesub.pdf]
Maiti, T., Ren, H., and Sinha, S. Prediction error of small area predictors with shrinking both
means and variances. Scandinavian Journal of Statistics. [pdf], [Supplementary Materials]
Sinha, S. and Yoo, S. (2012). Score tests in the presence of errors in covariates in matched
case-control studies. Journal of Multivariate Analysis.
[pdf]
Sinha, S. (2012). A functional method for conditional logistic regression
with errors-in-covariates. Journal of the Nonparametric Statistics.
[pdf]
Dass, S. C., Maiti, T., Ren, H., and Sinha, S. (2012). Confidence interval estimation of small
area parameters shrinking both means and variances. Survey Methodology.
[pdf]
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.
Journal of Equine Veterinary Science. [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. Biometrics. [pdf]
Sinha, S. (2010). An estimated-score approach for dealing with missing covariate data in matched
case-control studies. Canadian Journal of Statistics, 38, No 2. [pdf]
Osterstock, J., Sinha, S., Seabury, C.M., and Cohen, N. D. (2010). Effects of classifying disease states
in genetic association studies for paratuborculosis.
Preventive Veterinary Medicine. [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
Sinha, S., Mallick, B. K., Kipnis, V., and Carroll, R. J. Semiparametric Bayesian
analysis of nutritional epidemiology data in the presence of measurement
error. Biometrics. [pdf]
Here is the code:
[Readme.txt],
[R-code],
[Fortran-subroutine]
Sun, J., Sinha, S., Wang, S., and Maiti, T. Bias corrected inference for the conditional
logistic regression. Statistics in Medicine. [pdf]
Here is the code for bias corrected estimator. [Readme.txt], [R-code]
Sinha, S., and Wang, S. (2009). A new semiparametric procedure for matched case-control
studies with missing covariates. Journal of Nonparametric Statistics.
[pdf]
Sinha, S., Gruber, S. B., Mukherjee, B., and Rennert, G. (2008). Inference of
haplotype effects in matched case-control studies using unphased genotype
data. International Journal of Biostatistics, 4, Issue 1, Article 6.
[pdf]
Here is the code: [Readme.txt],
[R-code], [Fortran subroutines]
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. and Maiti, T. (2007). Analysis of matched
case-control data in presence of nonignorable missing data.
Biometrics. [pdf]
Here is the code [R-script],
[Fortran subroutines]
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]
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., 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]
Here is the [R-code]
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]
Here is the code in a [zipped folder]
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]
Book Chapters
Wang, T., Bandyopadhyay, D. and Sinha, S. Efficient estimation of the additive risks model for interval-censored data. To appear as a book chapter in an edited volume on interval-censored data (Editors: Jianguo Sun and Ding-Geng Chen). https://arxiv.org/abs/2203.09726, R package https://github.com/laozaoer/MMIntAdd
Sinha, S. (2021). Bayesian approaches for handling covariate measurement error.
Handbook of Measurement Error Models Edited by Grace Yi, Aurore Delaigle and Paul Gustafson (Chapman & Hall/CRC Press), eBook ISBN 9781315101279.
Sinha, S. (2007), Bayesian methods for case-control studies: Annotated bibliography. ISBA Bulletin, 16, 5-8. Complete bulletin. [pdf]
Mukherjee, B., Sinha, S., and Ghosh, M. (2005). Bayesian
analysis for case-control studies. Handbook of Statistics, 25, 793–819.
[pdf]
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