Krishna Saha

Selected Refereed Journal Articles (Out of 45 Total)

1. Saha, K.K. and Wang, S. (2019): Confidence intervals for the difference in the success rates of two treatments in the analysis of correlated binary responses. Biometrical Journal, 61, 983 - 1002. https://doi.org/10.1002/bimj.201700089
2. Saha, K.K. and Wang, S. (2018): Confidence intervals for a common intraclass correlation in the analysis of clustered binary responses. Journal of Biopharmaceutical Statistics, 28, 682 - 697. https://doi.org/10.1080/10543406.2017.1377727
3. Saha, K.K., Miller, D. and Wang, S. (2016): A comparison of some approximate confidence intervals for a single proportion for clustered binary outcome data. International Journal of Biostatistics, 12, 1-24. https://doi.org/10.1515/ijb-2015-0024
4. Sen, D., Chaubey, Y. and Saha, K.K. (2014): On testing coefficient of variation in an inverse Gaussian population. Statistics and Probability Letters, 90, 121-128. https://doi.org/10.1016/j.spl.2014.03.023
5. Sinha, S., Saha, K.K. and Wang, S. (2014): Semiparametric approach for non-monotone missing covariates in a parametric regression model. Biometrics 70, 299-311. https://doi.org/10.1111/biom.12159
6. Pradhan, V., Saha, K.K., Banerjee, T., and Evans, J., (2014): Weighted profile likelihood-based confidence interval for the difference between two proportions with paired binomial data. Statistics in Medicine, 33, 2984-2997. https://doi.org/10.1002/sim.6130
7. Saha, K.K (2014): Inference concerning a common dispersion of several treatment groups in the analysis of over/under-dispersed count data. Biometrical Journal, 56, 441-460. https://doi.org/10.1002/bimj.201300105
8. Saha, K.K., Bilisoly, R. and Dziuda, D.M. (2014): Hybrid based confidence intervals for the ratio of two treatment means in the over-dispersed Poisson data. Journal of Applied Statistics, 41, 439 - 453. https://doi.org/10.1080/02664763.2013.840273
9. Saha, K.K., (2013): Estimating the treatment effect in the analysis of extra-dispersed count response data from clinical trials. Journal of Biometrics & Biostatistics, 4:165. DOI: 10.4172/2155-6180.1000165
10. Saha, K.K., (2013): Interval estimation of the mean difference in the analysis of over-dispersed count data. Biometrical Journal, 55, 114-133. https://doi.org/10.1002/bimj.201200032
11. Saha, K.K., (2012): Profile Likelihood-based confidence interval of the intraclass correlation for binary outcome data sampled from clusters. Statistics in Medicine, 31, 3982–4002. https://pubmed.ncbi.nlm.nih.gov/22826179/
12. Saha, K.K., Sen, D., and Jin, C. (2012): Profile Likelihood-based confidence interval for the dispersion parameter in the analysis of one-way layout of count data. Journal of Applied Statistics, 39, 765-783. https://doi.org/10.1080/02664763.2011.616581
13. Saha, K.K. (2011): Analysis of proportions for clustered binary data in the presence of unequal dispersions.  Journal of Statistical Planning and Inference, 141, 2933-2945. https://doi.org/10.1016/j.jspi.2011.03.018
14. Saha, K.K. (2011): A comparison study of some competing discrete models for proportions or counts, with Applications to Biological Data. Journal of the Indian Society of Agricultural Statistics. 65, 143-153. 
15. Saha, K.K. and Paul, R. (2011): Interval estimation of the negative binomial dispersion parameter. Journal of Statistical Computation and Simulation, 81, 1993-2002. https://doi.org/10.1080/00949655.2010.512998
16. Saha, K.K. (2011). Interval estimation of the over-dispersion parameter in the analysis of one-way layout of count data. Statistics in Medicine, 30, 39-51. https://doi.org/10.1002/sim.4061
17. Saha, K.K. (2009). Quel test for two linear restrictions in the nonlinear models. Journal of Modern Applied Statistical Methods, 8, 132-146. https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1488&context=jmasm
18. Saha, K.K. and Bilisoly, R. (2009): Testing the homogeneity of the means of several groups of count data in the presence of unequal dispersions. Computational Statistics & Data Analysis, 53, 9, 3305-3313. https://doi.org/10.1016/j.csda.2009.01.019
19. Saha, K.K. (2008): Semiparametric estimation for the dispersion parameter in the analysis of over or under dispersed count data. Journal of Applied Statistics, 35, 12, 1383-1397. https://econpapers.repec.org/RePEc:taf:japsta:v:35:y:2008:i:12:p:1383-1397
20. Saha, K.K., and King, M.L. (2008). An alternative Wald type test for two linear restrictions with applications to non-linear regression models. Journal of Statistical Computation and Simulation, 78, 11, 1017-1031. https://doi.org/10.1080/00949650701423382
21. Saha, K.K. (2008): Analysis of one-way layout of count data in the presence of over or under dispersion. Journal of Statistical Planning and Inference, 138, 7, 2067-2081. https://doi.org/10.1016/j.jspi.2007.08.002
22. Paul, S.R. and Saha, K.K. (2007). The generalized linear model and extensions: A review and some biological and environmental applications. Environmetrics, 18, 421-443. https://doi.org/10.1002/env.849 
23. Saha, K.K. and Paul, S.R. (2005): Bias-corrected maximum likelihood estimator of the intra-class correlation parameter for binary data. Statistics in Medicine, 24, 3497-3512. https://doi.org/10.1002/sim.2197
24. Saha, K.K., and Paul, S.R. (2005): Bias corrected maximum likelihood estimator of the negative binomial dispersion parameter. Biometrics, 61, 179-185. https://doi.org/10.1111/j.0006-341X.2005.030833.x
25. Paul, S.R, Saha, K.K., and Balasooriya, U. (2003): An empirical investigation of different operating characteristics of several estimates of the intraclass correlation in the analysis of binary data, Journal of Statistical Computation and Simulation, 73, 7, 507-523. https://doi.org/10.1080/0094965021000050883
26. Saha, K.K. and Sutradhar, B.C. (1999): On the distribution of the extremes of unequally correlated normal variables with applications to antedependent cluster data, Annals of the Institute of Statistical Mathematics, 51, 2, 301-322. https://doi.org/10.1023/A:1003810208881

Selected Presentations (Out of 96 Total)

1. Alternative Test Procedures for Testing Homogeneity of the Risk Difference in Multiple Comparative Trials in the Innovations in Testing and Inference Session #108. The 2022 Joint Statistical Meetings, Washington, DC, Aug 6 – Aug 11, 2022.
2. Likelihood-based Approach for Testing the Homogeneity of Risk Difference or Risk Ratio in a Multicenter Randomized Clinical Trial in the WNAR Invited Session of Recent Advances in Categorical Data Analytics. The 2022 Western North American Region (WNAR 2022) Annual Meeting Virtual Conference, June 10 – June 15, 2022.
3. Comparing the accuracy of two diagnostic tests in the analysis of CTC images for detecting colon polyps in the Invited Session of Novel Innovations in Survival Analysis. The 2019 International Indian Statistical Association Conference (INDSTATS 2019), Mumbai, India, December 26-30, 2019.
4. Analysis of Diagnostic Tests in Diagnostic Medicine with an Application to CTC Images for Detecting Colon Polyps. The 2019 International Conference on Applied Probability and Statistics (CAPS2019) in Hanoi, Vietnam, at Vietnam Institute for Advanced Study in Mathematics, April 2-6, 2019.
5. Analysis of Correlated Binary Data in Split-Cluster Designs with an Application to a Split-Mouth Trial in the Workshop on Mathematical and Statistical Applications in Life Sciences and Engineering. The 12th International Conference on Mathematical Sciences for Advancement of Science and Technology (MSAST 2018) in Kolkata, India, at the Indismart Hotel, Dec 21-23, 2018.
6. Analysis of Diagnostic Tests in the CTC Images for Detecting Colon Polyps in the Image and High-Dimensional Processing Session CS69. The 2018 Symposium on Data Science & Statistics (SDSS 2018) in Reston, VA, at the Hyatt Regency, May 15-20, 2018.
7. Estimating the Common Intraclass Correlation Coefficient for Clustered Binary Responses in the Modern Approaches to Analysis of Correlated Data Session. The 44th Annual Meeting of the Statistical Society of Canada, Brock University in St. Catharines, ON, May 29 to June 1, 2016, (with Suojin Wang).
8. Estimation of Response Proportion in Correlated Binary Data: An Application to CTC Images Data in the Complex Data Analysis Session. The 2015 Spring Research Conference, Hyatt Regency Cincinnati, Cincinnati, OH, May 20-22, 2015 (with Daniel Miller).
9. Inference Concerning the Difference between Two Treatments in Clinical Trials in the Biopharmaceutical Applications and Survival Analysis Session. The 2015 Eastern North American Region (2015 ENAR) Spring Meeting, Hyatt Regency Miami, Miami, FL, March 15-18, 2015.
10. Statistical Analysis of Means and Dispersions from Several Treatment Groups for Extra-Dispersed Count Data from Toxicology Studies.  The 42nd Annual Meeting of the Statistical Society of Canada, University of Toronto, Toronto, ON, May 25-28, 2014.
11. Interval Estimation of the Hybrid Based Confidence Intervals for the Ratio of Two Treatment Means.  The 22nd International Workshop Matrices and Statistics (IWMS2013), University of Toronto, Toronto, ON, August 12-15, 2013. (Invited Talk)
12. A Semiparametric Method for a Partially Missing Covariate Data in the G.E.E. International Conference on Robust Statistics 2012, University of Vermont, Burlington, VT, August 5-10, 2012.
13. Interval Estimation of the Intraclass Correlation for Binary Outcome Data Sampled from Clusters - an Application to Radiation Exposure Data. The 21st Annual Applied Statistics Symposium - International Chinese Statistical Association, Westin Waterfront, Boston, MA, June 23 – 26, 2012. (Invited Talk)
14. Confidence Interval Estimation for the Dispersion Parameter in Count Data. The Statistics 2011 Canada / IMST-2011 Conference, Concordia University, Montreal, Canada, July 1-4, 2011. (Invited Talk)
15. Profile Likelihood Based Confidence Interval for the Dispersion Parameter in Count Data, with applications to Tumor Data. Eastern North American Region (ENAR) 2011 Spring Meeting, Miami, Florida, March 20-23, 2011 (with D. Sen and C. Jin)
16. Profile Likelihood-Based Confidence Interval for the Dispersion Parameter in the Analysis of One-Way Layout of Count Data. The First International Conference on Theory and Applications of Statistics, Dhaka, Bangladesh, December 26-28, 2010.
17. Analysis of Proportions for Clustered Binary Data in the Presence of Unequal Dispersions. Eighth International Indian Statistical Association Joint Statistical Meeting, Visakhapatnam, India, January 4-8, 2010.
18. Analysis of Proportions for Clustered Binary Data in the Presence of Unequal Dispersions. Seventh International Triennial Calcutta Symposium, Kolkata, India, December 28-31, 2009.
19. Estimating the Risk Ratio in the Analysis of Correlated Binary Data. The 34th New England Statistics Symposium, University of Rhode Island, Providence RI, Sept 30- Oct 2, 2021.
20. A Study on Inferential Methods for the Risk Ratio in the Analysis of Clustered Binary Data. Connecticut State University Faculty Research Conference, Southern Connecticut State University, New Haven, Connecticut, May 4, 2019.
21. Improved Confidence Interval for the Dispersion Parameter in Count Data Using Profile Likelihood. Department of Mathematics and Statistics, Concordia University, Montreal, July 3, 2009.
22. The Rel and Quel Tests for Two Linear Restrictions. School of Business and Information Technology, Monash University, Clayton, Melbourne, Australia (with M.L. King), January 19, 2000.
23. Estimation of the Intraclass Correlation in the Analysis of Toxicological Data. Mathematics Department Colloquium, Central Connecticut State University, New Britain, Connecticut, March 12, 2021.