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Nilanjan Chatterjee

Showing results (61-70 of 401) with videos related to

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Journal of the American Statistical Association|March 24, 2009
Analysis of Smoking Cessation Patterns Using a Stochastic Mixed-Effects Model With a Latent Cured StateSheng Luo, Ciprian M Crainiceanu, Thomas A Louis, et al.
Journal of the American Statistical Association|August 30, 2016
Constrained Maximum Likelihood Estimation for Model Calibration Using Summary-level Information from External Big Data SourcesNilanjan Chatterjee, Yi-Hau Chen, Paige Maas, et al.
Biometrics|March 18, 2006
Case-control and case-only designs with genotype and family history data: estimating relative risk, residual familial aggregation, and cumulative riskNilanjan Chatterjee, Zeynep Kalaylioglu, Joanna H Shih, et al.
Biostatistics (Oxford, England)|April 12, 2013
Controlling the local false discovery rate in the adaptive LassoJoshua N Sampson, Nilanjan Chatterjee, Raymond J Carroll, et al.
Statistical Science : a Review Journal of the Institute of Mathematical Statistics|June 15, 2010
Analysis of Case-Control Association Studies: SNPs, Imputation and HaplotypesNilanjan Chatterjee, Yi-Hau Chen, Sheng Luo, et al.
International Journal of Cancer|November 26, 2003
Fat, fiber, fruits, vegetables, and risk of colorectal adenomasAleyamma Mathew, Ulrike Peters, Nilanjan Chatterjee, et al.
Journal of the American Statistical Association|September 6, 2021
A penalized regression framework for building polygenic risk models based on summary statistics from genome-wide association studies and incorporating external informationTing-Huei Chen, Nilanjan Chatterjee, Maria Teresa Landi, et al.
Cancer Epidemiology, Biomarkers & Prevention : a Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology|January 8, 2011
Predicting the future of genetic risk predictionNilanjan Chatterjee, Ju-Hyun Park, Neil Caporaso, et al.
Biometrics|January 29, 2009
Bayesian inference for smoking cessation with a latent cure stateSheng Luo, Ciprian M Crainiceanu, Thomas A Louis, et al.
Genetic Epidemiology|March 4, 2011
Efficient study design for next generation sequencingJoshua Sampson, Kevin Jacobs, Meredith Yeager, et al.
Pageof 41

Showing results (61-70 of 401) with videos related to

Sort By:
Pageof 41
Journal of the American Statistical Association|March 24, 2009
Analysis of Smoking Cessation Patterns Using a Stochastic Mixed-Effects Model With a Latent Cured StateSheng Luo, Ciprian M Crainiceanu, Thomas A Louis, et al.
Journal of the American Statistical Association|August 30, 2016
Constrained Maximum Likelihood Estimation for Model Calibration Using Summary-level Information from External Big Data SourcesNilanjan Chatterjee, Yi-Hau Chen, Paige Maas, et al.
Biometrics|March 18, 2006
Case-control and case-only designs with genotype and family history data: estimating relative risk, residual familial aggregation, and cumulative riskNilanjan Chatterjee, Zeynep Kalaylioglu, Joanna H Shih, et al.
Biostatistics (Oxford, England)|April 12, 2013
Controlling the local false discovery rate in the adaptive LassoJoshua N Sampson, Nilanjan Chatterjee, Raymond J Carroll, et al.
Statistical Science : a Review Journal of the Institute of Mathematical Statistics|June 15, 2010
Analysis of Case-Control Association Studies: SNPs, Imputation and HaplotypesNilanjan Chatterjee, Yi-Hau Chen, Sheng Luo, et al.
International Journal of Cancer|November 26, 2003
Fat, fiber, fruits, vegetables, and risk of colorectal adenomasAleyamma Mathew, Ulrike Peters, Nilanjan Chatterjee, et al.
Journal of the American Statistical Association|September 6, 2021
A penalized regression framework for building polygenic risk models based on summary statistics from genome-wide association studies and incorporating external informationTing-Huei Chen, Nilanjan Chatterjee, Maria Teresa Landi, et al.
Cancer Epidemiology, Biomarkers & Prevention : a Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology|January 8, 2011
Predicting the future of genetic risk predictionNilanjan Chatterjee, Ju-Hyun Park, Neil Caporaso, et al.
Biometrics|January 29, 2009
Bayesian inference for smoking cessation with a latent cure stateSheng Luo, Ciprian M Crainiceanu, Thomas A Louis, et al.
Genetic Epidemiology|March 4, 2011
Efficient study design for next generation sequencingJoshua Sampson, Kevin Jacobs, Meredith Yeager, et al.
Pageof 41