Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Biostatistics (140)
- Statistical Methodology (74)
- Statistical Theory (73)
- Survival Analysis (45)
- Statistical Models (43)
-
- Medicine and Health Sciences (42)
- Public Health (35)
- Epidemiology (31)
- Genetics and Genomics (21)
- Life Sciences (21)
- Bioinformatics (19)
- Clinical Trials (19)
- Computational Biology (19)
- Longitudinal Data Analysis and Time Series (19)
- Multivariate Analysis (17)
- Categorical Data Analysis (14)
- Genetics (14)
- Microarrays (13)
- Applied Mathematics (12)
- Numerical Analysis and Computation (12)
- Diseases (11)
- Disease Modeling (10)
- Clinical Epidemiology (5)
- Laboratory and Basic Science Research (2)
- Social and Behavioral Sciences (2)
- Analytical, Diagnostic and Therapeutic Techniques and Equipment (1)
- Applied Statistics (1)
- Biomedical Engineering and Bioengineering (1)
- Keyword
-
- Genetics (12)
- Inverse probability weighting (5)
- Mediation (5)
- Causal inference (4)
- Survival analysis (4)
-
- Causal Inference (3)
- Cox model (3)
- Hazard ratio (3)
- Interaction (3)
- Interval censoring (3)
- Mediation analysis (3)
- Ancillary variable (2)
- Censoring (2)
- Cluster randomized trial (2)
- Comparative Effectiveness Research (2)
- Confounding (2)
- Correlated data (2)
- Counterfactual (2)
- Decomposition (2)
- Direct and indirect effects (2)
- Direct effects (2)
- Doubly robust (2)
- Generalized Linear Model (2)
- Longitudinal data (2)
- MCMC (2)
- Marginal hazard ratio (2)
- Measurement Error (2)
- Mediation analysis; natural direct effects; natural indirect effects; multiple robustness; local efficiency (2)
- Missing data (2)
- Missing not at random (2)
Articles 151 - 180 of 212
Full-Text Articles in Statistics and Probability
Estimation Of Controlled Direct Effects, Sylvie Goetgeluk, Stijn Vansteelandt, Els Goetghebeur
Estimation Of Controlled Direct Effects, Sylvie Goetgeluk, Stijn Vansteelandt, Els Goetghebeur
Harvard University Biostatistics Working Paper Series
No abstract provided.
Spatio-Temporal Associations Between Goes Aerosol Optical Depth Retrievals And Ground-Level Pm2.5, Christopher J. Paciorek, Yang Liu, Hortensia Moreno-Macias, Shobha Kondragunta
Spatio-Temporal Associations Between Goes Aerosol Optical Depth Retrievals And Ground-Level Pm2.5, Christopher J. Paciorek, Yang Liu, Hortensia Moreno-Macias, Shobha Kondragunta
Harvard University Biostatistics Working Paper Series
We assess the strength of association between aerosol optical depth (AOD) retrievals from the GOES Aerosol/Smoke Product (GASP) and ground-level fine particulate matter (PM2.5) to assess AOD as a proxy for PM2.5 in the United States. GASP AOD is retrieved from a geostationary platform and therefore provides dense temporal coverage with half-hourly observations every day, in contrast to once per day snapshots from polar-orbiting satellites. However, GASP AOD is based on a less-sophisticated instrument and retrieval algorithm. We find that correlations between GASP AOD and PM2.5 over time at fixed locations are reasonably high, except in the winter and in …
Assessing Population Level Genetic Instability Via Moving Average, Samuel Mcdaniel, Rebecca Betensky, Tianxi Cai
Assessing Population Level Genetic Instability Via Moving Average, Samuel Mcdaniel, Rebecca Betensky, Tianxi Cai
Harvard University Biostatistics Working Paper Series
No abstract provided.
Comparing Trends In Cancer Rates Across Overlapping Regions, Yi Li, Ram C. Tiwari
Comparing Trends In Cancer Rates Across Overlapping Regions, Yi Li, Ram C. Tiwari
Harvard University Biostatistics Working Paper Series
No abstract provided.
Correcting Instrumental Variables Estimators For Systematic Measurement Error, Stijn Vansteelandt, Manoochehr Babanezhad, Els Goetghebeur
Correcting Instrumental Variables Estimators For Systematic Measurement Error, Stijn Vansteelandt, Manoochehr Babanezhad, Els Goetghebeur
Harvard University Biostatistics Working Paper Series
No abstract provided.
Effectively Combining Independent 2 X 2 Tables For Valid Inferences In Meta Analysis With All Available Data But No Artificial Continuity Corrections For Studies With Zero Events And Its Application To The Analysis Of Rosiglitazone's Cardiovascular Disease Related Event Data, Lu Tian, Tianxi Cai, Nikita Piankov, Pierre-Yves Cremieux, L. J. Wei
Effectively Combining Independent 2 X 2 Tables For Valid Inferences In Meta Analysis With All Available Data But No Artificial Continuity Corrections For Studies With Zero Events And Its Application To The Analysis Of Rosiglitazone's Cardiovascular Disease Related Event Data, Lu Tian, Tianxi Cai, Nikita Piankov, Pierre-Yves Cremieux, L. J. Wei
Harvard University Biostatistics Working Paper Series
No abstract provided.
Assessment Of A Cgh-Based Genetic Instability, David A. Engler, Yiping Shen, J F. Gusella, Rebecca A. Betensky
Assessment Of A Cgh-Based Genetic Instability, David A. Engler, Yiping Shen, J F. Gusella, Rebecca A. Betensky
Harvard University Biostatistics Working Paper Series
No abstract provided.
Survival Analysis With Large Dimensional Covariates: An Application In Microarray Studies, David A. Engler, Yi Li
Survival Analysis With Large Dimensional Covariates: An Application In Microarray Studies, David A. Engler, Yi Li
Harvard University Biostatistics Working Paper Series
Use of microarray technology often leads to high-dimensional and low- sample size data settings. Over the past several years, a variety of novel approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present. Among standard variable selection methods shown both to have good predictive accuracy and to be computationally efficient is the elastic net penalization approach. In this paper, adaptation of the elastic net approach is presented for variable selection both under the Cox proportional hazards model and under an accelerated failure time …
Estimating Time-To-Event From Longitudinal Categorical Data Using Random Effects Markov Models: Application To Multiple Sclerosis Progression, Micha Mandel, Rebecca A. Betensky
Estimating Time-To-Event From Longitudinal Categorical Data Using Random Effects Markov Models: Application To Multiple Sclerosis Progression, Micha Mandel, Rebecca A. Betensky
Harvard University Biostatistics Working Paper Series
No abstract provided.
Simultaneous Confidence Intervals Based On The Percentile Bootstrap Approach, Micha Mandel, Rebecca A. Betensky
Simultaneous Confidence Intervals Based On The Percentile Bootstrap Approach, Micha Mandel, Rebecca A. Betensky
Harvard University Biostatistics Working Paper Series
No abstract provided.
Identifying Patients Who Need Additional Biomarkers For Better Prediction Of Health Outcome Or Diagnosis Of Clinical Phenotype, Lu Tian, Tianxi Cai, L. J. Wei
Identifying Patients Who Need Additional Biomarkers For Better Prediction Of Health Outcome Or Diagnosis Of Clinical Phenotype, Lu Tian, Tianxi Cai, L. J. Wei
Harvard University Biostatistics Working Paper Series
No abstract provided.
Conservative Estimation Of Optimal Multiple Testing Procedures, James E. Signorovitch
Conservative Estimation Of Optimal Multiple Testing Procedures, James E. Signorovitch
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano
A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano
Harvard University Biostatistics Working Paper Series
No abstract provided.
Spatio-Temporal Analysis Of Areal Data And Discovery Of Neighborhood Relationships In Conditionally Autoregressive Models, Subharup Guha, Louise Ryan
Spatio-Temporal Analysis Of Areal Data And Discovery Of Neighborhood Relationships In Conditionally Autoregressive Models, Subharup Guha, Louise Ryan
Harvard University Biostatistics Working Paper Series
No abstract provided.
Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh
Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh
Harvard University Biostatistics Working Paper Series
No abstract provided.
Multiple Testing With An Empirical Alternative Hypothesis, James E. Signorovitch
Multiple Testing With An Empirical Alternative Hypothesis, James E. Signorovitch
Harvard University Biostatistics Working Paper Series
An optimal multiple testing procedure is identified for linear hypotheses under the general linear model, maximizing the expected number of false null hypotheses rejected at any significance level. The optimal procedure depends on the unknown data-generating distribution, but can be consistently estimated. Drawing information together across many hypotheses, the estimated optimal procedure provides an empirical alternative hypothesis by adapting to underlying patterns of departure from the null. Proposed multiple testing procedures based on the empirical alternative are evaluated through simulations and an application to gene expression microarray data. Compared to a standard multiple testing procedure, it is not unusual for …
Bayesian Hidden Markov Modeling Of Array Cgh Data, Subharup Guha, Yi Li, Donna Neuberg
Bayesian Hidden Markov Modeling Of Array Cgh Data, Subharup Guha, Yi Li, Donna Neuberg
Harvard University Biostatistics Working Paper Series
Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for …
Spatial Cluster Detection For Censored Outcome Data, Andrea J. Cook, Diane Gold, Yi Li
Spatial Cluster Detection For Censored Outcome Data, Andrea J. Cook, Diane Gold, Yi Li
Harvard University Biostatistics Working Paper Series
No abstract provided.
Structural Inference In Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Xihong Lin, Donglin Zeng
Structural Inference In Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Xihong Lin, Donglin Zeng
Harvard University Biostatistics Working Paper Series
No abstract provided.
Estimation In Semiparametric Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Donglin Zeng, Xihong Lin
Estimation In Semiparametric Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Donglin Zeng, Xihong Lin
Harvard University Biostatistics Working Paper Series
No abstract provided.
Nonparametric Regression Using Local Kernel Estimating Equations For Correlated Failure Time Data, Zhangsheng Yu, Xihong Lin
Nonparametric Regression Using Local Kernel Estimating Equations For Correlated Failure Time Data, Zhangsheng Yu, Xihong Lin
Harvard University Biostatistics Working Paper Series
No abstract provided.
Causal Inference In Hybrid Intervention Trials Involving Treatment Choice, Qi Long, Rod Little, Xihong Lin
Causal Inference In Hybrid Intervention Trials Involving Treatment Choice, Qi Long, Rod Little, Xihong Lin
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Comparison Of Methods For Estimating The Causal Effect Of A Treatment In Randomized Clinical Trials Subject To Noncompliance, Rod Little, Qi Long, Xihong Lin
A Comparison Of Methods For Estimating The Causal Effect Of A Treatment In Randomized Clinical Trials Subject To Noncompliance, Rod Little, Qi Long, Xihong Lin
Harvard University Biostatistics Working Paper Series
No abstract provided.
Bayesian Smoothing Of Irregularly-Spaced Data Using Fourier Basis Functions, Christopher J. Paciorek
Bayesian Smoothing Of Irregularly-Spaced Data Using Fourier Basis Functions, Christopher J. Paciorek
Harvard University Biostatistics Working Paper Series
No abstract provided.
Predicting Future Responses Based On Possibly Misspecified Working Models, Tianxi Cai, Lu Tian, Scott D. Solomon, L.J. Wei
Predicting Future Responses Based On Possibly Misspecified Working Models, Tianxi Cai, Lu Tian, Scott D. Solomon, L.J. Wei
Harvard University Biostatistics Working Paper Series
No abstract provided.
An Informative Bayesian Structural Equation Model To Assess Source-Specific Health Effects Of Air Pollution, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski
An Informative Bayesian Structural Equation Model To Assess Source-Specific Health Effects Of Air Pollution, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski
Harvard University Biostatistics Working Paper Series
No abstract provided.
Mixed Multiplicative Factor Analysis Model For Air Pollution Exposure Assessment, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski
Mixed Multiplicative Factor Analysis Model For Air Pollution Exposure Assessment, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Computationally Tractable Multivariate Random Effects Model For Clustered Binary Data, Brent A. Coull, E. Andres Houseman, Rebecca A. Betensky
A Computationally Tractable Multivariate Random Effects Model For Clustered Binary Data, Brent A. Coull, E. Andres Houseman, Rebecca A. Betensky
Harvard University Biostatistics Working Paper Series
No abstract provided.
Using Profile Likelihood For Semiparametric Model Selection With Application To Proportional Hazards Mixed Models, Ronghui Xu, Anthony Gamst, Michael Donohue, Florin Vaida, David P. Harrington
Using Profile Likelihood For Semiparametric Model Selection With Application To Proportional Hazards Mixed Models, Ronghui Xu, Anthony Gamst, Michael Donohue, Florin Vaida, David P. Harrington
Harvard University Biostatistics Working Paper Series
No abstract provided.
Posterior Simulation In The Generalized Linear Model With Semiparmetric Random Effects, Subharup Guha
Posterior Simulation In The Generalized Linear Model With Semiparmetric Random Effects, Subharup Guha
Harvard University Biostatistics Working Paper Series
Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model, normal base measures and Gibbs sampling procedures based on the Pólya urn scheme are often used to simulate posterior draws. These algorithms are applicable in the conjugate case when (for a normal base measure) the likelihood is normal. In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998) and Neal (2000) are often applied to generate posterior samples. Some common problems associated with simulation algorithms for non-conjugate MDP …