Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Genetics (12)
- ACGH data; Moving average; Perturbation method; Gaussian process; Genomic data (1)
- As-treated analysis; Per-protocol analysis; Causal inference; Instrumental variables; Principal stratification; Propensity scores (1)
- Asymptotic bias and variance; Clustered survival data; Efficiency; Estimating equation; Kernel smoothing; Marginal model; Sandwich estimator (1)
- Asymptotic bias; EM algorithm; Maximum likelihood estimator; Measurement error; Structural modeling; Transitional Models (1)
-
- Asymptotic efficiency; Conditional score method; Functional modeling; Measurement error; Longitudinal data; Semiparametric inference; Transition models (1)
- BLUPs; Kernel function; Model/variable selection; Nonparametric regression; Penalized likelihood; REML; Score test; Smoothing parameter; Support vector machines (1)
- Beta mixture; DNA methylation; cancer; epigenetics; mixture model (1)
- Clinical trials; Doubly randomized preference trials; EM algorithm; Partically randomized preference trials; Randomization; Selection bias (1)
- Empirical Bayes; False discovery rate; Clustering; Density estimation (1)
- High dimensional regression; Interval estimation; Orale property; Regularized estimation; Resampling methods (1)
- Multiple testing; multiple comparisons; mixture models; Poisson regression; genome-wide association (1)
Articles 1 - 19 of 19
Full-Text Articles in Computational Biology
Multiple Testing Of Local Maxima For Detection Of Peaks In Chip-Seq Data, Armin Schwartzman, Andrew Jaffe, Yulia Gavrilov, Clifford A. Meyer
Multiple Testing Of Local Maxima For Detection Of Peaks In Chip-Seq Data, Armin Schwartzman, Andrew Jaffe, Yulia Gavrilov, Clifford A. Meyer
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Perturbation Method For Inference On Regularized Regression Estimates, Jessica Minnier, Lu Tian, Tianxi Cai
A Perturbation Method For Inference On Regularized Regression Estimates, Jessica Minnier, Lu Tian, Tianxi Cai
Harvard University Biostatistics Working Paper Series
No abstract provided.
Powerful Snp Set Analysis For Case-Control Genome Wide Association Studies, Michael C. Wu, Peter Kraft, Michael P. Epstein, Deanne M. Taylor, Stephen J. Chanock, David J. Hunter, Xihong Lin
Powerful Snp Set Analysis For Case-Control Genome Wide Association Studies, Michael C. Wu, Peter Kraft, Michael P. Epstein, Deanne M. Taylor, Stephen J. Chanock, David J. Hunter, Xihong Lin
Harvard University Biostatistics Working Paper Series
No abstract provided.
Sparse Linear Discriminant Analysis For Simultaneous Testing For The Significance Of A Gene Set/Pathway And Gene Selection, Michael C. Wu, Lingson Zhang, Zhaoxi Wang, David C. Christiani, Xihong Lin
Sparse Linear Discriminant Analysis For Simultaneous Testing For The Significance Of A Gene Set/Pathway And Gene Selection, Michael C. Wu, Lingson Zhang, Zhaoxi Wang, David C. Christiani, Xihong Lin
Harvard University Biostatistics Working Paper Series
No abstract provided.
Estimation And Testing For The Effect Of A Genetic Pathway On A Disease Outcome Using Logistic Kernel Machine Regression Via Logistic Mixed Models, Dawei Liu, Debashis Ghosh, Xihong Lin
Estimation And Testing For The Effect Of A Genetic Pathway On A Disease Outcome Using Logistic Kernel Machine Regression Via Logistic Mixed Models, Dawei Liu, Debashis Ghosh, Xihong Lin
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Powerful And Flexible Multilocus Association Test For Quantitative Traits, Lydia Coulter Kwee, Dawei Liu, Xihong Lin, Debashis Ghosh, Michael P. Epstein
A Powerful And Flexible Multilocus Association Test For Quantitative Traits, Lydia Coulter Kwee, Dawei Liu, Xihong Lin, Debashis Ghosh, Michael P. Epstein
Harvard University Biostatistics Working Paper Series
No abstract provided.
Model-Based Clustering Of Methylation Array Data: A Recursive-Partitioning Algorithm For High-Dimensional Data Arising As A Mixture Of Beta Distributions, E. Andres Houseman, Brock C. Christensen, Ru-Fang Yeh, Carmen J. Marsit, Margaret R. Karagas, Margaret Wrensch, Heather H. Nelson, Joseph Wiemels, Shichun Zheng, John K. Wiencke, Karl T. Kelsey
Model-Based Clustering Of Methylation Array Data: A Recursive-Partitioning Algorithm For High-Dimensional Data Arising As A Mixture Of Beta Distributions, E. Andres Houseman, Brock C. Christensen, Ru-Fang Yeh, Carmen J. Marsit, Margaret R. Karagas, Margaret Wrensch, Heather H. Nelson, Joseph Wiemels, Shichun Zheng, John K. Wiencke, Karl T. Kelsey
Harvard University Biostatistics Working Paper Series
No abstract provided.
Empirical Null And False Discovery Rate Inference For Exponential Families, Armin Schwartzman
Empirical Null And False Discovery Rate Inference For Exponential Families, Armin Schwartzman
Harvard University Biostatistics Working Paper Series
No abstract provided.
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.
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 …
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.
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 …
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.