ProQuest Subject Index - Biostatistics at HARVARD UNIVERSITY

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You are viewing titles for HARVARD UNIVERSITY in the Biostatistics available through the UMI Dissertations & Thesis Gradwoorks site

Robust inference using higher order influence functions	Assessing and testing for population stratification and its impact on power of family-based association studies in the United States

Analyses of periodic observations and time series data with applications to HIV prevention and state-space models	Statistical models for removing microarray batch effects and analyzing genome tiling microarrays

Using mixed effects models to integrate high-dimensional, genomic data and an array-based analysis of the evolution of brain aging	Leveraging hidden correlations in high-dimensional biological data

Statistical issues in genome-wide association studies	Novel methods for efficient surveillance and monitoring

Stochastics and networks in genomic data	Novel multivariate and Bayesian approaches to genetic association testing and integrated genomics

Resampling methods for high-dimensional data and nonparametric regression with applications to brain imaging, bioinformatics, and sleep/circadian medicine	Distance based methods for space time modelling of the health of populations

Statistical methods for high-dimensional genomic data	Modern approaches in association mapping

Multilevel models for zero-inflated count data in environmental health and health disparities research	Robust methodology for predicting and evaluating prognosis in right censored time to event data

Three applications of statistics to medical research	Disease mapping and statistical issues in public health surveillance

Improving LQAS for monitoring and evaluation of health programs in resource-poor settings	The Analysis of Somatic Copy Number Alteration in Human Cancers

Copy Number Variation in the Human Genome: Tools, Methods, and Applications to Disease	Accounting for uncertainty in environmental health risk assessment

Statistical Methodology for Failure Time Data in the Presence of Truncation	Efficient Monte Carlo Methods for Sampling and Inference: Networks, Brains, Proteins

Bayesian Methods for Global Health Monitoring	Bayesian Methods for Modeling Branching Tree Processes with Application to Drug Resistant Tuberculosis

Novel Methodologies in Statistical Genetics for the Discovery of Causal Variants	Variable Selection Methods for Longitudinal Data

Statistical Methods for Panel Studies with Applications in Environmental Epidemiology	Statistical Methodology for Sequence Analysis

Statistical methods for clinical trials with multiple outcomes, HIV surveillance, and nonparametric meta-analysis	Hidden Markov Models Predict Epigenetic Chromatin Domains

Inference and Prediction for High Dimensional Data via Penalized Regression and Kernel Machine Methods	Survival analysis with high-dimensional covariates, with applications to cancer genomics

Multivariate Data Analysis with Applications to Cancer	Landmark Prediction of Survival

Contributions to Imputation Methods Based on Ranks and to Treatment Selection Methods in Personalized Medicine	Estimating Network Features and Associated Measures of Uncertainty and Their Incorporation in Network Generation and Analysis

Kernel Machine Methods for Risk Prediction with High Dimensional Data