TOP >> UNIVERSITY OF MICHIGAN >> Biostatistics
 
Browse Institutions
You are viewing titles for UNIVERSITY OF MICHIGAN in the Biostatistics available through the UMI Dissertations & Thesis Gradwoorks site
 
Some problems in statistical inference under order restrictions
 Sources and exposures of ambient air pollutants and their relationship to adverse birth outcomes and respiratory disease
 
Statistical methods in surrogate marker research for clinical trials
 Gene regulatory network reconstruction and pathway inference from high throughput gene expression data
 
Hybrid bootstrap for mapping quantitative trait loci and change point problems
 High-dimensional survival data analysis and it application to microarray data
 
Semiparametric methods for estimating cumulative treatment effects in the presence of non-proportional hazards and dependent censoring
 Disclosure risk assessments and control
 
Advances in modeling and inference of neuroimaging data
 Bayesian hierarchical modeling for problems in computational biology
 
A general framework for inferring the developmental causes of modularity of morphological variation with applications to the craniomandibular complex in rodents
 Some topics in missing data and adaptive confidence intervals
 
A study of non-regularity in dynamic treatment regimes and some design considerations for multicomponent interventions
 Bayesian predictive inference for three topics in survey samples
 
The development and application of a risk index to predict individualized chronic disease risk
 In silico haplotyping, genotyping and analysis of resequencing data using Markov models
 
Efficient methods for analysis of genome scale data
 Integrative statistical methods for the analysis of transcriptomic and metabolomic data
 
Some new insights about the accelerated failure time model
 Models and methods for genome-wide association studies
 
Model selection and l1 penalization for individualized treatment rules
 The developmental origins of health and disease in women from the Michigan Bone Health and Metabolism study: An examination with longitudinal and intergenerational data
 
Bayesian Modeling for High Throughput Genomic Data
 Statistical methods for genome-wide association studies of gene expression, with applications to the genetic study of psoriasis
 
Time series analysis for nonlinear dynamical systems with applications to modeling of infectious diseases
 Stochastic Dynamic Models for Functional Data
 
Innovative Statistical Models for Inference from Complex Design Surveys and Longitudinal Studies
 Flexible Methods for Clustered Event History Data
 
Joint Composite Estimating Functions in Spatial and Spatio-Temporal Models
 Effects of a Misattributed Cause of Death on Cancer Mortality
 
Time-dependent cross-ratio estimation for bivariate failure times
 Quantitative approaches to understanding cancer genomes
 
Methods for statistical and population genetics analysis
 Some Novel Spatial Stochastic Models for Functional Neuroimaging Analysis
 
Imputation and Dynamic Models in Semiparametric Survival Analysis
 Improving Small-Sample Inference in Group Randomized Trials and Other Sources of Correlated Binary Outcomes
 
On Estimation and Inference under Order Restrictions
 Statistical Methods and Models for Modern Genetic Analysis
 
Ignorable and Nonignorable Modeling in Regression with Incomplete Covariates
 Artificial Mixture Methods for Correlated Nominal Responses and Discrete Failure Time
 
Generalized Statistical Approaches for the Design for Phase I Trials
 Developing and Application of Statistical Algorithms for High-Dimensional Biological Data Analysis
 
Developing pseudo-observation and multiple imputation approaches for analysis of dependently censored survival and quality-adjusted survival data
 Combining Information from Multiple Complex Surveys
 
Analysis of marked recurrent events in the presence of a terminating event
 Shrinkage Methods Utilizing Auxiliary Information to Improve High-Dimensional Prediction Models
 
Applications of Circular Distributions and Spatial Point Processes to the Analysis of Periodontal Data
 Statistical methods for analyzing human genetic variation in diverse populations