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Among the important scientific developments of the 20th century is the explosive growth in statistical reasoning and methods for application to studies of human health. Examples include developments in likelihood methods for inference, epidemiologic statistics, clinical trials, survival analysis, and statistical genetics. Substantive problems in public health and biomedical research have fueled the development of statistical methods, which in turn have improved our ability to draw valid inferences from data. The objective of Biostatistics is to advance statistical science and its application to problems of human health and disease, with the ultimate goal of advancing the public's health.

Publisher: Oxford University Press

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Volume 10, Number 2, 8 April 2009

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Generalized linear models with unspecified reference distribution
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Modified test statistics by inter-voxel variance shrinkage with an application to f MRI
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Biomarker evaluation and comparison using the controls as a reference population
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A new serially correlated gamma-frailty process for longitudinal count data
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Measurement error caused by spatial misalignment in environmental epidemiology
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Optimal multistage designsa general framework for efficient genome-wide association studies
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Optimal 2-stage design with given power in association studies
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Statistical independence of the colocalized association signals for type 1 diabetes and RPS26 gene expression on chromosome 12q13
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Bayesian graphical models for regression on multiple data sets with different variables
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Microarray background correction: maximum likelihood estimation for the normalexponential convolution
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A robust method for finely stratified familial studies with proband-based sampling
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Bias in 2-part mixed models for longitudinal semicontinuous data
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A Bayesian model for evaluating influenza antiviral efficacy in household studies with asymptomatic infections
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