This handbook provides quick access to common and specialized probability distributions for modeling practical problems and performing statistical calculations. This second edition enhances the PC calculator StatCalc with electronic help manuals and now contains R functions for cases where StatCalc ..
This handbook provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, with a primary focus on case-control studies in epidemiology. Authors will be encouraged to illustrate the statistical methods they describe by..
Offers a treatment of different kinds of James-Stein and ridge regression estimators from a frequentist and Bayesian point of view. The book explains and compares estimators analytically as well as numerically and includes Mathematica and Maple programs used in numerical comparison.;College or unive..
This book introduces the authors’ recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The book covers the foundational motivations for this new approach, the bas..
Focusing on the important role that statistical methods play in the analysis of the data collected as well as in the overall clinical trial process, Introduction to Randomized Controlled Clinical Trials provides a concise and accessible introduction to clinical trials. This second edition features n..
Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets an..
Longitudinal studies often investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest. An example is prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. This book provides a fu..
Kernal Smoothing provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers. This is facilitated by the authors' focus on the simplest settings, namely density estimation and nonparametric regression. They pay particular attention to the problem of..
Local Polynomial Modelling and Its Applications describes data-analytic approaches to regression problems encountered in many scientific disciplines. These nonparametric methods are powerful in exploring fine structural relationships and yield useful diagnostic tools for parametric models. The autho..