Series:

Springer Series in Statistics

2 total works

Cover of Statistical Models Based on Counting Processes
Modern survival analysis and more general event history analysis may be effectively handled in the mathematical framework of counting processes, stochastic integration, martingale central limit theory and product integration. This book presents this theory, which has been the subject of an intense research activity during the past one-and-a-half decades. The exposition of the theory is integrated with the careful presentation of many practical examples, based almost exlusively on the authors' experience, with detailed numerical and graphical illustrations. "Statistical Models Based on Counting Processes" may be viewed as a research monograph for mathematical statisticians and biostatisticians, although almost all methods are given in sufficient detail to be used in practice by other mathematically oriented researchers studying event histories (demographers, econometricians, epidemiologists, actuariala mathematicians, reliability engineers, biologists). Much of the material has so far only been available in the journal literature (if at all), and a wide variety of researchers will find this an invlauable survey of the subject.

Cover of Model Assisted Survey Sampling
Featuring the model-assisted approach to estimation in surveys, this book stresses important general principles for estimation and analysis in surveys. This includes the use of modelling in sampling, stating the precision in survey estimates, the use of supplementary information from census or administrative files, nonresponse and missing data, regression and other types of statistical analysis of survey data, survey errors and error models and estimation for subpopulations and small areas. The book is intended for statistics students, survey methodologists and those engaged in survey research in a variety of disciplines.