Bøger af Michael Smithson

The book brings together material on the analysis of limited and bounded variables that is scattered across the literature in several disciplines, and presents it in a style that is both more accessible and up-to-date. The authors provide worked examples in each chapter using real datasets from a variety of disciplines. The software used for the examples include R, SAS, and Stata. The data, software code, and detailed explanations of the example models are available on an accompanying website.

Designed for graduate students and researchers in the behavioral, social, health, and medical sciences, this text employs generalized linear models, including mixed models, for categorical and limited dependent variables. Categorical variables include both nominal and ordinal variables. Discrete or continuous limited dependent variables have restricted support, whether through censorship or truncation or by their nature. The book incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages.

Research from the fields of cognitive psychology, social psychology, organizational studies, sociology, and social anthroplogy are reviewed here in anticipation of what Dr. Smithson characterizes as the beginning of a "creative dialogue between these researchers".

Introduces the basis of the confidence interval framework and provides the criteria for 'best' confidence intervals, along with the trade-offs between confidence and precision. This book covers topics such as the transformation principle, confidence intervals, and the relationship between confidence interval and significance testing frameworks.

Fuzzy set theory deals with sets or categories whose boundaries are blurry or, in other words, 'fuzzy.' This book presents an introduction to fuzzy set theory, focusing on its applicability to the social sciences. It provides a guide for researchers wishing to combine fuzzy set theory with standard statistical techniques and model-testing.