This book provides a practical guide to the analysis of data from randomized controlled trials (RCT). It gives an answer to the question of how to estimate the intervention effect in an appropriate way. This problem is examined for different RCT designs, such as RCTs with one follow-up measurement, RCTs with more than one follow-up measurement, cluster RCTs, cross-over trials, stepped wedge trials, and N-of-1 trials. The statistical methods are explained in a non-mathematical way and are illustrated by extensive examples. All datasets used in the book are available for download, so readers can reanalyse the examples to gain a better understanding of the methods used. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other fields.
Introduction.- Analysis of RCT data with one follow-up measurement.- Analysis of RCT data with more than one follow-up measurement.- Analysis of data from a cluster RCT.- Analysis of data from a cross-over trial.- Analysis of data from stepped wedge trials.- Analysis of data from N-of-1 trials.- Dichotomous outcomes.- What to do when only a baseline measurement is available.- Sample size calculations.
Jos Twisk is a professor in applied biostatistics at the Amsterdam University Medical Centre, where he is the director of the Epidemiology Master Program and head of the Expertise Centre for Applied Longitudinal Data Analysis. He has written several textbooks varying from the basic principles of applied biostatistics to applied longitudinal data analysis and applied mixed model analysis. His main activities include applied methodological research, consulting and teaching courses on mixed model analysis, longitudinal data analysis, multilevel analysis, applied basic statistics and the analysis of RCT data. He has authored and co-authored more than 1000 peer-reviewed international papers.
This book provides a practical guide to the analysis of data from randomized controlled trials (RCT). It gives an answer to the question of how to estimate the intervention effect in an appropriate way. This problem is examined for different RCT designs, such as RCTs with one follow-up measurement, RCTs with more than one follow-up measurement, cluster RCTs, cross-over trials, stepped wedge trials, and N-of-1 trials. The statistical methods are explained in a non-mathematical way and are illustrated by extensive examples. All datasets used in the book are available for download, so readers can reanalyse the examples to gain a better understanding of the methods used. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other fields.