Statistical Methods in Psychiatry and Related Fields
Longitudinal, Clustered, and Other Repeated Measures Data
Chapman & Hall/CRC Interdisciplinary Statistics Series

Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations.

Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics.

This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time.

Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details.

Features

• Provides an overview of intermediate to advanced statistical methods applied to psychiatry.



• Takes a non-technical approach with mathematical details kept to a minimum.





• Includes lots of detailed examples from published studies in psychiatry and related fields.





• Software programs, data sets and output are available on a supplementary website.

The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians.

The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data.

Ralitza Gueorguieva is a Senior Research Scientist at the Department of Biostatistics, Yale School of Public Health.

She has more than 20 years experience in statistical methodology development and collaborations with psychiatrists and other researchers, and is the author of over 130 peer-reviewed publications.

Introduction

Traditional Methods for Analysis of Longitudinal and Clustered Data

Linear Mixed Models for Longitudinal and Clustered Data

Linear Models for Non-normal Outcomes

Nonparametric Methods for the Analysis of Repeatedly Measured Data

Post-hoc Analysis and Adjustments for Multiple Comparisons

Handling of Missing Data and Dropout in Longitudinal Studies

Controlling for Covariates in Studies with Repeated Measures

Assessment of Moderator and Mediator Effects

Mixture Models for Trajectory Analyses

Study Design and Sample Size Calculations

Summary and Further Readings

Ralitza Gueorguieva is a Senior Research Scientist at the Department of Biostatistics, Yale School of Public Health. She has more than 20 years experience in statistical methodology development and collaborations with psychiatrists and other researchers, and is the author of over 130 peer-reviewed publications.