Applied Linear Regression for Longitudinal Data: With an Emphasis on Missing Observations

This book provides best practices in longitudinal data analysis at an intermediate level, with a focus on visualizing techniques to understand statistical concepts and handle missing observations. It is ideal for researchers and students in epidemiological, health, social, and behavioral sciences.

Format: Hardback
Length: 226 pages
Publication date: 09 December 2022
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the realm of intermediate-level longitudinal data analysis, offering a concise yet profound exploration of best practices. By employing a minimalistic approach, it ensures that readers gain a deep understanding of statistical concepts without being overwhelmed by complex formulas. Instead, it employs visualizations to illustrate crucial techniques, making the subject matter accessible and engaging.

The book addresses the pressing need to comprehend the statistical nuances of longitudinal data analysis by presenting essential methods in a visually compelling manner. It elucidates diverse solutions, including multiple imputation, in a conceptual framework, while also clarifying the implications of missing observations through visualization techniques.

Key features of this invaluable resource include:

Comprehensive Coverage: The book provides a comprehensive treatment of longitudinal data analysis, encompassing a wide range of topics and applications. It serves as an ideal companion for researchers and students in epidemiological, health, social, and behavioral sciences who engage with longitudinal studies, regardless of their mathematical background.

Online Datasets and Examples: To enhance the learning experience, the book offers access to comprehensive datasets and examples online. These resources enable readers to apply the discussed methods and gain practical insights into real-world longitudinal data analysis scenarios.

State-of-the-Art Methods: The book presents state-of-the-art methods for dealing with missing observations in a non-technical manner, with a special focus on sensitivity analysis. By employing these techniques, researchers can obtain more reliable and accurate estimates and interpretations of longitudinal data.

Conceptualization of Comparative Studies: The book conceptualizes the analysis of comparative (experimental and observational) studies, providing valuable insights into the differences and similarities between these study designs. This knowledge is crucial for researchers seeking to draw meaningful conclusions from longitudinal data.

Clear and Concise Writing: The author's clear and concise writing style makes the book accessible to a wide audience, including those with limited statistical knowledge. It avoids jargon and technical terms, ensuring that readers can grasp the concepts and apply them effectively in their research endeavors.

In summary, this book is a valuable resource for researchers and students seeking to excel in longitudinal data analysis. By employing a visual and conceptual approach, it provides a comprehensive understanding of statistical concepts while offering practical insights and solutions to address the challenges of working with longitudinal data. Whether you are a novice or an experienced researcher, this book will undoubtedly enhance your analytical skills and contribute to your research endeavors.

Weight: 490g
Dimension: 162 x 240 x 23 (mm)
ISBN-13: 9780367634315