This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract math
Applied Linear Regression for Longitudinal Data
โ Scribed by Frans E.S. Tan, Shahab Jolani
- Publisher
- CRC Press/Chapman & Hall
- Year
- 2022
- Tongue
- English
- Leaves
- 248
- Series
- Chapman & Hall/CRC Texts in Statistical Science
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas. Different solutions such as multiple imputation are explained conceptually and consequences of missing observations are clarified using visualization techniques. Key features include the following:
- Provides datasets and examples online
- Gives state-of-the-art methods of dealing with missing observations in a non-technical way with a special focus on sensitivity analysis
- Conceptualises the analysis of comparative (experimental and observational) studies
It is the ideal companion for researchers and students in epidemiological, health, and social and behavioral sciences working with longitudinal studies without a mathematical background.
๐ SIMILAR VOLUMES
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance
<p><P>This paperback edition is a reprint of the 2000 edition.</P><P></P><P>This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, suc
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this book puts major emphasis on exploratory data analysis for all aspects of the model. Several variations to the conventional linear mixed model are discussed. Most anal