UID:
almahu_9949434895602882
Format:
1 online resource (1 volume) :
,
illustrations (black and white, and colour).
ISBN:
9781003121381
,
1003121381
,
9781000798258
,
1000798259
,
9781000798227
,
1000798224
Series Statement:
Chapman & Hall/CRC texts in statistical science series
Content:
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.
Additional Edition:
Print version: Tan, Frans. Applied linear regression for longitudinal data. Boca Raton : Chapman & Hall/CRC, 2022 ISBN 9780367634315
Language:
English
DOI:
10.1201/9781003121381
URL:
https://www.taylorfrancis.com/books/9781003121381
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