Applied linear regression for longitudinal data : with an emphasis on missing observations / Frans E.S. Tan, Shahab Jolani

Von:

Tan, Frans [VerfasserIn]

Mitwirkende(r):

Jolani, Shahab [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Chapman & Hall/CRC texts in statistical science seriesVerlag: Boca Raton : Chapman & Hall/CRC, 2022Beschreibung: 1 Online-Ressource (1 volume) : illustrations (black and white, and colour)ISBN:

9781003121381
1003121381
1000798259
9781000798227
1000798224
9781000798258

Schlagwörter:

Andere physische Formen: 9780367634315 | 0367634317 | 9780367634315 | Erscheint auch als: Applied linear regression for longitudinal data. Druck-Ausgabe Boca Raton : Chapman & Hall/CRC, 2022LOC-Klassifikation:

QA278.2

Online-Ressourcen:

Zugang im Netz des KIT

Zusammenfassung: 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 backgroundPPN: PPN: 188264431XPackage identifier: Produktsigel: ZDB-4-NLEBK | BSZ-4-NLEBK-KAUB

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