Longitudinal Studies 2 : Modeling Data Using Multivariate Analysis

Statistical models are used to study the relationship between exposure and disease while accounting for the potential role of other factors' impact upon outcomes. This adjustment is useful to obtain unbiased estimates of true effects or to predict future outcomes. Statistical models include a systematic and an error component. The systematic component explains the variability of the response variable as a function of the predictors and is summarized in the effect estimates (model coefficients). The error element of the model represents the variability in the data unexplained by the model and is used to build measures of precisions around the point estimates (Confidence Intervals).

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:2249

Enthalten in:

Methods in molecular biology (Clifton, N.J.) - 2249(2021) vom: 19., Seite 103-124

Sprache:

Englisch

Beteiligte Personen:

Ravani, Pietro [VerfasserIn]
Barrett, Brendan J [VerfasserIn]
Parfrey, Patrick S [VerfasserIn]

Links:

Volltext

Themen:

Confounding; interaction
Effect estimates
Estimate precision
Journal Article
Multivariable analysis
Regression methods
Statistical models

Anmerkungen:

Date Completed 22.06.2021

Date Revised 22.06.2021

published: Print

Citation Status MEDLINE

doi:

10.1007/978-1-0716-1138-8_7

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM324264569