[Logistic regression].
Regresión logística.
Confounding and interaction variables
Función sigmoidea
Logistic regression
Maximum likelihood
Máxima verosimilitud
Regresión logística
Sigmoid function
Variables de confusión y de interacción
Journal
Semergen
ISSN: 1578-8865
Titre abrégé: Semergen
Pays: Spain
ID NLM: 9610769
Informations de publication
Date de publication:
11 Oct 2023
11 Oct 2023
Historique:
received:
10
07
2023
accepted:
22
08
2023
medline:
13
10
2023
pubmed:
13
10
2023
entrez:
13
10
2023
Statut:
aheadofprint
Résumé
Logistic regression is a group of statistical techniques that aim to test hypotheses or causal relationships between a categorical dependent variable and other independent variables that can be categorical and quantitative. Through this model we intend to study the probability that the event studied will occur based on some variables that we assume are relevant or influential. In this method it is necessary to detect effect modifier and confounding variables. Its parameters are estimated with the maximum likelihood method through a process with successive iterations.
Identifiants
pubmed: 37832165
pii: S1138-3593(23)00166-1
doi: 10.1016/j.semerg.2023.102086
pii:
doi:
Types de publication
English Abstract
Journal Article
Langues
spa
Sous-ensembles de citation
IM
Pagination
102086Informations de copyright
Copyright © 2023 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.