Performance metrics for models designed to predict treatment effect.

Maas, C C H M; Kent, D M; Hughes, M C; Dekker, R; Lingsma, H F; van Klaveren, D

Maas, C C H M; Kent, D M; Hughes, M C; Dekker, R; Lingsma, H F; van Klaveren, D.

Afiliación

Maas CCHM; Department of Public Health, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, Netherlands. c.h.m.maas@erasmusmc.nl.
Kent DM; Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, USA.
Hughes MC; Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, USA.
Dekker R; Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, Netherlands.
Lingsma HF; Department of Public Health, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, Netherlands.
van Klaveren D; Department of Public Health, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, Netherlands.

BMC Med Res Methodol ; 23(1): 165, 2023 07 08.

Article en En | MEDLINE | ID: mdl-37422647

Asunto(s)

Modelos Teóricos; Ensayos Clínicos Controlados Aleatorios como Asunto; Humanos; Calibración

Palabras clave

Causal forest; Heterogeneous treatment effect; Logistic regression; Prediction models

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ensayos Clínicos Controlados Aleatorios como Asunto / Modelos Teóricos Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article

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