Using recursive partitioning to find and estimate heterogenous treatment effects in randomized clinical trials

Berk, Richard; Olson, Matthew; Buja, Andreas; Ouss, Aurélie

doi:10.1007/s11292-019-09410-0

Using recursive partitioning to find and estimate heterogenous treatment effects in randomized clinical trials

When for an RCT heterogeneous treatment effects are inductively obtained, significant complications are introduced. Special loss functions may be needed to find local, average treatment effects followed by techniques that properly address post-selection statistical inference., Reanalyzing a recidivi...

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Bibliographische Detailangaben
1. VerfasserIn:	Berk, Richard (VerfasserIn)
Beteiligte:	Olson, Matthew ; Buja, Andreas ; Ouss, Aurélie
Medienart:	Elektronisch Aufsatz
Sprache:	Englisch
Veröffentlicht:	2021
In:	Journal of experimental criminology Jahr: 2021, Band: 17, Heft: 3, Seiten: 519-538
Online-Zugang:	Volltext (lizenzpflichtig)
Journals Online & Print:	Lade...
Verfügbarkeit prüfen:	HBZ Gateway
Schlagwörter:	Decision trees Post-selection statistical inference Heterogeneous treatment effects Randomized experiments