Sensitivity Analysis for Binary Outcome Misclassification in Randomization Tests via Integer Programming

Conducting a randomization test is a common method for testing causal null hypotheses in randomized experiments. The popularity of randomization tests is largely because their statistical validity only depends on the randomization design, and no distributional or modeling assumption on the outcome v...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Journal of computational and graphical statistics Ročník 34; číslo 4; s. 1528 - 1541
Hlavní autori:	Heng, Siyu, Shaw, Pamela A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Taylor & Francis 02.10.2025 Taylor & Francis Ltd
Predmet:	Accuracy Design-based causal inference Fisher's sharp null Integer programming Matched observational studies Neyman's weak null Randomization Randomization inference Sensitivity analysis Warning randomization inference Neyman’s weak null Fisher’s sharp null integer programming matched observational studies design-based causal inference
ISSN:	1061-8600, 1537-2715
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!