Metodbevispost

Difference-in-Means Estimator

The difference-in-means estimator is the design-based workhorse for analyzing randomized experiments: it estimates the average treatment effect simply as the difference between the average outcome among treated units and the average outcome among control units. Rooted in Jerzy Neyman's potential-outcomes framework and central to modern treatments by Imbens and Rubin and by Gerber and Green, it is unbiased under randomization, comes with a conservative Neyman variance estimator, and supports exact randomization inference, requiring no model of how outcomes are generated.

Sources recorded, not reviewed

Källpost

Citat kopierade ordagrant från metodens källpost. Ingen verifiering på källnivå härleds från dem.

Difference-in-Means Estimator for Randomized Experiments

Taxonomisk metodpost · process-pipeline / political-science

Gerber, A. S., & Green, D. P. (2012). Field Experiments: Design, Analysis, and Interpretation. New York: W. W. Norton. · ISBN 9780393979954
Imbens, G. W., & Rubin, D. B. (2015). Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. Cambridge: Cambridge University Press. · ISBN 9780521885881

Öppna fullständig metod

Kuraterade påståenden

Påståenden lagrade i bevisloggen, var och en med sin egen bedömning.

Inga kuraterade påståenden ännu

Denna vy hittar inte på en påståendebedömning när loggen saknar en.

Relaterade metoder

Genererade från metodgrafen och visade som maskinföreslagna relationer – inga bevispåståenden härleds.

Same method familyAudit Experimentmachine-suggested · Relational suggestion, not evidence.Same method familyField Experiment in Politicsmachine-suggested · Relational suggestion, not evidence.Same method familyNatural Experiment in Politicsmachine-suggested · Relational suggestion, not evidence.Same method familySurvey Experimentmachine-suggested · Relational suggestion, not evidence.