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|a (JST)3598783
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|a eng
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|a Manski, Charles F.
|e verfasserin
|4 aut
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|a Statistical Treatment Rules for Heterogeneous Populations
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|c 2004
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|a Text
|b txt
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|a An important objective of empirical research on treatment response is to provide decision makers with information useful in choosing treatments. This paper studies minimax-regret treatment choice using the sample data generated by a classical randomized experiment. Consider a utilitarian social planner who must choose among the feasible statistical treatment rules, these being functions that map the sample data and observed covariates of population members into a treatment allocation. If the planner knew the population distribution of treatment response, the optimal treatment rule would maximize mean welfare conditional on all observed covariates. The appropriate use of covariate information is a more subtle matter when only sample data on treatment response are available. I consider the class of conditional empirical success rules; that is, rules assigning persons to treatments that yield the best experimental outcomes conditional on alternative subsets of the observed covariates. I derive a closed-form bound on the maximum regret of any such rule. Comparison of the bounds for rules that condition on smaller and larger subsets of the covariates yields sufficient sample sizes for productive use of covariate information. When the available sample size exceeds the sufficiency boundary, a planner can be certain that conditioning treatment choice on more covariates is preferable (in terms of minimax regret) to conditioning on fewer covariates.
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|a Copyright 2004 Econometric Society
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|a Finite sample theory
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|a Large-deviations theory
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|a Minimax regret
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|a Randomized experiments
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|a Risk
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|a Social planner
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|a Statistical decision theory
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|a Treatment response
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Statistical sampling
|x Sampling methods
|x Random sampling
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Measures of variability
|x Sample size
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|a Information science
|x Data products
|x Datasets
|x Test data
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Decision theory
|x Statistical decision theory
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|a Political science
|x Political philosophy
|x Social contract
|x State of nature
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Central tendencies
|x Population mean
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|a Mathematics
|x Pure mathematics
|x Probability theory
|x Random variables
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|a Mathematics
|x Applied mathematics
|x Game theory
|x Minimax
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|a Mathematics
|x Pure mathematics
|x Probability theory
|x Probability interpretations
|x Frequentism
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Statistical sampling
|x Sampling methods
|x Data sampling
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|a research-article
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0 |
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|i Enthalten in
|t Econometrica
|d Wiley
|g 72(2004), 4, Seite 1221-1246
|w (DE-627)270425721
|w (DE-600)1477253-X
|x 14680262
|7 nnns
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773 |
1 |
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|g volume:72
|g year:2004
|g number:4
|g pages:1221-1246
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|u https://www.jstor.org/stable/3598783
|3 Volltext
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|d 72
|j 2004
|e 4
|h 1221-1246
|