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- W82903766 abstract "This article explores strengths of randomization to enhance the appropriateness of using statistical theory to make causal inferences. The goal of randomization is to obtain an unbiased estimate of a treatment effect by eliminating any noncomparability between experimental units (observations) that might introduce error when generating causal statements. A randomization plan renders any systematic source of bias that could plausibly affect treatment outcomes, as random noise. Philosophical issues of causation are also addressed in the context of hypothesis testing and equilibrating experimental units. Experimental designs using randomization offset certain threats to internal validity; however, in some cases, alternative approaches – such as regression discontinuity and propensity score methods – may be required to institute controls where randomization is not appropriate. This article examines these alternative strategies as viable alternatives to randomization where tight laboratory controls may not be feasible in complex field settings." @default.
- W82903766 created "2016-06-24" @default.
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- W82903766 date "2010-01-01" @default.
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- W82903766 title "Methods for Approximating Random Assignment: Regression Discontinuity and Propensity Scores" @default.
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- W82903766 doi "https://doi.org/10.1016/b978-0-08-044894-7.01715-2" @default.
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