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type="main" xml:id="rssb12027-abs-0001" <title type="main">Summary</title> <p>The propensity score plays a central role in a variety of causal inference settings. In particular, matching and weighting methods based on the estimated propensity score have become increasingly common in the analysis of observational data....</p>
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In their landmark study of a field experiment, Gerber and Green (2000) found that get-out-the-vote calls reduce turnout by five percentage points. In this article, I introduce statistical methods that can uncover discrepancies between experimental design and actual implementation. The...
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We attempt to clarify, and suggest how to avoid, several serious misunderstandings about and fallacies of causal inference. These issues concern some of the most fundamental advantages and disadvantages of each basic research design. Problems include improper use of hypothesis tests for...
Persistent link: https://www.econbiz.de/10005316036
Missing data are frequently encountered in the statistical analysis of randomized experiments. I propose statistical methods that can be used to analyse randomized experiments with a non-ignorable missing binary outcome where the missing data mechanism may depend on the unobserved values of the...
Persistent link: https://www.econbiz.de/10005334909
Many randomized experiments suffer from the "truncation-by-death" problem where potential outcomes are not defined for some subpopulations. For example, in medical trials, quality-of-life measures are only defined for surviving patients. In this article, I derive the sharp bounds on causal...
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