Quasi‐Experiments
Bibliographic Data
| ID | 23702913 |
|---|---|
| Authors | Charles S Reichardt (0000-0002-6233-6795, University of Denver, corresponding author) |
| Year | 2015 |
| Pages | 1-14 |
| Publication date | 2015-05-15 |
| Open Access | Yes |
| Type | OTHER |
| Venue | Emerging Trends in the Social and Behavioral Sciences (JOURNAL) |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/9781118900772.etrds0270 |
| OpenAlex | W4231659958 |
| ISBN | 9781118900772 |
| Language | EN |
| References cited | 10 |
Quasi‐experiments are research designs used to estimate treatment effects when treatments are not assigned at random. Research in quasi‐experimentation will advance on four fronts. First, researchers will elaborate the complete array of quasi‐experimental comparisons. Second, researchers will refine statistical methods for taking account of initial selection differences. Third, researchers will both improve sensitivity analyses to take account of biases and create empirically based theories of the degree to which biases are removed. And fourth, researchers will assess how well quasi‐experiments address the full panoply of complications that arise in practice.
Data science · Design of experiments · Econometrics · Machine learning · Management science · Selection (genetic algorithm) · Sensitivity (control systems) · Statistics · Advanced Causal Inference Techniques · Computer Science · Engineering · Mathematics · Psychology · Statistical Methods and Inference · Statistical Methods in Clinical Trials
| Highly cited | No |
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