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konfound: Command to quantify robustness of causal inferences.
- Source :
-
Stata Journal . Sep2019, Vol. 19 Issue 3, p523-550. 28p. - Publication Year :
- 2019
-
Abstract
- Statistical methods that quantify the discourse about causal inferences in terms of possible sources of biases are becoming increasingly important to many social-science fields such as public policy, sociology, and education. These methods are also known as "robustness or sensitivity analyses". A series of recent works (Frank [2000, Sociological Methods and Research 29: 147-194]; Pan and Frank [2003, Journal of Educational and Behavioral Statistics 28: 315-337]; Frank and Min [2007, Sociological Methodology 37: 349-392]; and Frank et al. [2013, Educational Evaluation and Policy Analysis 35: 437-460]) on robustness analysis extends earlier methods. We implement these recent developments in Stata. In particular, we provide commands to quantify the percent bias necessary to invalidate an inference from a Rubin causal model framework and the robustness of causal inferences in terms of correlations associated with unobserved variables. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1536867X
- Volume :
- 19
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Stata Journal
- Publication Type :
- Academic Journal
- Accession number :
- 138764528
- Full Text :
- https://doi.org/10.1177/1536867X19874223