Extended Sensitivity Analysis for Heterogeneous Unmeasured Confounding with An Application to Sibling Studies of Returns to Education
| Autor: | Raiden B. Hasegawa, Colin B. Fogarty |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Statistics and Probability FOS: Computer and information sciences quadratic programming 01 natural sciences Methodology (stat.ME) 010104 statistics & probability 03 medical and health sciences Statistics Sensitivity (control systems) 0101 mathematics Sibling causal inference Robustness (economics) Observational studies Statistics - Methodology Mathematics Earnings Cognition hidden bias 030104 developmental biology Modeling and Simulation Causal inference nuisance parameters Observational study Statistics Probability and Uncertainty superpopulation inference Type I and type II errors |
| Zdroj: | arXiv Ann. Appl. Stat. 13, no. 2 (2019), 767-796 |
| DOI: | 10.48550/arxiv.1711.05570 |
| Popis: | The conventional model for assessing insensitivity to hidden bias in paired observational studies constructs a worst-case distribution for treatment assignments subject to bounds on the maximal bias to which any given pair is subjected. In studies where rare cases of extreme hidden bias are suspected, the maximal bias may be substantially larger than the typical bias across pairs, such that a correctly specified bound on the maximal bias would yield an unduly pessimistic perception of the study's robustness to hidden bias. We present an extended sensitivity analysis which allows researchers to simultaneously bound the maximal and typical bias perturbing the pairs under investigation while maintaining the desired Type I error rate. We motivate and illustrate our method with two sibling studies on the impact of schooling on earnings, one containing information of cognitive ability of siblings and the other not. Cognitive ability, clearly influential of both earnings and degree of schooling, is likely similar between members of most sibling pairs yet could, conceivably, vary drastically for some siblings. The method is straightforward to implement, simply requiring the solution to a quadratic program. Comment: Both authors contributed equally to this work |
| Databáze: | OpenAIRE |
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