Handle with Care: A Sociologist's Guide to Causal Inference with Instrumental Variables
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| Title: | Handle with Care: A Sociologist's Guide to Causal Inference with Instrumental Variables |
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| Language: | English |
| Authors: | Chris Felton (ORCID |
| Source: | Sociological Methods & Research. 2026 55(1):3-50. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 48 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Evaluative |
| Descriptors: | Social Science Research, Sociology, Statistical Inference, Statistical Bias, Computation, Research Methodology |
| DOI: | 10.1177/00491241241235900 |
| ISSN: | 0049-1241 1552-8294 |
| Abstract: | Instrumental variables (IV) analysis is a powerful, but fragile, tool for drawing causal inferences from observational data. Sociologists increasingly turn to this strategy in settings where unmeasured confounding between the treatment and outcome is likely. This paper reviews the assumptions required for IV and the consequences of violating them, focusing on sociological applications. We highlight three methodological problems IV faces: (i) identification bias, an asymptotic bias from assumption violations; (ii) estimation bias, a finite-sample bias that persists even when assumptions hold; and (iii) type-M error, the exaggeration of effect size given statistical significance. In each case, we emphasize how weak instruments exacerbate these problems and make results sensitive to minor violations of assumptions. We survey IV papers from top sociology journals, finding that assumptions often go unstated and robust uncertainty measures are rarely used. We provide a practical checklist to show how IV, despite its fragility, can still be useful when handled with care. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1495936 |
| Database: | ERIC |
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