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Unobserved but not unimportant: The effects of unmeasured variables on causal attributions

Coe, R.

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Authors

R. Coe



Abstract

The objective of the present study was to estimate how much difference the inclusion of plausibly important but unmeasured variables could make to estimates of the effects of educational programmes. Two examples of policy-relevant research in education were identified. A sensitivity analysis using Monte Carlo simulation was conducted to estimate the size of a possible spurious 'effect' that could actually be entirely due to the failure to incorporate a plausible unobserved variable. In both examples the effect size reported in the original study was within the range of possible spurious effects. What appeared to the original researchers to be substantial and unequivocal causal effects were reduced to tiny and uncertain differences when the effects of plausible unobserved differences were taken into account. Evaluators who rely on statistical control should be more cautious in making causal claims, consider possible effects of unmeasured variables and conduct sensitivity analyses. Alternatively, stronger designs should be used.

Citation

Coe, R. (2009). Unobserved but not unimportant: The effects of unmeasured variables on causal attributions. Effective education, 1(2), 101-122. https://doi.org/10.1080/19415530903522519

Journal Article Type Article
Publication Date Sep 1, 2009
Deposit Date Feb 10, 2010
Publicly Available Date Apr 1, 2011
Journal Effective Education
Print ISSN 1941-5532
Electronic ISSN 1941-5540
Publisher Taylor and Francis
Peer Reviewed Peer Reviewed
Volume 1
Issue 2
Pages 101-122
DOI https://doi.org/10.1080/19415530903522519
Keywords Selection bias, Unobserved variables, Causal inference, Sensitivity analysis, Monte Carlo simulation, Education. policy.

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