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The ability bias in the effect of field of study on wages has not been tested yet by IV methods due to difficulties in finding credible instrumental variables.
Using empirical data, we demonstrated the degree and direction of bias in the effect estimate when using these methods compared with multiple imputation (MI).
This empirical choice mitigates the problem of the immigration variable incorrectly picking up the tendency of immigrants to locate in areas with historically low levels of immigration through the 1989 average volunteering control and, therefore, create bias in the effect of immigration on the individual likelihood of volunteering.
There may be bias in the effect of the drugs.
However, in this situation, the algorithm we describe would still suggest that there is bias in the effect estimate.
However, this also gave potential for larger population heterogeneity, increasing the potential for confounding and therefore bias in the effect estimates.
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As a consequence some bias in the effects of need indicators and the adjustment for need can be expected.
Thus, the no-symptom group may contain some false negatives, which would lead to a conservative bias in the effects we describe.
We lacked measures of supply of health services, as well as direct measures of access to care, and thus bias in the effects of need indicators are possible.
For each paper, we examined the study design and assessed potential biases in the effect estimates.
Finally, we checked whether publication bias could be a bias source in the effect size estimates in our meta-analysis [ 44].
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