2018
DOI: 10.1177/1053815118793430
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Using Propensity Score Weighting to Reduce Selection Bias in Large-Scale Data Sets

Abstract: Data sets from large-scale longitudinal surveys involving young children and families have become available for secondary analysis by researchers in a variety of fields. Researchers in early intervention have conducted secondary analyses of such data sets to explore relationships between nonmalleable and malleable factors and child outcomes, and to address issues of measurement. Survey data have been used to a lesser extent to examine plausible causal relationships between variables, perhaps due to the increas… Show more

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Cited by 26 publications
(16 citation statements)
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“…We used IPW to minimise selection bias due to responsiveness to the questionnaire in which maltreatment was reported. 27 This resulted in a good balance of the measured covariates between those who responded and did not respond to the online questionnaire (see online supplementary eFigure 3), therefore, reducing bias due to selective participation. Of note, unweighted estimates were similar to weighted estimates, indicating that bias due to selection to the online questionnaire did not substantially affect results (results available from authors on request).…”
Section: Strengths and Limitationsmentioning
confidence: 99%
“…We used IPW to minimise selection bias due to responsiveness to the questionnaire in which maltreatment was reported. 27 This resulted in a good balance of the measured covariates between those who responded and did not respond to the online questionnaire (see online supplementary eFigure 3), therefore, reducing bias due to selective participation. Of note, unweighted estimates were similar to weighted estimates, indicating that bias due to selection to the online questionnaire did not substantially affect results (results available from authors on request).…”
Section: Strengths and Limitationsmentioning
confidence: 99%
“…It cannot be generalized to all surgical procedures, and the results may differ for stable surgical teams. However, analyses based on stabilized IPT weighting reduce selection bias and make causal effects more plausible 40,59 . Effects of unmeasured co-variables and of ongoing developments, such as refined surgical procedures, cannot be ruled out.…”
Section: Discussionmentioning
confidence: 99%
“…Differences between survivor responders and non‐responders were evaluated using chi‐square tests or Fisher's exact tests as appropriate (Tables S1 and S2). To account for potential non‐response bias, demographic and treatment characteristics that differed between responders and non‐responders (Table S3) were incorporated into a propensity score through a logit model to determine the probability of participation 29 . The estimated propensity score was then used as a covariate in all regressions models.…”
Section: Methodsmentioning
confidence: 99%