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Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results
In studies involving human subjects, voluntary participation may lead to sampling bias, thus limiting the generalizability of findings. This effect may be especially pronounced in developmental studies, where parents serve as both the primary environmental input and decision maker of whether their c...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MIT Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323845/ https://www.ncbi.nlm.nih.gov/pubmed/32617442 http://dx.doi.org/10.1162/opmi_a_00031 |
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author | Yu, Yue Shafto, Patrick Bonawitz, Elizabeth |
author_facet | Yu, Yue Shafto, Patrick Bonawitz, Elizabeth |
author_sort | Yu, Yue |
collection | PubMed |
description | In studies involving human subjects, voluntary participation may lead to sampling bias, thus limiting the generalizability of findings. This effect may be especially pronounced in developmental studies, where parents serve as both the primary environmental input and decision maker of whether their child participates in a study. We present a novel empirical and modeling approach to estimate how parental consent may bias measurements of children’s behavior. Specifically, we coupled naturalistic observations of parent–child interactions in public spaces with a behavioral test with children, and used modeling methods to impute the behavior of children who did not participate. Results showed that parents’ tendency to use questions to teach was associated with both children’s behavior in the test and parents’ tendency to participate. Exploiting these associations with a model-based multiple imputation and a propensity score–matching procedure, we estimated that the means of the participating and not-participating groups could differ as much as 0.23 standard deviations for the test measurements, and standard deviations themselves are likely underestimated. These results suggest that ignoring factors associated with consent may lead to systematic biases when generalizing beyond lab samples, and the proposed general approach provides a way to estimate these biases in future research. |
format | Online Article Text |
id | pubmed-7323845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MIT Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-73238452020-06-30 Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results Yu, Yue Shafto, Patrick Bonawitz, Elizabeth Open Mind (Camb) Research Articles In studies involving human subjects, voluntary participation may lead to sampling bias, thus limiting the generalizability of findings. This effect may be especially pronounced in developmental studies, where parents serve as both the primary environmental input and decision maker of whether their child participates in a study. We present a novel empirical and modeling approach to estimate how parental consent may bias measurements of children’s behavior. Specifically, we coupled naturalistic observations of parent–child interactions in public spaces with a behavioral test with children, and used modeling methods to impute the behavior of children who did not participate. Results showed that parents’ tendency to use questions to teach was associated with both children’s behavior in the test and parents’ tendency to participate. Exploiting these associations with a model-based multiple imputation and a propensity score–matching procedure, we estimated that the means of the participating and not-participating groups could differ as much as 0.23 standard deviations for the test measurements, and standard deviations themselves are likely underestimated. These results suggest that ignoring factors associated with consent may lead to systematic biases when generalizing beyond lab samples, and the proposed general approach provides a way to estimate these biases in future research. MIT Press 2020-03-01 /pmc/articles/PMC7323845/ /pubmed/32617442 http://dx.doi.org/10.1162/opmi_a_00031 Text en © 2020 Massachusetts Institute of Technology https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Articles Yu, Yue Shafto, Patrick Bonawitz, Elizabeth Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results |
title | Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results |
title_full | Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results |
title_fullStr | Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results |
title_full_unstemmed | Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results |
title_short | Inconvenient Samples: Modeling Biases Related to Parental Consent by Coupling Observational and Experimental Results |
title_sort | inconvenient samples: modeling biases related to parental consent by coupling observational and experimental results |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323845/ https://www.ncbi.nlm.nih.gov/pubmed/32617442 http://dx.doi.org/10.1162/opmi_a_00031 |
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