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Oh No! They Cut My Funding! Using "Post Hoc" Planned Missing Data Designs to Salvage Longitudinal Research.

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Title: Oh No! They Cut My Funding! Using "Post Hoc" Planned Missing Data Designs to Salvage Longitudinal Research.
Authors: Feng, Yi (AUTHOR), Hancock, Gregory R. (AUTHOR)
Source: Child Development. May/Jun2021, Vol. 92 Issue 3, p1199-1216. 18p. 4 Diagrams, 2 Charts, 3 Graphs.
Subjects: Child development, Child development research, Research funding, Child psychology, Longitudinal method
Abstract: Having one's funding cut in the course of conducting a longitudinal study has become an increasingly real challenge faced by developmental researchers. The main purpose of the current work is to propose "post hoc" planned missing (PHPM) data designs as a promising solution in such difficult situations. This study discusses general guidelines that can be followed to search for viable PHPM designs within a given budget restriction. Illustrative examples across different longitudinal research contexts are provided, each showing how PHPM data designs can help salvage longitudinal studies when an unexpected funding cut occurs mid‐study. With the illustrative examples, the article also shows how developmental researchers can conveniently identify viable designs using the R package simPM. [ABSTRACT FROM AUTHOR]
Copyright of Child Development is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Label: Title
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  Data: Oh No! They Cut My Funding! Using "Post Hoc" Planned Missing Data Designs to Salvage Longitudinal Research.
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  Data: <searchLink fieldCode="AR" term="%22Feng%2C+Yi%22">Feng, Yi</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hancock%2C+Gregory+R%2E%22">Hancock, Gregory R.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Child+Development%22">Child Development</searchLink>. May/Jun2021, Vol. 92 Issue 3, p1199-1216. 18p. 4 Diagrams, 2 Charts, 3 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Child+development%22">Child development</searchLink><br /><searchLink fieldCode="DE" term="%22Child+development+research%22">Child development research</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Child+psychology%22">Child psychology</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink>
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  Label: Abstract
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  Data: Having one's funding cut in the course of conducting a longitudinal study has become an increasingly real challenge faced by developmental researchers. The main purpose of the current work is to propose "post hoc" planned missing (PHPM) data designs as a promising solution in such difficult situations. This study discusses general guidelines that can be followed to search for viable PHPM designs within a given budget restriction. Illustrative examples across different longitudinal research contexts are provided, each showing how PHPM data designs can help salvage longitudinal studies when an unexpected funding cut occurs mid‐study. With the illustrative examples, the article also shows how developmental researchers can conveniently identify viable designs using the R package simPM. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Child Development is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=150671914
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        Value: 10.1111/cdev.13501
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 1199
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      – SubjectFull: Child development
        Type: general
      – SubjectFull: Child development research
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Child psychology
        Type: general
      – SubjectFull: Longitudinal method
        Type: general
    Titles:
      – TitleFull: Oh No! They Cut My Funding! Using "Post Hoc" Planned Missing Data Designs to Salvage Longitudinal Research.
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            NameFull: Feng, Yi
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            NameFull: Hancock, Gregory R.
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              M: 05
              Text: May/Jun2021
              Type: published
              Y: 2021
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