3 datasets found
  1. Most-to-Least Influential County-Level Economic Variables Contributing to...

    • plos.figshare.com
    xls
    Updated Jun 4, 2025
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    Michele L.F. Bolduc; Parya Saberi; Torsten B. Neilands; Carla I. Mercado; Shanice Battle Johnson; Zoe R. F. Freggens; Desmond Banks; Rashid Njai; Kai McKeever Bullard (2025). Most-to-Least Influential County-Level Economic Variables Contributing to County Prevalence of Poor Mental Health Based on Dominance Analysis Ranked by Standardized Dominance Weights, Overall and by Urban/Rural Classification, United States, 2019. [Dataset]. http://doi.org/10.1371/journal.pone.0300939.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Michele L.F. Bolduc; Parya Saberi; Torsten B. Neilands; Carla I. Mercado; Shanice Battle Johnson; Zoe R. F. Freggens; Desmond Banks; Rashid Njai; Kai McKeever Bullard
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Most-to-Least Influential County-Level Economic Variables Contributing to County Prevalence of Poor Mental Health Based on Dominance Analysis Ranked by Standardized Dominance Weights, Overall and by Urban/Rural Classification, United States, 2019.

  2. s

    Food for the poor USA Import & Buyer Data

    • seair.co.in
    Updated Jan 11, 2025
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    Seair Exim Solutions (2025). Food for the poor USA Import & Buyer Data [Dataset]. https://www.seair.co.in/us-importers/food-for-the-poor.aspx
    Explore at:
    .text/.csv/.xml/.xls/.binAvailable download formats
    Dataset updated
    Jan 11, 2025
    Dataset authored and provided by
    Seair Exim Solutions
    Area covered
    United States
    Description

    View Food for the poor import data USA including customs records, shipments, HS codes, suppliers, buyer details & company profile at Seair Exim.

  3. Beta Coefficients, 95% Confidence Interval, and Statistical Significance for...

    • plos.figshare.com
    xls
    Updated Jun 4, 2025
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    Michele L.F. Bolduc; Parya Saberi; Torsten B. Neilands; Carla I. Mercado; Shanice Battle Johnson; Zoe R. F. Freggens; Desmond Banks; Rashid Njai; Kai McKeever Bullard (2025). Beta Coefficients, 95% Confidence Interval, and Statistical Significance for County-Level Economic Variables Using Linear Regression with Prevalence of Poor Mental Health as the Dependent Variable, Overall and by Urban/Rural Classification, United States, 2019. Blue-filled cells indicate a positive association between the variable and the dependent variable; red-filled cells indicate a negative association; greyed out cells indicate the variable was not significant; blank cells indicate a variable that was not included in the model. [Dataset]. http://doi.org/10.1371/journal.pone.0300939.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Michele L.F. Bolduc; Parya Saberi; Torsten B. Neilands; Carla I. Mercado; Shanice Battle Johnson; Zoe R. F. Freggens; Desmond Banks; Rashid Njai; Kai McKeever Bullard
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Beta Coefficients, 95% Confidence Interval, and Statistical Significance for County-Level Economic Variables Using Linear Regression with Prevalence of Poor Mental Health as the Dependent Variable, Overall and by Urban/Rural Classification, United States, 2019. Blue-filled cells indicate a positive association between the variable and the dependent variable; red-filled cells indicate a negative association; greyed out cells indicate the variable was not significant; blank cells indicate a variable that was not included in the model.

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Share
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Click to copy link
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Michele L.F. Bolduc; Parya Saberi; Torsten B. Neilands; Carla I. Mercado; Shanice Battle Johnson; Zoe R. F. Freggens; Desmond Banks; Rashid Njai; Kai McKeever Bullard (2025). Most-to-Least Influential County-Level Economic Variables Contributing to County Prevalence of Poor Mental Health Based on Dominance Analysis Ranked by Standardized Dominance Weights, Overall and by Urban/Rural Classification, United States, 2019. [Dataset]. http://doi.org/10.1371/journal.pone.0300939.t002
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Most-to-Least Influential County-Level Economic Variables Contributing to County Prevalence of Poor Mental Health Based on Dominance Analysis Ranked by Standardized Dominance Weights, Overall and by Urban/Rural Classification, United States, 2019.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 4, 2025
Dataset provided by
PLOShttp://plos.org/
Authors
Michele L.F. Bolduc; Parya Saberi; Torsten B. Neilands; Carla I. Mercado; Shanice Battle Johnson; Zoe R. F. Freggens; Desmond Banks; Rashid Njai; Kai McKeever Bullard
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
United States
Description

Most-to-Least Influential County-Level Economic Variables Contributing to County Prevalence of Poor Mental Health Based on Dominance Analysis Ranked by Standardized Dominance Weights, Overall and by Urban/Rural Classification, United States, 2019.

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