Identifying multilevel predictors of behavioral outcomes like park use: A comparison of conditional and marginal modeling approaches Article Swipe
Marilyn E. Wende
,
S. Morgan Hughey
,
Alexander C. McLain
,
Shirelle H. Hallum
,
J. Aaron Hipp
,
Jasper Schipperijn
,
Ellen W. Stowe
,
Andrew T. Kaczynski
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0301549
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0301549
This study compared marginal and conditional modeling approaches for identifying individual, park and neighborhood park use predictors. Data were derived from the ParkIndex study, which occurred in 128 block groups in Brooklyn (New York), Seattle (Washington), Raleigh (North Carolina), and Greenville (South Carolina). Survey respondents (n = 320) indicated parks within one half-mile of their block group used within the past month. Parks (n = 263) were audited using the Community Park Audit Tool. Measures were collected at the individual (park visitation, physical activity, sociodemographic characteristics), park (distance, quality, size), and block group (park count, population density, age structure, racial composition, walkability) levels. Generalized linear mixed models and generalized estimating equations were used. Ten-fold cross validation compared predictive performance of models. Conditional and marginal models identified common park use predictors: participant race, participant education, distance to parks, park quality, and population >65yrs. Additionally, the conditional mode identified park size as a park use predictor. The conditional model exhibited superior predictive value compared to the marginal model, and they exhibited similar generalizability. Future research should consider conditional and marginal approaches for analyzing health behavior data and employ cross-validation techniques to identify instances where marginal models display superior or comparable performance.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0301549
- https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0301549&type=printable
- OA Status
- gold
- Cited By
- 1
- References
- 89
- Related Works
- 10
- OpenAlex ID
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https://openalex.org/W4394841269Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pone.0301549Digital Object Identifier
- Title
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Identifying multilevel predictors of behavioral outcomes like park use: A comparison of conditional and marginal modeling approachesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-04-16Full publication date if available
- Authors
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Marilyn E. Wende, S. Morgan Hughey, Alexander C. McLain, Shirelle H. Hallum, J. Aaron Hipp, Jasper Schipperijn, Ellen W. Stowe, Andrew T. KaczynskiList of authors in order
- Landing page
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https://doi.org/10.1371/journal.pone.0301549Publisher landing page
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0301549&type=printableDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0301549&type=printableDirect OA link when available
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Marginal model, Multilevel model, Statistics, Econometrics, Psychology, Regression analysis, MathematicsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.characteristics), | 85 |
| abstract_inverted_index.generalizability. | 170 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5008358084, https://openalex.org/A5049015330, https://openalex.org/A5042682670, https://openalex.org/A5051069727, https://openalex.org/A5085390694, https://openalex.org/A5040578884, https://openalex.org/A5055523232, https://openalex.org/A5029940529 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I137902535, https://openalex.org/I155781252, https://openalex.org/I177969490, https://openalex.org/I204593131, https://openalex.org/I33213144 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.76081311 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |