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Skewed logit model for analyzing correlated infant morbidity data

Skewed logit model for analyzing correlated infant morbidity data

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b9852b9685c54e45af35d7b7f8901028

Skewed logit model for analyzing correlated infant morbidity data

About this item

Full title

Skewed logit model for analyzing correlated infant morbidity data

Publisher

United States: Public Library of Science

Journal title

PloS one, 2021-02, Vol.16 (2), p.e0246269-e0246269

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

Infant morbidity is a topic of interest because it is used globally as an indicator of the status of health care in a country. A large body of evidence supports an association between bacterial vaginosis (BV) and infant morbidity. When estimating the relationship between the predictors and the estimated variable of morbidity severity, the latter ex...

Alternative Titles

Full title

Skewed logit model for analyzing correlated infant morbidity data

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_b9852b9685c54e45af35d7b7f8901028

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b9852b9685c54e45af35d7b7f8901028

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0246269

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