2021
DOI: 10.1371/journal.pone.0246269
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Skewed logit model for analyzing correlated infant morbidity data

Abstract: Background 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 exhibits imbalanced data, which means that violation of symmetry is expected. Two competing methods of analysis, that is, (1) probit and (2) logit technique… Show more

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Cited by 6 publications
(3 citation statements)
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“…Our data were clustered by counties; thus, an exchangeable correlation structure is the most flexible in modeling the association through the generalized estimation equations (GEE) approach. Notably, both independent [30] and autoregressive (AR) (1) [31,32] correlation structures under nonnormal responses have been considered. e independent structure assumes a weak correlation among the subjects in a cluster, and the number of clusters is small.…”
Section: Methodsmentioning
confidence: 99%
“…Our data were clustered by counties; thus, an exchangeable correlation structure is the most flexible in modeling the association through the generalized estimation equations (GEE) approach. Notably, both independent [30] and autoregressive (AR) (1) [31,32] correlation structures under nonnormal responses have been considered. e independent structure assumes a weak correlation among the subjects in a cluster, and the number of clusters is small.…”
Section: Methodsmentioning
confidence: 99%
“…Ref. [16] analyzed logistic regression when some of the explanatory variables have skewed cell probabilities and lastly [17] considered the logistic model proposed by [1] to examine correlated infant morbidity data. More recently, Ref.…”
Section: Introductionmentioning
confidence: 99%
“…Pérez-Sánchez et al (2014) studied the risk variables underlying automobile insurance claims taking into account the asymmetry of the database. Alkhalaf and Zumbo (2017) studied logistic regression when some of the predictors have skewed cell probabilities and finally Mwenda et al (2021) uses the logistic model proposed by Prentice (1976) to study correlated infant morbidity data.…”
Section: Introductionmentioning
confidence: 99%