title: Log-Logistic Proportional Odds Model for Analyzing Infant Mortality in Bangladesh.
abstract: Log-logistic parametric survival regression model has been used to find out the potential determinants of infant mortality in Bangladesh using the data extracted from Bangladesh Demographic and Health Survey, 2011. First, nonparametric product-limit approach has been used to examine the unadjusted association between infant mortality and covariate of interest. It is found that maternal education, membership of nongovernmental organizations, age of mother at birth, sex of child, size of child at birth, and place of delivery play an important role in reducing the infant mortality, adjusting relevant covariates.
authors.affiliation: 1 University of Dhaka, Dhaka, Bangladesh.
authors.forename: Most
authors.initials: M
authors.lastname: Fatima-Tuz-Zahura
authors.affiliation: 1 University of Dhaka, Dhaka, Bangladesh.
authors.forename: Khandoker Akib
authors.initials: KA
authors.lastname: Mohammad
authors.affiliation: 1 University of Dhaka, Dhaka, Bangladesh.
authors.forename: Wasimul
authors.initials: W
authors.lastname: Bari
mesh_terms: D001459:Bangladesh / Q000453:epidemiology; D005260:Female; D006306:Health Surveys; D006801:Humans; D007223:Infant; D007226:Infant Mortality / Q000639:trends*; D016015:Logistic Models; D008297:Male; D012307:Risk Factors
keywords: Infant mortality; log-logistic survival regression model; product-limit approach; proportional odds model; random censored data