Analyzing infant mortality with geoadditive categorical regression models: a case study for Nigeria.
In this paper, we analyze infant mortality in Nigeria based on the data set from the 1999 Nigeria Demographic and Health Survey (NDHS). We investigate spatial patterns at a highly disaggregated level of Nigerian states and consider non-linear effects of mother's age at birth. Time to the occurrence of a child's death can intuitively be considered to be categorical in nature and the determinants of a child's death may differ in different age groups. Thus, it may be desirable to investigate separately the death of a child in the first month and in the remaining 11 months of the first year of life. To avoid selection bias, the data set used for this case study is based on information on children who were born 12 months preceding the survey. Inference is Bayesian and is based on Markov chain Monte Carlo (MCMC) techniques. We find that spatial variation and the determinants of death indeed differ considerably for the two age groups considered.
Department of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany.
Samson B
SB
Adebayo
Ludwig
L
Fahrmeir
Stephan
S
Klasen
D000293:Adolescent; D000328:Adult; D005260:Female; D006801:Humans; D007226:Infant Mortality / Q000639:trends*; D007231:Infant, Newborn; D008297:Male; D008390:Markov Chains; D008423:Maternal Age; D008875:Middle Aged; D009010:Monte Carlo Method; D009549:Nigeria / Q000453:epidemiology; D012044:Regression Analysis; D012307:Risk Factors