This book presents advanced statistical techniques used to analyze demographic data, which it illustrates through modelling maternal and child health in the African context using data from Demographic and Health Surveys in several countries in the continent.

This book presents both theoretical contributions and empirical applications of advanced statistical techniques including geo-additive models that link individual measures with area variables to account for spatial correlation; multilevel models that address the issue of clustering within family and household; multi-process models that account for interdependencies over life-course events and non-random utilization of health services; and flexible parametric alternatives to existing intensity models. These analytical techniques are illustrated mainly through modeling maternal and child health in the African context, using data from demographic and health surveys. In the past, the estimation of levels, trends and differentials in demographic and health outcomes in developing countries was heavily reliant on indirect methods that were devised to suit limited or deficient data. In recent decades, world-wide surveys like the World Fertility Survey and its successor, the Demographic and Health Survey have played an important role in filling the gap in survey data from developing countries. Such modern demographic and health surveys enable investigators to make in-depth analyses that guide policy intervention strategies, and such analyses require the modern and advanced statistical techniques covered in this book. The text is ideally suited for academics, professionals, and decision makers in the social and health sciences, as well as others with an interest in statistical modelling, demographic and health surveys. Scientists and students in applied statistics, epidemiology, medicine, social and behavioural sciences will find it of value.

Examines household surveys data from Africa using novel techniques State of the art techniques and their application to real world data Empirical results and their implications for evidence-based policy interventions Includes supplementary material: sn.pub/extras

Inhalt

1: Advanced Techniques for Modelling Maternal and Child Health in Africa: Samuel OM Manda, Ngianga-Bakwin Kandala and Gebrenegus Ghilagaber.- PART I: CHILD HEALTH AND SURVIVAL: 2: Disentangling Selection and Causality in Assessing the Effects of Health Inputs on Child Survival. Case Studies from Egypt, Eritrea, and Uganda: Gebrenegus Ghilagaber.- 3: Modelling Spatial Effects on Childhood Mortality via Geo-Additive Bayesian Discrete-time Survival Model: A Case Study from Nigeria: G Ghilagaber, D Antai and N-B Kandala.- 4: Bayesian Geo-additive Mixed Latent Variable Models with Applications on the Child's Health problems in some African Countries: K Khatab.- 5: Mapping socio-economic inequalities in health status in Malawian children: a Bayesian approach: L Kazembe.- 6: Analysis of Grouped Survival Data: **A Synthesis of Various Traditions and Application to Modeling Childhood Mortality in Eritrea: G Ghilagaber.- 7: Modelling Immunisation Coverage in Nigeria using Bayesian Structured Additive Regression: SB Adebayo and WB Yahya.- 8: Macro Determinants of Geographical Variation in Childhood Survival in South Africa using Flexible Spatial Mixture Models: S Manda.- 9: Socio-demographic determinants of Anaemia in children in Uganda : A multilevel analysis: SN Kandala.- PART II: MATERNAL HEALTH: 10: A Family of Flexible Parametric Duration Functions with Applications to Modelling Transition to Parenthood in Eritrea, Ghana, and Kenya: G Ghilagaber, W Elisa, and S O Gyimah.- 11: Spatial variation of predictors of prevalent hypertension in Sub-Saharan Africa: A case study of South-Africa: N-B Kandala.- 12: A Semiparametric Stratified Survival Model for Timing of First Birth in South Africa: S Manda, R Meyer and B Cai.-** 13: Stepwise Geoadditive Regression modelling of levels and trends of fertility in Nigeria: Guiding tools towards attaining MDGs: SB Adebayo and E Gayawan.- 14: A Spatial Analysis of Age at Sexual Initiation among Nigerian Youth as aTool for HIV Prevention: A Bayesian Approach: AA Abiodun et al.- 15: Assessing Geographic Co-morbidity Associated with Vascular Diseases in South Africa: A joint Bayesian Modeling Approach: NB Kandala, SOM Manda, W Tigbe.- 16: Advances in Modelling Maternal and Child Health in Africa: What Have We Learned and What is Next?: Gebrenegus Ghilagaber.