Statistical Modelling for Evidence-Based Public Health

Foreword.- Chapter 1 Advancing evidence-based decision-making in public health: The critical role of practical biostatistical methods for health monitoring in sub-Saharan Africa.- Part I Bivariate (or Joint) Modelling of Public Health Data.- Chapter 2 A trivariate copula model with endogenous predictor variable to estimate determinants of zero-dose and under-immunized children in Angola and Ethiopia using survey data.- Chapter 3 Determinants of female schooling and fertility in Malawi: An application of bivariate Poisson regression model.- Chapter 4 A copula approach to sample selection modeling of treatment adherence and viral load among HIV patients on antiretroviral therapy.- Chapter 5 Joint Modelling of Water, Sanitation, and Hygiene (WASH) Using a Generalized Joint Regression Model in Namibia.- Part II Hierarchical and Multilevel Modelling of Health Data.- Chapter 6 Hierarchical outlier linkages between cluster and subject levels in a multivariate logistic regression model for child mortality data from a complex survey in Malawi.- Chapter 7 Application of mixed effects models to predict viral suppression and CD4 cell counts in a cohort of ART patients in Namibia.- Chapter 8 Transition autoregressive mixed models applied to analysis of viral load and CD4 cell count data for ART patients in Nambia.- Chapter 9 Modeling viral load using mixed effects regression models and generalized estimating equations.- Part III Time-To- Event Modelling of HIV and AIDS, Child and Maternal Health Data.- Chapter 10 Semiparametric and parametric mixed-effects survival regression methods applied to the analysis of women’s birth interval data in Malawi.- Chapter 11 Competing risks of defaulting and transferring out in the ART cohort of HIV and TB co-infected individuals in Namibia.- Part IV Model Fitting, Causal Inference, and Machine Learning Techniques for Public Health Data.- Chapter 12 Properties of model errors in logistic regression and their application to detect outliers in child mortality study.- Chapter 13 Methods Using Propensity Scores to Estimate Causal Effects in Observational Longitudinal Studies.- Chapter 14 Robust, quantile, and mean regression diagnostics for a comprehensive analysis of outlier haemoglobin levels in women using cross-sectional survey data in Malawi.- Chapter 15 A Machine Learning Approach to Identifying Shared Determinants of the Childhood Stunting in Kenya, Tanzania, Zambia and Malawi.- Chapter 16 Modelling progression of HIV disease using homogenous semi-Markov processes with an application to a cohort in Namibia.- Chapter 17 Modeling viral load with response missingness and covariate measurement error.- Chapter 18 Application of multivariable binary logistic regression model, nomogram and classification tree to predict baseline acute respiratory distress in severe malaria African children.- Part V Advanced Spatial and Bayesian Statistical Methods for Public Health Data Modelling.- Chapter 19 Incorporating Heavy-Tailed Spatial Random Effects in the Analysis of Areal Disease Data.- Chapter 20 Mapping HIV epidemic in Namibia using Bayesian spatial modelling.- Chapter 21 Mixed-effects logistic regression grouped outlier residuals and GeoSpatial logistic model applied to analysis of outlier communities to late treatment-seeking behaviour for childhood malaria in Malawi.- Chapter 22 Mapping gender-specific spatial disparities in HIV testing and condom use in Namibia.- Index.

• Erscheinungsdatum: 26.09.2025
• Autor/Autorin: Lawrence N. Kazembe
• Reihe: Mathematics and Statistics (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 28.6 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 551 Seiten
• ISBN: 9783031972812
• Lieferung: Sofort per Download
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