Volume 47 - Article 11 | Pages 291–344
A probabilistic model for analyzing summary birth history data
By Katherine Wilson, Jon Wakefield
References
Alkema, L. and New, J. (2014). Global estimation of child mortality using a Bayesian B-spline bias-reduction model. The Annals of Applied Statistics 8: 2122–2149.
Alkema, L., New, J.R., Pedersen, J., and You, D. (2014). Child mortality estimation 2013: an overview of updates in estimation methods by the United Nations Inter- Agency Group for Child Mortality Estimation. PLoS One 9: e101112.
Besag, J., York, J., and Mollié, A. (1991). Bayesian image restoration with two applications in spatial statistics. Annals of the Institute of Statistics and Mathematics 43: 1–59.
Brady, E. and Hill, K. (2017). Testing survey-based methods for rapid monitoring of child mortality, with implications for summary birth history data. PLoS One 12: e0176366.
Brass, W. (1975). Methods for Estimating Fertility and Mortality from Limited and Defective Data. North Carolina: Chapel Hill.
Brass, W. (1964). Uses of census or survey data for the estimation of vital rates. Paper presented at the African Seminar on Vital Statistics, Addis Ababa, 14–19 December, 1964.
Burstein, R., Wang, H., Reiner Jr, R.C., and Hay, S.I. (2018). Development and validation of a new method for indirect estimation of neonatal, infant, and child mortality trends using summary birth histories. PLoS Medicine 15: e1002687.
Coale, A.J. and Trussell, J. (1977). Annex I: estimating the time to which Brass estimates apply. Population Bulletin of the United Nations 10: 87–89.
Feeney, G. (1976). Estimating infant mortality rates from child survivorship data by age of mother. Asian and Pacific Census Newsletter 3: 12–16.
Golding, N., Burstein, R., Longbottom, J., Browne, A., Fullman, N., Osgood- Zimmerman, A., Earl, L., Bhatt, S., Cameron, E., Casey, D., Dwyer-Lindgren, L., Farag, T., Flaxman, A., Fraser, M., Gething, P., Gibson, H., Graetz, N., Krause, L., Kulikoff, X., Lim, S., Mappin, B., Morozoff, C., Reiner, R., Sligar, A., Smith, D., Wang, H., Weiss, D., Murray, C., Moyes, C., and Hay, S. (2017). Mapping under-5 and neon- tal mortality in Africa, 2000–15: a baseline analysis for the Sustainable Development Goals. The Lancet 390: 2171–2182.
Hill, K., Brady, E., Zimmerman, L., Montana, L., Silva, R., and Amouzou, A. (2015). Monitoring change in child mortality through household surveys. PLoS One 10: e0137713.
Hill, K. and Figueroa, M.E. (1999). Child mortality estimation by time since first birth. Hopkins Population Center.
Hill, K., You, D., Inoue, M., and Oestergaard, M.Z. (2012). Child mortality estimation: accelerated progress in reducing global child mortality, 1990–2010. PLoS Medicine 9: e1001303.
Hill, K., Zlotnik, H., and Trussell, J. (1983). Demographic Estimation: A Manual on Indirect Techniques. Manual X.
Kristensen, K. (2014). TMB: General random effect model builder tool inspired by ADMB. Rpackage version.
Kristensen, K., Nielsen, A., Berg, C. W., Skaug, H., and Bell, B. M. (2016). TMB: Automatic Differentiation and Laplace approximation. Journal of Statistical Software 70: 1–21.
Li, Z.R., Hsiao, Y., Godwin, J., Martin, B.D., Wakefield, J., and Clark, S.J. (2019). Changes in the spatial distribution of the under five mortality rate: small-area analysis of 122 DHS surveys in 262 subregions of 35 countries in Africa. PLoS One 14: e0210645.
Malawi, D. H. S. (2016). Malawi Demographic Health Survey 2016–16. Zomba, Malawi: NSO/Malawi and ICF Macro.
National Statistical Office – NSO/Malawi and ICF Macro (2011). Malawi Demographic and Health Survey 2010. Zomba, Malawi: National Statistical Office – NSO/Malawi and ICF Macro .
Pedersen, J. and Liu, J. (2012). Child mortality estimation: Appropriate time periods for child mortality estimates from full birth histories. PLoS Medicine 9: e1001289.
Preston, S.H., Heuveline, P., and Guillot, M. (2000). Demography: Measuring and Modeling Population Processes. Malden, MA: Blackwell.
Rajaratnam, J.K., Tran, L.N., Lopez, A.D., and Murray, C.J. (2010). Measuring under- five mortality: validation of new low-cost methods. PLoS Medicine 7: e1000253.
Riebler, A., Sørbye, S., Simpson, D., and Rue, H. (2016). An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Statistical Methods in Medical Research 25: 1145–1165.
Rue, H. and Held, L. (2005). Gaussian Markov Random Fields: Theory and Application. Boca Raton: Chapman and Hall/CRC Press.
Simpson, D., Rue, H., Riebler, A., Martins, T., and Sørbye, S. (2017). Penalising model component complexity: A principled, practical approach to constructing priors (with discussion. Statistical Science 32: 1–28.
Sullivan, J.M. (1972). Models for the estimation of the probability of dying between birth and exact ages of early childhood. Population Studies 26: 79–97.
Trussell, T.J. (1975). A re-estimation of the multiplying factors for the Brass technique for determining childhood survivorship rates. Population Studies 29: 97–107.
Verhulst, A. (2016). Child mortality estimation: An assessment of summary birth history methods using microsimulation. Demographic Research 34(39): 1075–1128.
Wakefield, J., Fuglstad, G.A., Riebler, A., Godwin, J., Wilson, K., and Clark, S. (2019). Estimating under five mortality in space and time in a developing world context. Statistical Methods in Medical Research 28: 2614–2634.
Wakefield, J.C. (2004). Ecological inference for 2 × 2 tables (with discussion. Journal of the Royal Statistical Society, Series A 167: 385–445.
Walker, N., Hill, K., and Zhao, F. (2012). Child mortality estimation: methods used to adjust for bias due to AIDS in estimating trends in under-five mortality. PLoS Med 9: e1001298.
Wilson, K. and Wakefield, J. (2020). Child mortality estimation incorporating summary birth history data. Biometrics Published online.