{"success":1,"msg":"","color":"rgb(28, 35, 49)","title":"Model-Based Estimates in Demography and Global Health: Quantifying the Contribution of Population-Period-Specific Information<\/b>","description":"webinar","title2":"","start":"2021-07-23 14:30","end":"2021-07-23 15:30","responsable":"Isabelle Beaudry <\/i><\/a>","speaker":"Leontine Alkema","id":"48","type":"webinar","timezone":"America\/Santiago","activity":"https:\/\/zoom.us\/j\/97174877298?pwd=dXFvaXVhc0wwK2l6QzAwTUFuVUtsZz09\r\nPasscode: 142023","abstract":"Sophisticated statistical models are used to produce estimates for demographic and health indicators even when data are limited, very uncertain or lacking. To facilitate interpretation and use of model-based estimates, we aim to provide a standardized approach to answer the question: To what extent is a model-based estimate of an indicator of interest informed by data for the relevant population-period as opposed to information supplied by other periods and populations and model assumptions? We propose a data weight measure to calculate the weight associated with population-period data set y relative to the model-based prior estimate obtained by fitting the model to all data excluding y. In addition, we propose a data-model accordance measure which quantifies how extreme the population-period data are relative to the prior model-based prediction."}