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.
We illustrate the insights obtained from the combination of both measures in toy examples and present preliminary findings for estimates of family planning indicators. This is joint work with Guandong (Elliot) Yang and Krista Gile.