Special Collection 1 - Article 4 | Pages 109–142  

How do we know we need to control for selectivity?

By Susan Watkins, Ina Warriner

This article is part of the Special Collection 1 "Social Interactions and HIV/AIDS in Rural Africa"


In the previous two decades there has been considerable progress in recognizing biases due to selectivity that are associated with the use of observational data to make causal inferences and in developing models to control for these biases statistically. Often there is a difference between estimates produced by models that attempt to control for selectivity and those that do not. Since a difference alone does not persuasively argue for one model over another, analysts typically rely on their a priori expectations of selectivity based on theory or intuition.
Here we suggest that the analyst’s judgement about the appropriate analytical model may be informed by simple descriptive statistics and qualitative data. We use data on social networks collected in rural Kenya, since the analysis of networks is likely to raise questions of selectivity, and simple examples.
Although we do not provide general rules for assessing when models that control for selectivity should be used, we conclude by recommending that analysts inform their judgement rather than rely on theory and intuition to justify controlling for selectivity. Although our data are particular, the implications of our approach are general, since a priori evaluations of the credibility of assumptions on which analytic models are based can be made in other settings and for other research questions.

Author's Affiliation

Other articles by the same author/authors in Demographic Research

Asking God about the date you will die: HIV testing as a zone of uncertainty in rural Malawi
Volume 23 - Article 32

The Malawi Diffusion and Ideational Change Project 2004-06: Data collection, data quality, and analysis of attrition
Volume 20 - Article 21

A summary of Special Collection 1: Social Interactions and HIV/AIDS in Rural Africa
Volume 9 - Article 12

Attrition in Longitudinal Household Survey Data: Some Tests for Three Developing-Country Samples
Volume 5 - Article 4

Empirical Assessments of Social Networks, Fertility and Family Planning Programs: Nonlinearities and their Implications
Volume 3 - Article 7

"Moving" and Marrying: Modelling HIV Infection among Newly-weds in Malawi
Special Collection 1 - Article 7

Introduction to "Research on Demographic Aspects of HIV/AIDS in Rural Africa"
Special Collection 1 - Article 1

Most recent similar articles in Demographic Research

Calculating contraceptive prevalence and unmet need for family planning in low-fertility countries with the Generations and Gender Survey
Volume 49 - Article 21    | Keywords: cross-national study, Demographic and Health Surveys (DHS), Europe, family planning, Fertility and Family Survey (FFS), Generations and Gender Survey (GGS), longitudinal data, panel data, unplanned births, World Fertility Survey

Parental status homogeneity in social networks: The role of homophilous tie selection in Germany
Volume 48 - Article 2    | Keywords: fertility, homophily, network selection, social contagion, social interaction, social networks

“One hand does not bring up a child:” Child fostering among single mothers in Nairobi slums
Volume 46 - Article 30    | Keywords: child fostering, informal settlements, Kenya, kinship, single motherhood, sub-Saharan Africa

To what extent were life expectancy gains in South Africa attributable to declines in HIV/AIDS mortality from 2006 to 2017? A life table analysis of age-specific mortality
Volume 46 - Article 18    | Keywords: antiretroviral therapy, HIV/AIDS, life expectancy, South Africa

Accuracy of wives' proxy reports of husbands' fertility preferences in sub-Saharan Africa
Volume 46 - Article 17    | Keywords: couples, Demographic and Health Surveys (DHS), family planning, fertility, fertility desires, spousal relationships, sub-Saharan Africa