Methods for handling missing data in clinical psychology studies are reviewed. Missing data
are defined, and a taxonomy of main approaches to analysis is presented, including …

An up-to-date, comprehensive treatment of a classic text on missing data in statistics The
topic of missing data has gained considerable attention in recent decades. This new edition …

Background: The national annually reported proportion of men who have sex with men
(MSM) among people living with HIV (PLWH) is growing in China. To better inform the public …

Background: HIV prevalence estimates from population-based surveys are vulnerable to
selection bias if HIV status is missing for a proportion of the eligible population. Standard …

Estimates of HIV prevalence are important for policy to establish the health status of a
country's population and to evaluate the effectiveness of population-based interventions and …

A recent study using Heckman-type selection models to adjust for non-response in the
Zambia 2007 Demographic and Health Survey (DHS) found a large correction in HIV …

Missing data are a recurrent problem in all types of medical and epidemiological studies,
regardless of the rigour with which they are designed and executed. Although causes of …

Standard corrections for missing data rely on the strong and generally untestable
assumption of missing at random. Heckman-type selection models relax this assumption, but …

Objectives Population-based HIV testing surveys have become central to deriving estimates
of national HIV prevalence in sub-Saharan Africa. However, limited participation in these …

Background: Heckman-type selection models have been used to control HIV prevalence
estimates for selection bias when participation in HIV testing and HIV status are associated …