Longitudinal life course perspectives on housing inequality in young adulthood

The simplest approach to dealing with missing data is to restrict the analysis to complete cases, i.e. individuals with no missing values. This can induce bias, however. Inverse probability weighting (IPW) is a commonly used method to correct this bias. It is also used to adjust for unequal sampling fractions in sample surveys. This article is a review of the use of IPW in epidemiological research. We describe how the bias in the complete-case analysis arises and how IPW can remove it. IPW is compared with multiple imputation (MI) and we explain why, despite MI generally being more efficient, IPW may sometimes be preferred. We discuss the choice of missingness model and methods such as weight truncation, weight stabilisation and augmented IPW. The use of IPW is illustrated on data from the 1958 British Birth Cohort.

The pioneering longitudinal studies of child development (all launched in the 1920s and 1930s) were extended well beyond childhood. Indeed, they eventually followed their young study members up to the middle years and later life. In doing so, they generated issues that could not be addressed satisfactorily by available theories. These include the recognition that individual lives are influenced by their ever-changing historical context, that the study of human lives calls for new ways of thinking about their pattern and dynamic, and that concepts of human development should apply to processes across the life span. Life course theory has evolved since the 1960s through programmatic efforts to address such issues.

While researchers are increasingly re-conceptualizing international migration, far less attention has been devoted to re-thinking short-distance residential mobility and immobility. In this paper we harness the life course approach to propose a new conceptual framework for residential mobility research. We contend that residential mobility and immobility should be re-conceptualized as relational practices that link lives through time and space while connecting people to structural conditions. Re-thinking and re-assessing residential mobility by exploiting new developments in longitudinal analysis will allow geographers to understand, critique and address pressing societal challenges.