Author Archives: Maarten J. Bijlsma
Commitment in ‘living-apart-together’ (LAT) relationships: less is more?
Roselinde van der Wiel writes about commitment in ‘living-apart-together’ (LAT) relationships and the factors underlying this commitment. In the past decades, new relationship types have arisen that suggest that commitment is of less importance in modern, individualized societies. ‘Living apart together’ (LAT) is one such relationship type. LAT refers to longer-term, monogamous partners who consider […]
Inferring population-level effects from individual-level effect estimates: G-computation
The fields of epidemiology and demography are closely aligned. Even demographers interested in fertility or migration, not just mortality, can learn a great deal from epidemiology. As a recent study has argued, epidemiology is currently undergoing a methodological revolution, and this is likely to affect demography as well. The epidemiological revolution is, in fact, a […]
A hot topic and a futile quest? The recent discussion on age-period-cohort analysis
Last year, Yang & Land released their book on age-period-cohort (APC) analysis. A large section of the December issue of Demography is dedicated to age-period-cohort analysis. And just a week or two ago a paper by Bell & Jones on the Yang & Land APC model was published in Demographic Research. APC analysis appears to […]
The bias-variance tradeoff: what it means for quantitative researchers
Most researchers are familiar with the difference between bias and precision. However, not everyone knows that we can allow for a little bit of bias in order to get big gains in precision, and when it can be beneficial to do so. In this post I detail the why and how. A refresher on bias […]
Homage to the Lexis diagram
The Lexis diagram belongs in the demographer’s toolbox like a mechanic’s wrench. It is the essential tool for visualizing lifelines and events as they occur along the intersection of age, (time) period and (birth) cohort. This means it is of great use to scientists doing longitudinal, time-to-event and even time series analyses. As such, it […]
Demography and epidemiology: past and future directions
Epidemiology and demography are often so close that it can be difficult to distinguish one from the other. Is it necessary to train health demographers when epidemiologists could just as well do the job? Could researchers from either field learn something from each other? As my first post for Demotrends, I thought I’d share some […]
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