output
20162024
most citedOn the collapsibility of measures of effect in the counterfactual causal framework

48 citations

7 papers

stat.ME2024★ 3 cited

Recovery and inference of causal effects with sequential adjustment for confounding and attrition

Johan de Aguas, Johan Pensar, Tomás Varnet Pérez +1

Confounding bias and selection bias bring two significant challenges to the validity of conclusions drawn from applied causal inference. The latter can stem from informative missin…

q-bio.PE2023★ 9 cited

A standardised protocol for assessment of relative SARS-CoV-2 variant severity, with application to severity risk for COVID-19 cases infected with Omicron BA.1 compared to Delta variants in six European countries

Tommy Nyberg, Peter Bager, Ingrid Bech Svalgaard +17

Several SARS-CoV-2 variants that evolved during the COVID-19 pandemic have appeared to differ in severity, based on analyses of single-country datasets. With decreased SARS-CoV-2 t…

physics.soc-ph2022

Effects of Non-Compulsory and Mandatory COVID-19 Interventions on Travel Distance and Time Away from Home: The Case of Norway in 2021

Meghana Kamineni, Kenth Engø-Monsen, Jørgen Eriksson Midtbø +4

Background: Due to the societal, economic, and health costs of COVID-19 non-pharmaceutical interventions (NPIs), it is important to assess their effects. Human mobility serves as a…

stat.AP2019★ 9 cited

A Dyadic IRT Model

Brian Gin, Nicholas Sim, Anders Skrondal +1

We propose a dyadic Item Response Theory (dIRT) model for measuring interactions of pairs of individuals when the responses to items represent the actions (or behaviors, perception…

cs.SE2018★ 10 cited

Key Lessons from Tailoring Agile Methods for Large-Scale Software Development

Torgeir Dingsøyr, Tore Dybå, Mette Gjertsen +5

We describe advice derived from one of the largest development programs in Norway, where twelve Scrum teams combined agile practices with traditional project management. The Perfor…

stat.ME2016★ 21 cited

Effect heterogeneity and variable selection for standardizing causal effects to a target population

Anders Huitfeldt, Sonja A. Swanson, Mats Julius Stensrud +1

The participants in randomized trials and other studies used for causal inference are often not representative of the populations seen by clinical decision-makers. To account for d…

stat.ME2016★ 48 cited

On the collapsibility of measures of effect in the counterfactual causal framework

Anders Huitfeldt, Mats Julius Stensrud, Etsuji Suzuki

A measure of association is said to be collapsible over a set of baseline covariates if the marginal value of the measure of association is equal to a weighted average of the strat…