Causal inference and case-control studies with applications related to childhood diabetes
2014 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Kausal inferens och fall-kontroll studier med applikationer inom barndiabetes (Swedish)
This thesis contributes to the research area of causal inference, where estimation of the effect of a treatment on an outcome of interest is the main objective. Some aspects of the estimation of average causal effects in observational studies in general, and case-control studies in particular, are explored.
An important part of estimating causal effects in an observational study is to control for covariates. The first paper of this thesis concerns the selection of minimal covariate sets sufficient for unconfoundedness of the treatment assignment. A data-driven implementation of two covariate selection algorithms is proposed and evaluated.
A common sampling scheme in epidemiology, and when investigating rare events, is the case-control design. In the second paper we study estimators of the marginal causal odds ratio in matched and independent case-control designs. Estimators that, under a logistic regression model, utilize information about the known prevalence of being a case is examined and compared through simulations.
The third paper investigates the particular situation where case-control sampled data is reused to estimate the effect of the case-defining event on an outcome of interest. The consequence of ignoring the design when estimating the average causal effect is discussed and a design-weighted matching estimator is proposed. The performance of the estimator is evaluated with simulation experiments, when matching on the covariates directly and when matching on the propensity score.
The last paper studies the effect of type 1 diabetes mellitus (T1DM) on school achievements using data from the Swedish Childhood Diabetes Register, a population-based incidence register. We apply theoretical results from the second and third papers in the estimation of the average causal effect within the T1DM population. A matching estimator that accounts for the matched case-control design is used.
Place, publisher, year, edition, pages
Umeå: Umeå universitet , 2014. , 22 p.
Statistical studies, ISSN 1100-8989 ; 48
covariate selection, design-weighted estimation, marginal effect, matching, register study, treatment effect, type 1 diabetes mellitus
Probability Theory and Statistics
Research subject Statistics
IdentifiersURN: urn:nbn:se:umu:diva-94993ISBN: 978-91-7601-151-5OAI: oai:DiVA.org:umu-94993DiVA: diva2:757008
2014-11-21, Hörsal F, Humanisthuset, Umeå universitet, Umeå, 10:15 (English)
Vansteelandt, Stijn, Professor
Waernbaum, Ingeborg, Docentde Luna, Xavier, ProfessorDahlquist, Gisela, Professor
List of papers