Kursplansdatabas för forskarutbildningskurser
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Kursplansdatabas för forskarutbildningskurser
KURSPLANER FÖR FORSKARUTBILDNINGSKURSER
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| Svensk benämning | Kausal inferens från observationsdata |
|---|---|
| Engelsk benämning | Causal Inference from observational data |
| Kursnummer | 2462 |
| Antal högskolepoäng | 1.5 |
| Kursansvarig institution | Institutet för miljömedicin |
| Särskild behörighet | Epidemiology I (course 1577) and Biostatistics I (course 1579) or corresponding courses. |
| Betygsskala | Godkänd/Icke godkänd |
| Fastställd av | The Board of Doctoral Education |
| Datum för fastställande | 2015-03-30 |
| Kursens syfte | |
| Kursens lärandemål | At the end of the course the student should be able to: - Recognize and formulate well defined questions concerning causal effects - Identify the key assumptions for causal inference from observational data - Conduct simple analyses to estimate causal effects under those assumptions - Use causal diagrams to represent a priori subject-matter knowledge, assumptions, and epidemiologic biases - Describe the role of subject-matter knowledge in observational research |
| Kursens innehåll | Causal inference from observational data is a key task of epidemiology and of allied sciences such as sociology, education, behavioral sciences, demography, economics, health services research, etc. These disciplines share a methodological framework for causal inference that has been developed over the last decades. This course presents this unifying causal theory and shows how epidemiologic concepts and methods can be understood within this general framework. The course emphasizes graphs and conceptualization in simple settings but also introduces statistical methods for time-varying exposures. Specifically, this course strives to a) formally define causal concepts such as causal effect and confounding, b) identify the conditions required to estimate causal effects, and c) use analytical methods that, under those conditions, provide estimates that can be endowed with a causal interpretation. These (causal) methods can be used under less restrictive conditions than traditional statistical methods. For example, causal methods allow one to estimate the causal effect of a time-varying exposure in the presence of time-dependent confounders that lie on the causal pathway between exposure and outcome. |
| Arbetsformer | Lectures and group sessions. The course is offered as full-time course over three days within the Swedish Interdisciplinary Graduate School for register-based research. |
| Obligatoriska moment | Individual examination |
| Examination | Individual written home examination where the students will conduct simple analyses to estimate causal effects in observational data. |
| Kurslitteratur och övriga läromedel | Recommended literature: Causal Inference, by Miguel Hernan and James Robins. The book can be downloaded (for free) from http://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ |
Kursansvarig |
Anita Berglund Institutet för miljömedicin Anita.Berglund@ki.se |
| Kontaktpersoner |
Ida Kettley Cronfalk Institutet för miljömedicin ida.kettley.cronfalk@ki.se |
