Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
On the Existence of Suitable Models for Additive Interaction with Continuous Exposures
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.ORCID iD: 0000-0002-2990-1959
University of Milano-Bicocca.ORCID iD: 0000-0001-9642-0242
Department of Medicine, Karolinska Institutet.ORCID iD: 0000-0003-3380-5342
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.ORCID iD: 0000-0003-1489-8512
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Additive interaction can be of importance for public health interventions and it is commonly defined using binary exposures. There has been expansions of the models to also include continuous exposures, which could lead to better and more precise estimations of the effect of interventions. In this paper we define the intervention for a continuous exposure as a monotonic function. Based on this function for the interventions we prove that there is no model for estimating additive interactions with continuous exposures for which it holds that; (i) both exposures have marginal effects and no additive interaction on the exposure level for both exposures, (ii) neither exposure has marginal effect and there is additive interaction between the exposures. We also show that a logistic regression model for continuous exposures will always produce additive interaction if both exposures have marginal effects.

Keywords [en]
Additive Interaction, Multiplicative Interaction, Logistic Regression, Linear Odds, Continuous Exposures, Public Health, Interventions
National Category
Probability Theory and Statistics Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Applied and Computational Mathematics, Mathematical Statistics
Identifiers
URN: urn:nbn:se:kth:diva-259549OAI: oai:DiVA.org:kth-259549DiVA, id: diva2:1352474
Note

QC 20190925

Available from: 2019-09-18 Created: 2019-09-18 Last updated: 2019-09-25Bibliographically approved
In thesis
1. Models for Additive and Sufficient Cause Interaction
Open this publication in new window or tab >>Models for Additive and Sufficient Cause Interaction
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of this thesis is to develop and explore models in, and related to, the sufficient cause framework, and additive interaction. Additive interaction is closely connected with public health interventions and can be used to make inferences about the sufficient causes in order to find the mechanisms behind an outcome, for instance a disease.

In paper A we extend the additive interaction, and interventions, to include continuous exposures. We show that there does not exist a model that does not lead to inconsistent conclusions about the interaction.

The sufficient cause framework can also be expressed using Boolean functions, which is expanded upon in paper B. In this paper we define a new model based on the multifactor potential outcome model (MFPO) and independence of causal influence models (ICI).

In paper C we discuss the modeling and estimation of additive interaction in relation to if the exposures are harmful or protective conditioned on some other exposure. If there is uncertainty about the effects direction there can be errors in the testing of the interaction effect.

Abstract [sv]

Målet med denna avhandling är att utveckla, och utforska modeller i det så kallade sufficent cause ramverket, och additiv interaktion. Additiv interaktion är nära kopplat till interventioner inom epidemiology och sociologi, men kan också användas för statistiska tester för sufficient causes för att förstå mekanimser bakom ett utfall, tex en sjukdom.

I artikel A så expanderar vi modellen för additiv interaktion och interventioner till att också inkludera kontinuerliga variabler. Vi visar att det inte finns någon modell som inte leder till motsägelser i slutsatsen om interaktionen.

Sufficient cause ramverket kan också utryckas via Boolska funktioner, vilket byggs vidare på i artikel B. I den artikeln definerar vi en modell baserad på mutltifactor potential outcome modellen (MFPO) och independence of causal influence modellen (ICI).

I artikel C diskuterar vi modelleringen och estimering av additiv interaktion i relation till om variablerna har skadlig eller skyddande effekt betingat på någon annan variabel. Om det finns osäkerhet kring en effekts riktning så kan det leda till fel i testerna för den additiva interaktionen.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2019. p. 134
Series
TRITA-SCI-FOU ; 2019;43
Keywords
Causal Inference, Sufficient Cause, Potential Outcomes, Counterfactual, Additive Interaction, Interaction, MFPO, ICI, Logistic Regression, Linear Odds, Public Health, Interventions, Probabilistic Potential Outcome
National Category
Probability Theory and Statistics
Research subject
Applied and Computational Mathematics, Mathematical Statistics
Identifiers
urn:nbn:se:kth:diva-259608 (URN)978-91-7873-308-8 (ISBN)
Presentation
2019-10-10, F11, Lindstedtsvägen 22, KTH Stockholm, 10:00 (English)
Opponent
Supervisors
Note

Examinator: Professor Henrik Hult, Matematik, KTH

Available from: 2019-09-19 Created: 2019-09-18 Last updated: 2019-09-19Bibliographically approved

Open Access in DiVA

AdditiveInteractionContinuous(278 kB)6 downloads
File information
File name FULLTEXT01.pdfFile size 278 kBChecksum SHA-512
e7fac6064f81a20892e2485e53a4a671c4d5396d789cd0cc53bf838598c1ae714a336b38a0143d42bee5d23e85ddb2d61c19d694087e8e1976b44944569c5e71
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Berglund, DanielCarlucci, ClaudiaWesterlind, HelgaKoski, Timo
By organisation
Mathematical Statistics
Probability Theory and StatisticsPublic Health, Global Health, Social Medicine and Epidemiology

Search outside of DiVA

GoogleGoogle Scholar
Total: 6 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 15 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf