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Weighted Effect Coding for Observational Data with wec
Stockholm University, Faculty of Social Sciences, The Swedish Institute for Social Research (SOFI).
Number of Authors: 3
2017 (English)In: The R Journal, ISSN 2073-4859, E-ISSN 2073-4859, Vol. 9, no 1, 477-485 p.Article in journal (Refereed) Published
Abstract [en]

Weighted effect coding refers to a specific coding matrix to include factor variables in generalised linear regression models. With weighted effect coding, the effect for each category represents the deviation of that category from the weighted mean (which corresponds to the sample mean). This technique has particularly attractive properties when analysing observational data, that commonly are unbalanced. The wec package is introduced, that provides functions to apply weighted effect coding to factor variables, and to interactions between (a.) a factor variable and a continuous variable and between (b.) two factor variables.

Place, publisher, year, edition, pages
2017. Vol. 9, no 1, 477-485 p.
National Category
Computer and Information Science Mathematics
Identifiers
URN: urn:nbn:se:su:diva-145229ISI: 000404756200033OAI: oai:DiVA.org:su-145229DiVA: diva2:1128763
Available from: 2017-07-28 Created: 2017-07-28 Last updated: 2017-07-28Bibliographically approved

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