Kompleksisen luokitellun aineiston riippuvuusrakenteen pelkistäminen : sovellus ylioppilaskirjoitusaineistoon
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Improving identification algorithms in causal inference
Tikka, Santtu (University of Jyväskylä, 2018)Causal models provide a formal approach to the study of causality. One of the most useful features of causal modeling is that it enables one to make causal claims about a phenomenon using observational data alone under ... -
Polynomial Regression and Measurement Error : Implications for Information Systems Research
Aguirre-Urreta, Miguel I.; Rönkkö, Mikko; Hu, Jiang (Association for Computing Machinery (ACM), 2020)Many of the phenomena of interest in information systems (IS) research are nonlinear, and it has consequently been recognized that by applying linear statistical models (e.g., linear regression), we may ignore important ... -
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