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Home Research Topics Eye Movement Corpus Analysis On the Ambiguity of Interaction and Nonlinear Main Effects in a Regime of Dependent Covariates

On the Ambiguity of Interaction and Nonlinear Main Effects in a Regime of Dependent Covariates

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Frequently the analysis of large experimental datasets reveals significant interactions that are difficult to interpret within the theoretical framework guiding the research. Some of these interactions are actually spurious artifacts arising from the presence of unspecified nonlinear main effects and statistically dependent covariates in the statistical model. Importantly, often such nonlinear main effects may be quite compatible (or, at least, may not be incompatible) with the current theoretical framework. In the present literature this issue has only been studied in terms of correlated (linearly dependent) covariates. Here we generalize to nonlinear main effects (i.e., main effects of arbitrary shape) and dependent covariates. We propose a novel nonparametric method to test for ambiguous or spurious interactions where present parametric methods fail. We illustrate the method with re-analyses of eye-movements, specifically of fixation durations and locations, during reading of natural sentences.

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Download this file (MatuschekKliegl2015.pdf)MatuschekKliegl2015.pdf[Manuscript preprint][ ]442 Kb09/12/2015 10:54
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Last Updated on Wednesday, 09 December 2015 10:54  

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