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{"index.qmd":[],"references.qmd":[],"4_rt.qmd":["lo2015transform","schramm2019reaction"],"2_predictors.qmd":[],"3_scales.qmd":[],"5_individual.qmd":[],"1_introduction.qmd":[]} | ||
{"3_scales.qmd":[],"5_individual.qmd":[],"references.qmd":[],"2_predictors.qmd":[],"4_rt.qmd":["wagenmakers2008diffusion","theriault2024check","lo2015transform","schramm2019reaction"],"index.qmd":[],"1_introduction.qmd":[]} |
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{"title":"Predictors","markdown":{"headingText":"Predictors","containsRefs":false,"markdown":"\n\n## Categorical predictors (Condition, Group, ...)\n\nNested interactions, contrasts, ...\n\n## Ordered predictors (Likert Scales)\n\nLikert scales, i.e., ordered multiple *discrete* choices are often used in surveys and questionnaires. While such data is often treated as a *continuous* variable, such assumption is not necessarily valid. Indeed, distance between the choices is not necessarily equal. For example, the difference between \"strongly agree\" and \"agree\" might not be the same as between \"agree\" and \"neutral\". 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