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Intro to Statistics with R: Repeated measures ANOVA

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4 horas9 vídeos41 ejercicios27.030 aprendicesTrophyDeclaración de cumplimiento

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Descripción del curso

This course focuses on within-groups comparisons and repeated measures design. With the help of a working memory training experiment, one of Professor Conway’s main areas of research, it will be explained what the pros and cons are of a repeated measures design and how to conduct the calculations in R yourself.
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  1. 1

    Introduction to repeated measures ANOVA

    Gratuito

    In this chapter, Professor Conway will review the pros and cons of a repeated measures design. There are many benefits to conducting experiments in this way, but there are also some issues that you need to take into consideration. For example, the lower cost and increased statistical power of a repeated measures design are great, but you need to take into account things like order effects, counterbalancing and missing data. This chapter will show you how!

    Reproducir Capítulo Ahora
    Introduction to repeated measures ANOVA
    50 xp
    Analogy between t-tests and ANOVA
    50 xp
    Between-groups vs. within-subjects designs
    50 xp
    A tale of two experiments
    50 xp
    Always one or the other?
    50 xp
    Explore the working memory data
    100 xp
    Pros of repeated measures ANOVA
    50 xp
    Reduced cost
    50 xp
    Statistically more powerful
    50 xp
    Cons of repeated measures ANOVA
    50 xp
    Counterbalancing
    50 xp
    Number of order conditions?
    50 xp
    Latin Squares design
    50 xp
    More on Latin Squares
    50 xp
    Handling missing data
    50 xp
    Why is missing data a problem?
    50 xp
    Sphericity assumption
    50 xp
    Understanding sphericity
    50 xp
    Mauchly's test
    100 xp
    Interpreting Mauchly's test results
    50 xp
    Summary
    50 xp
    Pros of repeated measures?
    50 xp
    Cons of repeated measures?
    50 xp
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