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Thread: How can I go deeper into ANOVA?

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    How can I go deeper into ANOVA?



    I am doing some research on office work and where people look at work.

    I have one independent variable with four different levels, that is I had the people work in four different light conditions in their offices.
    I have several dependent variables; each contains the information of how many times they looked at something in a light condition (e.g. one person looked 15 times at a painting on the wall when the light was brightest).

    I already ran an ANOVA and know that people significantly look more often at pictures when it's bright as opposed to when it's dark, but the number of times they looked at the floor is about the same for all four light conditions.

    So far, so good. Now that I have answered what effect the light has on where they look, I'd like to know if certain objects are more dominant/more often looked at than others. That is I'd like to know if they significantly looked more often at the painting than the floor. How do I extract this information?
    [SIZE="3"]"What can be said at all can be said clearly, and what we cannot talk about we must pass over in silence."[/SIZE]
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    Hi Parcival,

    There are different ways you could approach it, but here is one.

    Reformulate your dependent variable (DV) to be looking time, then make Object (the object they're looking at--floor, painting, etc) and Independent Variable. You could then test if they looked more at the painting than the floor in general, and if differences occur more in some lighting conditions (using an interaction term).

    This approach has a few issues however. The DV might be negatively correlated in the different conditions just because the more time you look at one object, the less time you look at the other. In fact, if you have only two objects, it wouldn't work, because if you know how much time someone looked at one, by definition you know how much time they looked at the other. But if you're comparing looking times for two objects out of say, 8, they're less likely to be correlated.

    The other thing is now it's a repeated measures study, so you need to treat it that way.

    Karen
    The Analysis Factor
    http://TheAnalysisFactor.com

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