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Thread: Regression coefficient for interaction

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    Regression coefficient for interaction




    Hi!

    I have a homework question that on the face looks rather simple to me, but I want to check with people who may have greater statistics knowledge than I!

    With this regression:

    var1 = β0 + β1var2 + β2var3 + β3(var2 var3)

    How many regression coefficients are used to represent var2 and how many are used to represent the interaction?

    As far as I can tell, I would say one for both...or is there something about the interaction being representative of the individual variables in a regression?

    Any help would be much appreciated!

    Thanks,

    smashing

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    Re: Regression coefficient for interaction

    As long as neither are categorical with greater than 2 groups, I would agree.
    Stop cowardice, ban guns!

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    Re: Regression coefficient for interaction


    Thanks!

    How does it change if some of the variables are indeed categorical with more than two groups?

    Binary-categorical interaction: consider the following linear regression model: (Notice that
    for simplicity, the variable with bold fonts represents a vector which can contain more than one
    predictor.)
    BMI = β0 + β1physact + β2nonwhite + β3(physact nonwhite)


    Binary-continuous interaction: consider the following linear regression model:
    BMI = β0 + β1SBP + β2diabetes + β3(SBP diabetes)

    Categorical-continuous interaction: consider the following linear regression model: (Notice
    that for simplicity, the variable with bold fonts represents a vector which can contain more than
    one predictor.)
    BMI = β0 + β1globrat + β2SBP + β3(globrat SBP)

    Continuous-continuous interaction: consider the following linear regression model:
    BMI = β0 + β1glucose + β2SBP + β3(glucose SBP)

    I'm being asked how many coefficient terms represent the interaction, as well as globrat and physat.

    Any help would be much appreciated!

    Thanks,

    smashing

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