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Thread: Continuous variables for correlations

  1. #1
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    Post Continuous variables for correlations


    I hope someone can help me with this question.

    If my variable is categorical (1=Sometimes, 2=Frequently ...) can I use it for in a correlational analysis? If not, can I recode my variable into a form such that it can be used?


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    Hi Justmira,

    You can calculate the Spearman's rank correlation coefficient. There are definitions and how-to's if you search on google.

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    You can just use the "regular" correlation coefficient (Pearson), but if your variable is a categorical one that represents an increasing/decreasing "quantity" or "frequency," then Spearman's rank-correlation coefficient will provide more meaningful results.

    Even when you do an ANOVA, which is usually just for categorical independent variables with continuous dependent variables, the software usually provides a calculation of r and r^2.

    There are many different correlation coefficients, depending on the variable types and the levels of measurement:

    point biserial -> dichotomous indep variable, continuous dependent variable
    phi -> both variables are dichotomies
    biserial -> same as point-biserial, but assumes an underlying "continuity" for the dichotomous variable
    tetrachoric -> same as phi, but with the assumption of an underlying "continuity"

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