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SPSS STATS ANALYSIS ** PLEASE HELP :(

  • 21-04-2016 3:16pm
    #1
    ron_1
    Registered Users, Registered Users 2 Posts: 9 ✭


    Basically working with some Data for a project and totally unsure of what tests to run on SPSS or how to present results.

    I have intervention group control group. I was to compare two PRE/POST variables with 4 interrelated PRE/post variables?

    Any ideas? If i haven't explained this enough feel free to ask thank you :)


Comments

  • #2
    tritium
    Registered Users, Registered Users 2 Posts: 7,666 ✭✭✭tritium


    ron_1 wrote: »
    Basically working with some Data for a project and totally unsure of what tests to run on SPSS or how to present results.

    I have intervention group control group. I was to compare two PRE/POST variables with 4 interrelated PRE/post variables?

    Any ideas? If i haven't explained this enough feel free to ask thank you :)

    Is the question that you want to assess two possible sets of factors to see which are better for separating the two groups?


  • #3
    ron_1
    Registered Users, Registered Users 2 Posts: 9 ✭ron_1


    so two groups, intervention and control.

    two factors - weight pre and weight post intervention (for the two groups)
    - Aerobic capacity pre and Aerobic capacity post (for the two groups)

    AND

    how these are related/correlated to 4 variables pre/post (for the two groups)

    Does that make sense? thank you for the reply, much appreciated.


  • #4
    ron_1
    Registered Users, Registered Users 2 Posts: 9 ✭ron_1


    Was thinking so far, Split the data set into intervention and control.

    Run paired samples T tests for each of the variables, as well as correclation of the 4 variables?

    slightly lost to be honest..


  • #5
    tritium
    Registered Users, Registered Users 2 Posts: 7,666 ✭✭✭tritium


    Seems reasonable based in what you describe. A couple of things to consider:

    Assess normality- if severely non normal you may need to apply a non parametric test instead

    Consider adjusting individual significance levels if you're interested in a conclusion at an overall significance level.

    Interaction plots for pairs of factors on the response may also be useful


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