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markbailey

Staff

Joined:

Jun 23, 2011

Re: Adjustment for variable (age, weight, sex, BMI, etc.)

  1. Select Analyze > Fit Model.
  2. Select Genotype and click Y.
  3. Select Glucagon and all the covariates.
  4. Do you expect interaction effects?
    1. If so, click Macros and select Factorial to Degree (2).
    2. If not, click Add.
  5. Click Run.
Learn it once, use it forever!
ZiV

New Contributor

Joined:

Jul 16, 2018

Re: Adjustment for variable (age, weight, sex, BMI, etc.)

would you happen to know if I can get the means and std of the adjusted results? When I do the process you've described I can see the p value of the adjusted variables, but I don't see their distribution. I know that in SPSS this is one of the outputs.
Ted

Community Trekker

Joined:

Mar 29, 2016

Re: Adjustment for variable (age, weight, sex, BMI, etc.)

I think, it's possible to use "Analyze > Fit Y by X", if the continuous variables to transform to discrete (better binary). For example, for age take less/more than 60, for weight a certain number that divides population into normal weight and obese, etc. Anyway: Select Glucagon as Y.