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  • multivariate logistic regression

    Dear Stata users,

    I have a project with multiple independent variables and one binary outcomes that I want to assess I am interested in looking for the predictors.
    here is what I have done
    1- check and visualize data.
    2-converted multi-categorical variables into multiple dummy variables.
    3-categorized most continuous variables.
    4-assessed the association between the independent variables and the outcomes using logistic regression.
    5 advanced those variables with P <0.1 (I have reach to this point)
    6 assessed for co-linearity
    7 form your final multivariate log regression using "mvreg" function.

    question 1: is this process correct? is there anything that I should do or adjust?
    question 2: mvreg is giving coef. Is there a way to convert them into Odds Ratios, apart from doing it manually?
    question 3: As I was searching for a way to get OR, I tried logit and regress functions for the same independent variable and outcome and I got different coef. Am I doing itwrong ?

    I really appreciate your feedback

    Amin

    thanks



  • #2
    The term 'multivariate' is actually preserved for 'multiple-outcome' variables. If you have a binary outcome variable, that is a logistic regression model and with several predictors/independent variables, should be called binary logistic multiple regression model. For the correct command type
    Code:
     logit outcome independent variables, or
    . The 'or' option will provide you the Odds Ratio. To get the Odds Ratio without the 'or' option, type
    Code:
    logistic outcome independent variables
    'regress' is for linear outcome variable and not recommended for binary outcomes.
    Last edited by Roman Mostazir; 05 Sep 2016, 06:28. Reason: typo
    Roman

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