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Level III

## Multivariate analysis vs Proportional hazard model

Hello,

when we are exploring certain predictors for bad outcome (mortality), we usually run univariate, followed by multivariate models (including all univariate analysis with p < 0.20) with backward elimination, where we report outcomes of this final model with specific OR including CI and p values.

Now recently , when I explored proportional hazards models, as we do have for all patients time to event (death) or discharge home - I was suprised to see different outcomes than in my multivariate models, where I used the same variables.

Is it generally better if you have a time to event , exploring those variables with proportional hazards than with univariate / multivariate analysis ? Do I first run better a univariate analysis and based on those identified with p < 0.2 (?) , which I enter into my proportional hazard model ? Or do I enter all potential variables ? Do I have to explore and exclude colinearity in proportional hazard first ?

What would be the advantage / disadvantage for either multivariate or proportional hazard  ?

Thanks a lot, Marc

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Staff

## Re: Multivariate analysis vs Proportional hazard model

I am not sure what you specifically mean by "we usually run univariate, followed by multivariate models (including all univariate analysis with p < 0.20) with backward elimination" but if you mean a linear model with regression, then there are likely some important differences for your data. The main differences are (1) censored life data and (2) non-normal distributions of life data. Because of these differences, the proportional hazards model or the parametric survival model tends to give better and more realistic estimates and tests.

Learn it once, use it forever!
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Level IV

3 REPLIES 3
Highlighted
Staff

## Re: Multivariate analysis vs Proportional hazard model

I am not sure what you specifically mean by "we usually run univariate, followed by multivariate models (including all univariate analysis with p < 0.20) with backward elimination" but if you mean a linear model with regression, then there are likely some important differences for your data. The main differences are (1) censored life data and (2) non-normal distributions of life data. Because of these differences, the proportional hazards model or the parametric survival model tends to give better and more realistic estimates and tests.

Learn it once, use it forever!
Highlighted
Level IV

Highlighted
Level III

## Re: Multivariate analysis vs Proportional hazard model

Thank you all ! Marc
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