I'm a statistics newbie, so please be gentle
I'm trying to figure out what test to use to analyze a categorical concurrent with continuous predictor for a categorical response.
For example:
How is hypertension with incrementally increasing age associated with overall death?
I'm trying to determine if hypertension is associated with overall death to varying degrees depending on the patient's age
i.e. As patients get older, they are more likely to die if they have hypertension than if they did not.
I have both time to death (continuous) and event of death (categorical) data.
All and any advice will be very much appreciated! thank you!
Thank you for your kind response Tyron!
I read both links.
I edited my question to clarify it.
From reading up on Laerd's Multi log regression, I'm not sure if multinomial log regression will be able to demonstrate the likelihood of an outcome for a categorical variable dependent on the change in the continuous variable
Hi Trenton
I think you should use Cox Proportional Hazard Model. This is time to event analysis and Hazard ratio will show you the effect of covariates in the model.
In your study , You have event (death) and time period (time to death).
covariates are : Hypertension (dichotomous) , Age (Continuous or categorical) and interaction term hypertension*Age
The hazard ratio (HR>1) will explain the effect of hypertension on mortality. also interaction will explain older age people with hypertension are at more risk or not.
All the best.
Before you conduct research, you need to know the types of statistics you are going to employ (parametric or non parametric) and the data scale requirement for each type - whether interval scale, ordinal/categorical etc. Statistically, it is wrong to collect data first using whatever scale you can think of then only looking for statistical methods that suit your scale.
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