How to test if gender impacts mortality rates when already considering age



Hi, I am currently working on a research project where I'm analysing the impact of different factors on mortality.

I have the past 10 years of data from a specific hospital and I have graphed the mortality curve by age separately for males and females. I can see that the one curve lies above the other so there seems to be a difference caused by gender but I want to have some sort of statistical value showing whether the difference is statistically significant.

I have p values showing that if I consider gender on it's own then this is significant (used a chi squared test I found online). But given that I'm also considering age, I want to check if gender still has a significant impact on mortality when I have already taken account of age.

Any help would be greatly appreciated!

Thanks so much.



Less is more. Stay pure. Stay poor.
Is mortality binary variable, Yes/No?

If so, you need to use multiple logistic regression and include in the model:

mortality = age + gender + age*gender, the latter being the interaction term. If it is significant the log-odds slopes by gender significantly differ.

Can you provide more information about the study context. I have a feeling there are more things you need to consider. I am an epidemiologist and run data all of the time and per your description, I am wondering if there are biases you need to address or control for in your analytics.



So I grouped the data into age bands and calculated mortality rates for each band. I then graphed this for males and females separately and wanted to see if the two graphs are statistically significantly different. I was considering just calculating chi squared p values for each age band separately but I would've preferred one overall p value.

There's actually a lot of other variables I'm considering (both dependent and independent) but I was just getting stuck on this principle of testing whether gender makes a difference or is it just that the females all happened to be older in my sample.

I haven't done stats in about 6 or 7 years so my knowledge here is lacking and I've been using mostly online tools to help me compute things. I also don't have access to (or know how to use) any statistical software. My knowledge basically consists of Excel which doesn't help much here.



No it's more like cubic or quadratic even. I think it would help if I could find a way to completely strip out the effect of age and then test if what's left between male and female is statistically significantly different but I don't know if that's possible.