Hi Listers,
I am interested in assessing the relationship between diabetes diagnosis (yes/no) and age in my data. In the summary statistics, we report results by age group but for this analysis I am opting to use age as continuous - still to clear it with my colleagues.
it was suggested I may want to use the Cochran-Armitage trend test using ptrend
ptrend nyes nno age
The Chi2 for departure has p<.001 which suggests the null hypothesis is not met. Does it mean that I should not be using the CA test as the assumption of linearity is not met?
I am also considering that, seen that I am using age as continuous, I could simply run a simple logistic regression with age as a predictor. Is there a way to assess if there is a linear association between diagnosis and age? Plotting the data shows a decrease with a dip at age 55 which is followed by an increase in diagnosis rates which suggests a non-linear association.
What's the best way forward?
Thank you in advance!
Related Posts with Trend analysis - ptrend
boxplots across groups?Dear All, My purpose is to replicate the following graph from a paper. Array The original dataset …
drop observationsHello! I am new in STATA. Please help me with this issue I need to drop observations with "choice" …
How to identify if each ID has two unique values for a variableHello! I am somewhat new to Stata and have tried to find an answer to this on other threads but have…
Query on teffects psmatchI am running propsensity score matching for an evaluation project, but due to confidentiality, do no…
ols interactions (is the effect of age on seius different for male and female?)Clyde Schechter is the effect of age on seius different for male and female? reg seius i.female##…
Subscribe to:
Post Comments (Atom)
0 Response to Trend analysis - ptrend
Post a Comment