# Search results

1. ### P value for trend

I would be very grateful if someone could help me with the code for this - I'm reporting the incidence of stroke in patients with diabetes versus no diabetes in 5 year bands, and would like to calculate the P value for trend over time if possible. I've tried the ptrend command but I'm confused...
2. ### How do I calculate p value for incidence rate

Thanks guys much appreciated!
3. ### How do I calculate p value for incidence rate

Hello, I have calculated the crude incidence rates per 1000 population per year of strokes in patients with and without kidney disease e.g.18.37 (16.94-19.9) vs 6.37 (5.78-7.0). How do I calculate the p value for difference? Thanks!
4. ### Case-case comparisons

Thank you for these suggestions! I don't think we are missing any confounding variables but you might be right about sample size. I have used a simple logistic model for crude ORs and multiple logistic for age-adjusted ORs.
5. ### Case-case comparisons

Dear all, I have a population of 2000 patients - all of whom have had a stroke. I have calculated the ORs of the stroke subtypes (there are 7 subtypes) according the presence or absence of kidney disease. However, some of the results don't really make sense and kidney disease appears to be...

Hi, I have a table of baseline characteristics of a cohort in which I have compared the differences between those with kidney disease and those without, using a combination of Chi-square test, t-test, or Kruskall-Wallis test as appropriate. How do I age-adjust the P values that I get from these...
7. ### Comparing correlation coefficients

Or a chi square test here? http://home.ubalt.edu/ntsbarsh/business-stat/otherapplets/MultiCorr.htm
8. ### Comparing correlation coefficients

Could I do just do R to Z fisher transformation and then do anova of the Z values? If I do this, should I use bonferroni correction? Thanks!
9. ### Comparing correlation coefficients

I have a group of about 1300 patients who had had disease 1 (subgroup 1), disease 2 (subgroup 2), or disease 3 (subgroup 3). I have correlated certain biomarkers with their kidney function in the whole group (N=1300), and then in each of these subgroups (N = circa 400 in each subgroup) e.g...
10. ### Comparing correlation coefficients

I have a group of about 1300 patients who had had disease 1 (subgroup 1), disease 2 (subgroup 2), or disease 3 (subgroup 3). I have correlated certain biomarkers with their kidney function in the whole group (N=1300), and then in each of these subgroups (N = circa 400 in each subgroup) e.g...
11. ### Comparing correlation coefficients

I have a group of about 1300 patients who had had disease 1 (subgroup 1), disease 2 (subgroup 2), or disease 3 (subgroup 3). I have correlated certain biomarkers with their kidney function in the whole group (N=1300), and then in each of these subgroups (N = circa 400 in each subgroup) e.g...
12. ### Comparing correlation coefficients

I have a group of about 1300 patients who had had disease 1 (subgroup 1), disease 2 (subgroup 2), or disease 3 (subgroup 3). I have correlated certain biomarkers with their kidney function in the whole group (N=1300), and then in each of these subgroups (N = circa 400 in each subgroup) e.g...
13. ### Comparing correlation coefficients

Hello, I have a large sample of patients who have had a TIA, minor stroke or major stroke. I have been looking at correlations in each of these three groups. Is there a statistical test in SPSS (or elsewhere) that would allow me to compare the correlation coefficients between each of three...
14. ### Is there a formal test for linearity?

Using SPSS, in preparation for correlation analysis, apart from scatterplots, is there a formal statistical test for linearity for two continuous variables? Someone suggested using Analzye -> Compare means -> Means -> under options, test for linearity? Is that the best test for this purpose...
15. ### When to log-transform?

Thank you - is it okay to leave them as continuous variables then?
16. ### When to log-transform?

Thank you - that is very helpful! My two variables are continuous variables though. I've read somewhere that Spearman's rank correlation requires one of the variables to be ordinal? Is that true?
17. ### When to log-transform?

Should Iog-transform variables for correlation if they aren't normally distributed even if I'm using a non-parametric test for correlation? And if so, why? Thanks for your help!