I have a short question regarding the data analysis. I have 2 data sets (data data frames *df). The first one is a signal which is yes / no / maybe and a second one is a data set which is response to this signal in percentage. The percentage increases after each yes and maybe (Like a rain fact and plant disease level). The signal response (second data set is delayed in time). I need to find out the relationships between this to data sets (signal and response). Which is the best method to do this in R.
PS.I tried cross correlation but results are not clear.
Thank you all
Example
Date Signal Response
01.02.2018 / no (as o) / 0%
01.03.2018 / yes (as 2) / 0%
01.04.2018 / no (as 0) / 0%
01.05.2018 / maybe (as 1) / 2%
etc....
Jos Feys Thank you very much, but I also need to find delay in time, in this case the time delay is a duration of incubation period for the disease, so I need to figured it out
You could pairwise compare the different (for the different time delays) correlation coefficients online:
http://vassarstats.net/rdiff.html
There is an article and SAS macro by Bill Leblanc on multiple comparisons of independent correlations:
Williams, R.H., & LeBlanc, W.G. 1995. Multiple Dunnett like Comparisons among Correlations for Equal N, Educational and Psychological Measurement, 55(3).
The SAS macro is in attachment, but maybe you just correct the p-values with some adjusting method (Bonferroni, Dunnet or other).
The 'R 'multcomp' package might be helpful here:
https://cran.r-project.org/web/packages/multcomp/multcomp.pdf
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