I have 22 patients. They have been measured pre and post treatment. There are 3 measurements per patient before treatment (pre baseline), and four measurements after treatment (post baseline). There are also missing values.
Patient pre1 pre2 pre3 post1 post2 post3 post4 1 3.2 2.7 3.3 5.9 NA 5.4 5.2 2 2.1 NA 3.4 6.6 5.3 6.8 5.7 ... 22 3.5 NA NA NA NA 2.3 5.3
I need to perform a Wilcoxon signed rank test to compare pre and post baselines. Since the number of pre and post data differ, I first calculate means of the pre and post values for each patient and then perform the Wilcoxon test on the two resulting vectors of means of equal length.
pre <- c(mean(pre1.patient1, pre2.patient1, pre3.patient1), mean(c(pre1.patient2, ... post <- c(mean(post1.patient1, ...
But due to the missing values, the number of values differ for each patient.
Do I need to use weighted means for the Wilcoxon signed rank test?
It would be great if you could provide a source for your answer, but not necessary.