I have the data for an ambulatory assessment for autonomic cardiovascular functioning and the labels for posture are really mixed (the number in parenthesis represents the code, not the number of participants):
- lying (10)
- sitting (11)
- standing (12)
- walking (13)
- sitting/ standing (15)
- sitting/ standing/ walking (16)
- standing/ walking (17)
Looking for options, I found out that some studies focus on vertical vs. horizontal postures, or even more specific supine vs. prone positions (Houtveen, Groot, & Geus, 2005; Watanabe, Reece, & Polus, 2007; van Dijk et al., 2013). Best option to still make sense of the data seems to reduce the labels to two categories. I am using
SPSS to accomplish this:
RECODE Posture_Code (10=1) (11=2) (12=2) (13=2) (15=2) (16=2) (17=2) INTO posture_2.
Using recode I highly unbalanced the sample (e.g. 18 vs. 125 in one case) so, I decided to run the nonparametric
Mann–Whitney U test. Is this a valid approach and, if not, what alternatives do I have to still make use of the data? Here's what I got from the test:
Edit: By'making use of the data' I mean to test for a main effect of posture on pre-ejection period and RSA.