1

I have a basic pre-post trial design. Two randomized Groups and two tests for each participant in each group one prior to the intervention (here V1) and one post (V2). I am completely new to this and have been reading up a lot on this and based on a few sources it was suggested that an ANCOVA test with the pre-test as a covariate was the most appropriate.

So, I modeled as follows:

y <- aov(V2~Group+V1, data=x)

And checked for normality of residuals and used the Levene's test to test for correlation between V2 and Group.

I got the following result for a certain variable of interest -

summary(y)
             Df  Sum Sq Mean Sq F value Pr(>F)    
Group         1   29996   29996   4.315 0.0386 *  
V1            1 3710598 3710598 533.844 <2e-16 ***
Residuals   325 2258983    6951                   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

I followed it up with a post-hoc Turkey Test and found that it was significant there as well.

I have a couple of questions:

  1. Is this the correct way to go?
  2. Why is my V1 (pretest) covariate having such a high level of significance and what does it mean? (I assumed that randomization essentially means that there is no difference between the groups at baseline).
  3. Can I conclude that there truly is a difference between the two groups for this particular aspect based on this?
GratefulForNow
  • 47
  • 5
  • This doesn't appear to be a specific programming question that's appropriate for Stack Overflow. If you have general questions about the interpretation of results from statistical models, then you should ask such questions over at [stats.se] instead. You are more likely to get better answers there. – MrFlick Aug 24 '20 at 20:10
  • Okay, thank you for your response! I will repost there, should I take this one down? – GratefulForNow Aug 24 '20 at 20:46

0 Answers0