I am helping with a statistical analysis plan for an RCT. We want to control for the outcome variable at baseline and also use sequential analysis with alpha spending. Sequential designs are new to me so I am trying to read up on the literature, but all the examples and discussions I can find just discuss simple models comparing two groups without other covariates.
If I understand things correctly, the theory requires a normally distributed test statistic and determining the information fraction at the individual interim analyses. Mimicking the considerations for a simple comparison of two means I could use the fitted coefficient of the treatment and its standard error to get the test statistics and use the number of subjects enrolled as the information fraction, but it is far from obvious to me that this is a good approach. My specific questions are:
- Wouldn’t the distribution of the baseline values affect the correlation between effect estimates at the interim analyses and thus the information fraction?
- Doing a z-test on a regression coefficient seem suboptimal, shouldn’t I at least use the corresponding quantile of a t-distribution? Or - even better - is it possible to do likelihood-ratio test with alpha-spending?
- Am I missing something basic? Is there a good reference for this sort of design?