Covariate significance testing - What is it?

Community SlicerSALT
6

Hi Quentin
Not sure I was able to follow everything

  1. you have 5 variables in total: group (4 different groups of PD patients), center/site, sex, age and education. Of these, group (4 valued), center (how many values?) and sex (binary) are group variables (i.e. categorical variables). age and education are continuous variables. Is that correct?

  2. how did you structure the input for shapeAnalysisMANCOVA? All groups/categorical variables need to be binary, mutually exclusive variables for shapeAnalysisMANCOVA. So, you would need to somehow be able to separate the analysis into different sets where you have only binary associations. That’s one of the downsides of using shapeAnalysisMANCOVA. If there is an order to your diagnosis (e.g. severity of disease groups) then you could group them into binary sets of increasing order. Alternatively, e.g. for the centers, you can have a binary variable for each center (so called one-shot variables), i.e. center1 (0/1), center2 (0/1) etc

  3. you mentioned you did an interaction test. But, if I understand correctly, you want to do a group difference test. Interaction tests with shapeAnalysisMANCOVA only work with continuous variables, e.g. if you are interested in the association of age with shape, correcting for the other co-variates.

  4. in a complex setting, such as yours with 3 categorical variables (2 of them being non-binary), shapeAnalysisMANCOVA is likely not going to yield correct results (there are just too many distinct sets to permute over).

  5. how did you set up the MFSDA analysis exactly. MFSDA may interpret your group variable (with 4 values) as a continuous variable. I will need to double-check, but I am quite sure that also MFSDA needs binary categorical variables.