I need help with choosing which tests to use, as well as the goal of the testing. I am sure some of my questions are answered already on this forum (though I did not find all I needed when searching) or in a textbook. However, I need som help specific to my project.

I have a dataset of 29 observations and a range of variables. The observations are biological structures (within humans), and we are studying whether they have changed shape from time A to time B (a very unspecific explanation, but will do for now). The time span between time A and B is not the same for all structures. Information about whether each structure has changed is available in two ways: 1) One dichotomized variable "Changed" gives the value "1" for those structures that changed from A to B, and "0" for those that did not. 2) A few continuous variables describe factors X, Y, Z of the structures at point of time. Variables calculation the difference between e.g. factor X at time A and factor X at time B describe the amount of change.

Other available variables are continuous variables describing the structures, as well as a range of categorical variables describing the patients whose

Here is what I wish:

- I want to test whether there is difference present
*at time A*between factors X, Y, Z of those structures that subsequently changed, and those that did not; - I want to check whether the change is affected by time between A and B (e.g., do the structures that has a large time span between A and B change more than those with shorter, or do they not?);
- I want to test whether the factors in (1.)
*adjusted*for the time between A and B.

Here are my preliminary solutions:

- For (1), I guess a T Test is a good option (assuming parametric distribution). I have also tried using Logistic regression (with the dichotomized variable Changed as the dependent variable), but that gives me a higher p value. As far as I've understood, but not totally understood, that difference has something to do with the nature of those tests.
- For (3), a logistic regression would be best. Changed as the dependent variable, and because of sample size, restricting myself to two undependent variables: [Structure factor at time A] and [time between A and B]. However, in this small project, that seems to weaken results.
- For (2), I can use linear regression ([Amount of change between A and B for each structure] against [Time span between A and B for each structure]. Or I could present it graphically with a scatter plot.

Here are my problems/questions:

- Is the project to small to be analytical? In a larger project, I would jump right at Logistic regression, allowing me to adjust possible confounders. However, will Logistic regression just "blur" things in such a small project?
- Is it best to only be descriptive? Is it better to only report univariate statistics for [1], with a T test (e.g., "is there a difference between the mean of factor X at time A among those structures that did change versus those that did not?"), and only assess the impact of time between A and B graphically with a scatter plot?
- Have you got suggestions for any other tests or ways of describing the data?

Thankyou in advance.