I am running a one-arm study in which a scale result (blood ketones) are reported across two consecutive 28 day periods (Control period=diet alone, Intervention=diet+supplement). This means I will have 56 data points per patient. I want to know if there is a significant change in both the total level of ketones and it would also be good to know if there is a difference in the daily variation of ketones. My plan was as follows:

Take a mean for each 28 day period per patient. Compare means across the two periods via paired t-test.

Calculate SD for each 28 day period, compare SDs via paired t-test as above.

Is this approach valid or should I use some form of ANOVA?

Actually, to further complicate matters, there is also a three day baseline period (no special diet) before the 56 day study starts in which patients report their blood ketones. Is there a good way to utilise all 59 data points across three different periods (3 day, 28 day, 28 day). We take more in depth ketone measures the for three days of baseline, control and intervention periods, so perhaps a better approach would be to just use 3 days across each period as then they are equal length.

I appreciate this sounds like an odd study design, but there were good reasons for it! ]]>

I need some guidance with respect to biostatistical analysis of my study data:

Prospective study which studies the outcome of a surgical procedure done for a fracture with a sample size of 30 patients

The outcome is being measured as two categorical variables (functional and radiological) at the end of 6 months from surgery.

Both outcomes are measured as 4 categories (Excellent, Good, Acceptable, Poor).

I wish to analyse the data as:

1. Are the surgical results significant in terms of functional outcome and radiological outcome separately

2. Is there a correlation between the functional and radiological outcome

Which test should be applied as there is no population data?

Any help will be greatly appreciated

Thank You. ]]>