Statistical t test for unequal sample sizes (paired samples) I am analyzing the paired samples. Patients with drug at time point 0, at time point 12 weeks, time point 24 weeks. 
I would like to see the significant differences in the patients over the time points. In other words I would like to see how effective the drug is? 
One problem here is I have 10 samples at zero time point, the samples have been given the drug at 12 weeks time point but two samples are missing for some reason. The same for third time point as well. My guess is I wont be able to use paired t test now because of unequal sample sizes. 
Which statistical test would be appropriate for this scenario? Any help/suggestions would be much appreciated.
Here is my experimental design.

  T0 T12 T24
n=10  8   8

 A: If you make the assumption that some samples are missing at random, you can:


*

*Conduct a paired test, leaving out the data for people that you don't have

*Conduct an unpaired test for the whole data
Then you get 2 p-values, and you have to


*

*Multiple adjust, that is, e.g., with a Bonferroni correction. Multiply the p-values by 2, if, after that, you reject one of them, you can reject your original null-hypothesis


Issues with the approach


*

*If the data is not missing at random, and in the worst case, the effect that you are testing for is inverted between the paired data you have, and the paired data you don't have, your statistic will be wrong


If you don't want to make this assumption, I don't see how you can leverage the pairedness of your data, since you don't know why the data is missing. That is, you will have to conduct an unpaired test
A: If the three time points are important, you should use an analysis for repeated data. But your sample size is small...(see for example http://bales.faculty.ucdavis.edu/wp-content/uploads/sites/250/2015/08/Educational-and-Psychological-Measurement-2015-Muth.pdf). 
An alternative would be to compare T12 to T0 on the one hand, and T24 to T0 on the other. What is the type of outcome?
