Hi,

well, i want to compare two paired groups (pre and post). the two groups have different sample sizes, and when i used paired student test (paired t-test), i observe that so many of my data are not taking into account (For example : Group 1 = 12 samples; Group 2 = 8 samples, when the t test is applied it calculate the p value between 8 samples). I wish you got my idea. so if you have any recommendations or explanation of that i will be so gratfull.

Thank you

Before you do anything, you need to give serious consideration to whether the surviving samples are comparable to the lost samples. If you beleive that they are then read on.

If you have access to a decent statistical package, like SPSS, SAS, or R, you can use a linear mixed model to handle this situation. The data set will need to be formatted with one observation per line, and you'll need two independent variables: a sample ID number, which will be the same for observations taken on the same sample, and a variable to indicate whether the observation is pre or post. The IDs will be a random factor; the pre–post indicator, a fixed factor. The software will calculate a t-test using all the data while taking into account the partial matching.

Alternatively you can perform a t-test by hand. The t-statistic is

t = (m2 - m1) / se , where

m1 and m2 are the sample pre and post means, respectively, calculated using all the data; and se is the standard error of the difference, calculated as follows:

se = sqrt[s1^2/n1 + s2^2/n2 - (2/n)cov(x,y)] ,

where s1 and s2 are the sample pre and post standard deviations, n1 and n2 are the pre and post sample sizes, and n is the number of complete pre-post pairs. You will have to look up how to compute the sample covariance, cov(x,y), which you will compute using only those samples having both pre and post observations, You will also need to look up how to compute the degrees of freedom for the t-test. See the wikipedia article on the "Welch-Satterthwaite equation".