I'm doing a study with data from a national representative population study. The design is cross-sectional. I've run into serious troubles with my data, and am doubting if I will be able to complete my thesis with a satisfactory level of quality.

The sample in total consists of over 4000 individulas. But after isolationg a group of individiuals which my research question related to, and exluding observations with missing data, I'm left with only about 240 individuals. The thought of how low this number is makes me shake at this point already, but it gets worse.

Becuase I actually want to compare three subgroups of these 240 individuals, and one of them (the smallest) has only 17 individuals. (Life satisfaction is the outcome.)

In addition i want to control for confounding variables, age, sex, marital status, eduaction and maybe level of physical functioning. How much does my data allow me to? I didn't ever think I would have to worry about this, as my original sample was so large, and noe I'm stuck with this rotten piece of material, and it makes me sick to the bone.

I have two questions I was hoping for a kind hearted individual or two to reply on:

1. Does linear regression allow me two compare the three groups when one group has only 17 individuals? I dummy coded the groups before i implemented them into the regression analysis.

**Am i right in that it is the t-test assumptions that applies here, and that the smallest group is too small for comparison, since it has only 17 individuals which is less than 30?**

**2. Do I have to worry about how many coviartes i include in the adjusted analysis when N is so small**

*Any*help, or attempt to help, is highly appreciated!