*Post by l***@gmail.com*Let me get into things briefly. I've got two independent groups

(samples): A) one as experimental and one as B) control group. Each

sample has variables X and Y. If more precisely, X is some

particular posture which dependent variable Y depends on. I am going

to apply only a confouding variable (intervention) to treat X on

EXPERIMENTAL and NO VARIABLE (e.g PLACEBO) on control group and

check if any changes being made upon Y (pain). I am not going to

talk nor about distribution nor about linear regression model so to

check any significant differences available in between independent

groups.

The question is only in the Subject line:

Subject: What SPSS procedure to follow in order to measure each

independent group's dependent variable's mean?

That is modified by "to check any significant differences".

presumably, especially, in Y. We are also told that Y depends

on X. And that you don't want to use a regression model.

Okay. You have requirements that conflict. Make up your

mind.

You can check means and the difference in X with a t-test.

If the groups differ by more than the least amount in X, then

X "confounds" whatever you see for a difference in Y -- A

simple t-test would be a poor test for "significance."

If X and Y are both continuous, the obvious comparison

would be the covariate/regression approach. An ANOVA

with a covariate gives means and adjusted means. But

there is an assumption that the regression lines are parallel.

Look at a scattergram of X and Y with the two groups

marked by different symbols to see what is going on --

whether lines are parallel and which means may differ.

--

Rich Ulrich