I want to use regression output (b, se B and cov of several predictors) as input for a new analysis.
One example: I want to compute:
SE^2(b1) + SE^2(b2) + 2 COV (b1,b2).
If I do a basic regression in Mplus (which I used because I have a choice of estimators, that I don't have in spss), and I look at the covariance table, the values reported there are extremely different from the covariances I get from the bcov command in SPSS regression.
They are so different that I am convinced they do not reflect the same value (e.g., .484 in mplus, and -.064 in spss).
Can anyone tell me: - What "estimated sample statistics" -> covariates in Mplus vs. "coefficient correlations" => "covariances" in spss refer to? - which one you think might be the cov(b1), referred to in the output? (my instinct says the SPSS one is the one I need) - How I could obtain this in the other program (i.e., if I need the spss one, how can I get this in MPlus)?
Please note that I did use the same estimator in mplus for my mock data on which I tested this, all other estimates (b, seB etc) are the same.
Model in Mplus:
MODEL: !Main effects leka on S; leka on P; leka on M; !Correlations between predictors S with P; M with P; S with M; OUTPUT: tech1; tech4; samp; stand; mod(4); Sampstat Mod(3.84);
Model in SPSS:
REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS BCOV R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Leka_t3 /METHOD=ENTER S P M.