st: Does MANCOVA suit my research question?

[Sascha Struys <saschastruys@gmail.com>]

Dear Statalist users,

I have doubts regarding the suitability of the statistical model I am
currently using to answer our research question. I am using Stata
11.2.

The following variables are involved:
- Two continuous outcome measures measured on two occasions (baseline
and 1-year follow-up) Out1, Out2, Cov1, Cov2
- Four continuous predictor variables, Pre1, Pre2, Pre3, Pre4
- Four continuous, one ordinal and three nominal covariates, Cov3,
Cov4, Cov5, Cov6, Cov7(ordinal), Cov8(nominal), Cov9(nominal),
Cov10(nominal)
  (these are demographics and measures that are associated with the
outcome measure)

We want to estimate the association of the four predictor variables
(Pre1 to 4) with the two outcome variables (Out1 & 2) assessed at the
1 year follow-up,
adjusting for the same measure assessed at baseline (Cov1 & 2) and
other covariates (Cov3 to 10).
Next to that we predict that the four predictor variables will be
stronger associated with outcome 1 versus outcome 2.

I took the following steps: first, I build a MANOVA model testing for
the overall significance of the model
and the overall significance of each predictor variable on both
outcome measures combined.
Second, I performed multivariate regression analysis to obtain the
coefficients of the predictor variables for both outcomes.
Third, I performed four F-tests to test the hypothesis that the
predictor variables are stronger associated with outcome 1 versus
outcome 2.

I used the following syntax:

. manova Out1 Out2 = c.Cov1 c.Cov2 c.Cov3 c.Cov4 c.Cov5 c.Cov6 Cov7
Cov8 Cov9 Cov10 c.Pre1 c.Pre2 c.Pre3 c.Pre4
. mvreg
. test [Out1]Pre1 = [Out2]Pre1
. test [Out1]Pre1 = [Out2]Pre2
. test [Out1]Pre1 = [Out2]Pre3
. test [Out1]Pre1 = [Out2]Pre4

My questions are:
Is this a suitable statistical model to answer our research question?
Does the multivariate statistic for Pre1 (continuous variable) and its
corresponding significant (p<0.05) F-ratio
state that the overall association of Pre1 with the combined outcome
measures, adjusted for covariates and other predictors, is
statistically significant at the p<0.5 level?

Does this model automatically adjusts the means of the outcome measures,
so that an overall significance of a predictor demonstrate that the
effect of that predictor is significant
given that the sample would have the same scores on all other
covariates and predictors? Would the method of analysis then be
MANCOVA?

Thanks for your consideration,

S.Y. Struijs
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