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From |
Sascha Struys <saschastruys@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Does MANCOVA suit my research question? |

Date |
Fri, 13 Jan 2012 20:08:23 +0100 |

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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: Does MANCOVA suit my research question?***From:*Cameron McIntosh <cnm100@hotmail.com>

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