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From |
"Boecking, Benjamin" <Benjamin.Boecking@iop.kcl.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: AIC/BIC and "comparison of standardized beta coefficients" |

Date |
Fri, 5 Dec 2008 16:18:04 -0000 |

Dear colleagues, I am currently analysing a longitudinal dataset (n = 62, up to 14 measurement occasions per person) using Mixed Models in STATA 10 (as the n turned out to be too small to use other models and/or programs). (1) I have a dependent variable A1 (outcome), and an independent variable A2 (predictor), and control thorughout for time. (2) Moreover, I lag the dependent variable with various offsets to see (a) whether I can predict changes in the DV by "previous" predictors and (b) which "lag" predicts best. Outcome_lag1 -> Predictor || Outcome_lag2 -> Predictor || Outcome_lag3 -> Predictor. (3) Once I have calculated these models, I switch the positions of the DV and IV and do everything again to maybe get a hint at the directionality in which these influences work. Now here are my problems: (1) When I compare two different models (e.g. M_lag -> Y vs. Y_lag->M) it happens that - although the beta for one model is smaller - the corresponding z-value is higher AND the model fit is BETTER (i.e. smaller). (1.1) Also, it happens that the model fits the better, the higher the lag is (although the predictive power decreases of course). However, I suppose this is mostly due to the decreased number of observations (depending on the respective lag OR the change of IV and DV), and NOT to a better model fit as with each lag, betas decrease. - So how can I get a "true" model fit, that takes the strength of the prediction into account? (Keep in mind that a lagged DV and a lagged IV inevitably produce changed patterns of "deleted" obeservations) - Is there a way of comparing model fits of different models to make a comparative statement about the "goodness of fit"? - And if not - is there any other way of reasonably comparing the various lagged models? (2) I'd like to compare the A1->A2 and the switched-around A2->A1 models. Yet again, as different sets of observations are deleted each time (i.e. the empty obervations in the dependent variable with the longestlag which is included in the model), I cannot compare the model fit indices. - Is there any test around which tests beta coefficients (of DIFFERENT models) against each other? I apologize to all of my colleagues who think this to be a stupid question, yet, any help would be appreciated. Many thanks Benjamin * * 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/

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