So you get number 1 from this output and number 2 is not available.
Andy Ross posted on Monday, November 07, 2005 - 11:12 am
Many thanks for your reply.
Maybe i'm reading the output wrong but i was hoping for a significance test/p-value telling me whether the full model was significantly better than the model with no predictors.
Do i need to calculate this by hand from Loglikelihood HO value? And if so, how would i go about doing this? My apologies if this sounds a little elementary. I have asked around but everyone here is used to the standard SPSS/Stata output...
You should run two models both with the covariates in the model: (1) a model with the slopes of the covariates free and (2) a model with the slopes of the covariates fixed to zero. You can then compute the loglikelihood difference and -2 time that is the chi-square difference.
Manuel posted on Monday, January 09, 2006 - 12:00 pm
Hello, I have a similar question: I am running a standard discrete time survival analysis. Without covariates I obtain a LL which is identical to that of other programs (i.e., Systat etc.). However, after including a single continuous covariate (proportional hazard assumption) the values differ vastly - how come (Mplus: -540.28 vs. SPSS/Systat:-1167.46)? THANK YOU VERY MUCH IN ADVANCE!!!
When there are covariates in the model, the loglikelihood values are on a different scale. This is why to compare nested models you need the covariates in both models.
Manuel posted on Monday, January 09, 2006 - 1:35 pm
thank you very much for your prompt reply! However, please let me rephrase my question: Should the chi-square diff test (effect vs. no effect of the covariate; covariate is part of both models but fixed to zero in the more restrictive model both models are nested) be identical to the chi-square diff test in the cox regression model (using any other program)?
Part of the reason I am asking is that Muthén & Masyn (2005, p. 36) note that Mplus can handle continuous covariates, while the traditional log-linear framework only allows categorical variables. I was not aware of that fact - but that should be reflected in the LL, shoud not it?
I don't know if the loglikelihoods would be the same. The Mplus loglikelihood is for y given x. If the cox regression loglikelihood is for y and x, then they would be different. I think the difference in the loglikelihoods would be the same however. Also, the Cox regression model usually means continuous-time survival. Mplus estimates a discrete-time survival model. I am assuming you are doing a discrete-time survival model.
Yes, that should be reflected in the loglikelihood.
Manuel posted on Monday, January 09, 2006 - 3:37 pm