Message/Author 

Amy Hartl posted on Saturday, September 22, 2012  3:22 pm



Greetings, I'm running a DTSA and would like to view the survival and hazard plots. I specify Plot2 in the output command, but it says the only plots available are: Histograms (sample values, estimated factor scores) Scatterplots (sample values, estimated factor scores) Item characteristic curves Information curves Are survival plots only available for continuous time SA? If not, how can I obtain these? I am following example 6.19 from the manual and am running version 6.11. Thank you! Amy 


You need to use the DSURVIVAL option of the VARIABLE command to specify which variables are the discretetime survival variables. Then you will get the plots. 

Amy Hartl posted on Sunday, September 23, 2012  9:13 am



Great, thank you! This yielded the estimated baseline survival curves. Is there a way I can get the estimated baseline hazard curves? It won't let me select it when I'm the plot menu. Below is the syntax in case that's useful. Thank you! TITLE: DTSA time and fship freq only DATA: FILE IS rec7to12.dat; VARIABLE: NAMES ARE dyadn f1 f2 freqF1 freqF2 u7 u8 u9 u10 u11 u12 ; USEVARIABLES= freqF1 freqF2 u812 ; CATEGORICAL = u8u12; dsurvival= u8u12; MISSING ARE ALL (9999.00); ANALYSIS: ESTIMATOR = MLR; MODEL: f BY u8u12@1; f ON freqF1 freqF2; f@0; OUTPUT: sampstat; stdyx; PLOT: TYPE IS Plot3; 


That plot is for continuoustime survival. 

Amy Hartl posted on Wednesday, September 26, 2012  9:09 am



I see. Okay, thank you! 

Amy Hartl posted on Wednesday, September 26, 2012  11:37 am



I see that loading all of the indicators @1 enforces the proportional odds assumption. How can I test the constant hazard rate assumption, i.e., how can I constrain the hazard rate to be equal across time? Can I do this without using type=mixture and a latent class design? Thank you for your help! 


You can run the model saying e.g. u1u5 on x; versus u1u5 on x (1); The latter approach is the same as saying f by u1u5@1; f on x; Twice the loglikelihood difference for the 2 models gives a chisquare test. 


Hi, I try see how the change of family cohesion during middle school influences high school substance use. The former was modeled as a growth curve and the later was a discrete survival. How can I combine the two in one model? I want to see if the family cohesion change will influence survival function. Is my syntax right? variable: names are age income sex sub4 sub5 sub6 w1f w2f w3f; usevariables are age income sex w1f w2f w3f sub4 sub5 sub6; categorical are sub4 sub5 sub6; missing is blank; classes=c(1); analysis: type=mixture; starts=100 10; ALGORITHM=INTEGRATION; model: %overall% if sfw1f@0 w2f@1 w3f@2; sd4sd6 on if sf(1); sd4sd6 on age sex income(2); Thank you. 


You say sd4sd6 on if sf(1); but those sd vbles are not in your usev list. They need to be scored as discretetime survival variables. And you may want to specify f by sd4sd6@1; f on age sex income; 

WenHsu Lin posted on Wednesday, May 20, 2015  7:25 pm



Thank you Dr./Prof. Muthen May I ask one follow up. The effect of all the covariates on the survival function is modeled on the on statement right? The explanation of such coefficient is similar to those we would get in the regular survival analysis right (i.e., the increase one unit in a covariate will increase the risk of experiencing the event)? Thank you. 

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