SAS Support Communities

Hi, It seems that when I'm using PROC LIFETEST to create a survival plot with number-at-risk printed on the x-axis, that whenever at least one stratum label is more than 3 characters the number-at-risk labels are printed as 1, 2, etc instead of the full strata format labels, while the strata names are printed as "1: [Label stratum 1]", "2: [Label Stratum 2]", etc. in legends (with the corresponding labels of each stratum instead of the bracketed text). See the attached file for an example (created using non-sensical data). I've been trying to get around this by modifying the template used to create the plots (Stat.Lifetest.Graphics.ProductLimitSurvival) to force the procedure to always print the full label (some additional tweaking will of course be necessary for long format labels), but I can't seem to get very much further at the moment. From what I can tell, the names to print in the figure are actually created before the template is called, since the parts of the plotting statements which hold the labels in question are never declared in the template. These include STRATUM (seems to hold stratum labels), and CLASSATRISK (seems to hold the number-at-risk labels). Is there any way to figure out where these undeclared variables come from? If not, is there any simpler way to do what I want? ... View more

I'm using the BY statement to have split calculations for various groups in the same dataset, but when I specify initial values for the intercept estimate in PROC GENMOD (INTERCEPT option to the MODEL statement), only the first of the BY-groups uses the initial value. Is there any way to give an initial value for each BY-group? Edit: Confused INITIAL and INTERCEPT options in original post. Message was edited by: T ... View more

I've just upgraded from SAS v9.1 to v9.2, and noticed the nice addition of AIC and other information criteria in the GENMOD procedure Goodness-of-fit output. However, I also noticed that the Deviance and Pearson Chi-square are not printed by default, but must be requested by the AGGREGATE option to the MODEL statement. The trouble is, for some reason that I don't quite understand, that when I leave the AGGREGATE option out, the Full Log Likelihood statistic becomes equal to the Log Likelihood, but when I give the AGGREGATE option the Full Log Likelihood statistic changes -- and consequently the AIC which is calculated from this (identical output in all other respects). As an example, the Goodness-of-fit output from two identical models (dist=bin,link=logit), save for the aggregate option. Note in particular the change in Full Log Likelihood. Without AGGREGATE option: Criterion DF Value Value/DF Log Likelihood -383.3357 Full Log Likelihood -383.3357 AIC (smaller is better) 770.6714 AICC (smaller is better) 770.6818 BIC (smaller is better) 780.7907 With AGGREGATE option: Criterion DF Value Value/DF Deviance 1082 722.9896 0.6682 Scaled Deviance 1082 722.9896 0.6682 Pearson Chi-Square 1082 1067.9233 0.9870 Scaled Pearson X2 1082 1067.9233 0.9870 Log Likelihood -383.3357 Full Log Likelihood -372.1276 AIC (smaller is better) 748.2552 AICC (smaller is better) 748.2655 BIC (smaller is better) 758.3744 All other output is identical. Should these values not be the same? ... View more