Hi, I was able to output a a restricted cubic spline (through effectplot statement in proc logistic) between my independent variable and binary outcome, sliced by a grouping variable. I would now like to change the axis and am trying to figure out how to save a "Logfit" output that also includes my additional grouping variable. I am then planning to recreate this graph in proc sgplot. I have noted the two main questions I have in red below.  Thanks for your help! proc logistic data=splines descending; class ruca(ref="1_urbancore") / param=ref; effect spl = spline(responsetime/ details naturalcubic basis=tpf(noint)knotmethod=percentiles(5)); model neurooutcome = ruca spl ruca*spl / expb cl outpred=Pred; effectplot slicefit (x=responsetime sliceby=ruca) / noobs clm; ods output fitplot=Logfit; (I was not able to output the LogFit with a group variable?) run; proc sgplot data=Logfit noautolegend; (how to I add a statement to indicate the separate series for a group variable?) band upper=_uclm lower=_lclm x=_xcont1 / transparency=.3; series y=_predicted x=_xcont1; xaxis values=(0 to 1200 by 100) grid offsetmin=.05 offsetmax=.05; yaxis values=(0 to 0.2 by 0.05) grid offsetmin=.05 offsetmax=.05 label="Predicted Probability of Survival with CPC 1 or 2"; title "Effect of RT"; run; ... View more

In my code I am attempting to calculate the elapsed time between two time points (response time). I have formatted all of my time variables into the "time." format in SAS. In majority of cases, I am able to calculate a positive elapsed time by subtracting time point 2 from time point 1 (i.e. 19:24:01 - 19:19:22 = 0:04:39 = 4 minutes 39 seconds elapsed).   Although there is a select group of observations where the time window crossed 12am (i.e.<23:59:59  and >00:00:00). Using my method to calculate the elapsed time, I am getting negative elapsed time. For example the time interval between 11:58:35PM and 0:05:51AM is calculated as -23:52, when the true interval should be 0:07:16 (7 minutes 16 seconds).   Does anyone know of a simple way to correct these observations? See current simple SAS code below: data datawithtime; set rawdata; elapsedtime=time2-time1; run; ... View more

I have been receiving the following error from SAS when I try to run a program.   ERROR: Insufficient space in file WORK.CARES1_8.DATA. ERROR: File WORK.CARES1_8.DATA is damaged. I/O processing did not complete From what I could gather from other forum posts, my temporary file work folder has been clogged up from SAS programs that have been incorrectly terminated (I have been terminating programs recently due to long running times). I am unable to find the folder to clear these temporary files? Is there a SAS proc or a location I should be looking in on my PC?   ... View more

I have created a multi-level logistic regression model using PROC GLIMMIX. I am able to obtain interaction estimates and 95% CIs on the multiplicative scale from the fixed effects output, although I am not sure if there is a simple way in SAS to output the estimates and 95% CIs on the additive scale (I am looking to calculate relative excess risk due to interaction [RERI] with a 95% CI). SAS code below. Thanks. proc glimmix data=cares2; class group outcome (ref="No") intervention (ref="No") smoker(ref="No") area(ref="urban") gender(ref="Female") /; model outcome = intervention area intervention*area gender / dist=binary link=logit ddfm=bw solution oddsratio cl; random intercept / subject=group; lsmeans intervention*area / slicedifftype=control('No' 'urban') adjust=bon oddsratio cl ilink; run; ... View more

I am conducting an interaction analysis in PROC GLIMMIX and would like to present my interaction analysis with a single reference category. The interaction is between two categorical variables (2-level and 5-level variable). I have only been able to build obtain an output displaying ORs with separate reference groups. See tables below - I am attempting to display results similar to Table 6 with a single reference group. proc glimmix data=cares2 method=quad; class group outcome (ref="No") intervention(ref="No") area(ref="small") gender(ref="Female") /; model outcome = intervention area gender age intervention*area / dist=binary link=logit ddfm=bw solution oddsratio; random intercept / subject=group; lsmeans intervention*area / slicediff=area adjust=bon oddsratio cl ilink; run;     ... View more

I am running a two-level multivariate logistic regression model in PROC GLIMMIX. My relationship of interest of the association between "intervention" and "outcome". My clustering variable is "level2". My moderating variable is "class" and I am adjusting the model for "a", "b", "c", and "d" confounders. All variables are categorical.   I am interested in identifying the effect if "class" on the relationship between "intervention" and "outcome". Most of the interaction terms in the Solutions for Fixed Effects tables are significant (p<0.001), although the type III tests of fixed effects shows a non-significant p-value for the overall "intervention*class" term (p=0.3881). The intervention*class Least Squares Means are all significant (<0.001). I am not exactly sure how to interpret these tables and could use some advice.   I am then provided with the Simple Effect Comparisons of intervention*class Least Squares Means By class. From my understanding, these are the effect estimates of the relationship of interest, stratified by my class levels. Is this correct? Also, is there a way to compare these effects apart from just observing to see if the ORs overlap?   Thank-you!       proc glimmix data=cares2; class level2 outcome (ref="No") intervention(ref="No") a(ref="No") b(ref="No") c(ref="No") d(ref="No"); model neurooutcome = intervention a b c d intervention*class / dist=binary link=logit ddfm=bw solution oddsratio; random intercept / subject=level2; lsmeans intervention*class / slicediff=class oddsratio cl ilink; run;     ... View more

I have 4 variables that are formatted as time variables (hh:mm:ss). Specifically, I am looking to exclude any observations from the dataset where where the time interval is 00:00:00, negative, or greater than 01:00:00.   How would I write this code in a typical if/then delete data set?     ... View more

Hi, I am trying to recode the variable "income" (numeric) into 5 stratified categories (new stratified variable = ses). Although my output demonstrates that only one category ("Q5") is being coded.   Is there a problem with my if/then/else statements? data data1; set data0; if income<25000 then ses='Q1'; if income<50000>=25000 then ses='Q2'; if income<80000>=50000 then ses='Q3'; if income<130000>=80000 then ses='Q4'; if income>=130000 then ses='Q5'; else sestatus=' '; run;     ... View more