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Yes. I also noticed I rename group to yr and in the model and random statement I had year instead of yr. It works now. ... View more

@jiltao Your request is below. I also attempted some of the options on the document I found online. When I changed the method for estimating the covariance parameters from REML to MIVQUE0 the data set converged. I attached the sheet of tips to help.    Also, do you think it may be because I am missing data for viral load? It reads in the files as "." The dataset is unbalanced and contains missing data. I do not know if that would cause the proc mixed model to not converge.    SAS code proc sort data = Firstvisit; by rfa_id testdate year; RUN; data avegvl_youth; set Firstvisit; keep rfa_id test_year testdate year sex_hars res_at_hiv_dx race_combined hiv_risk agegroup ccd4c ctimeyr days year mn quarter time first_cd4cgp result_vl_log10; by rfa_id testdate year; run; data youth_year; set avegvl_youth; if year=1999 then group = "1" ; else if year = 2000 then group = "2"; else if year = 2001 then group = "3"; else if year = 2002 then group = "4"; else if year = 2003 then group = "5"; else if year = 2004 then group = "6"; else if year = 2005 then group = "7"; else if year = 2006 then group = "8"; else if year = 2007 then group = "9"; else if year = 2008 then group = "10"; else if year = 2009 then group = "11"; else if year = 2010 then group = "12"; else if year = 2011 then group = "13"; else if year = 2012 then group = "14"; else if year = 2013 then group = "15"; else if year = 2014 then group = "16"; else if year = 2015 then group = "17"; else if year = 2016 then group = "18"; else if year = 2017 then group = "19"; else if year = 2018 then group = "20"; else if year = 2019 then group = "21"; else if year = 2020 then group = "22"; rename group = yr; run; ************************************* 1st Proc Mixed Code *****************************************************; ************************************* Unstructured *****************************************************; proc sort data = youth_year out = avegvl_youth_sort nodupkey; by rfa_id testdate year result_vl_log10; RUN; PROC MIXED data= avegvl_youth_sort covtest method=reml PLOTS(MAXPOINTS=NONE)noitprint; class rfa_id sex_hars (ref="F") res_at_hiv_dx (ref="Urban") race_combined (ref="Black") hiv_risk (ref="MSM") first_cd4cgp (ref="> 500") agegroup(ref="20-24"); model result_vl_log10= year ccd4c ctimeyr sex_hars res_at_hiv_dx race_combined hiv_risk first_cd4cgp agegroup ccd4c*sex_hars ccd4c*res_at_hiv_dx ccd4c*race_combined ccd4c*hiv_risk ccd4c*first_cd4cgp ccd4c*agegroup ctimeyr*sex_hars ctimeyr*res_at_hiv_dx ctimeyr*race_combined ctimeyr*hiv_risk ctimeyr*first_cd4cgp ctimeyr*agegroup/ solution cl outp = pred_un ; random intercept year / type= un subject=rfa_id; lsmeans sex_hars res_at_hiv_dx race_combined hiv_risk first_cd4cgp agegroup /diff adjust= tukey; title 'Mixed Model Results For Viral Load'; RUN; The output starts here:   581 proc sort data = Firstvisit; 582 by rfa_id testdate year; 583 RUN; NOTE: There were 57534 observations read from the data set WORK.FIRSTVISIT. NOTE: The data set WORK.FIRSTVISIT has 57534 observations and 36 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.07 seconds cpu time 0.07 seconds 584 585 data avegvl_youth; 586 set Firstvisit; 587 keep rfa_id test_year testdate year sex_hars res_at_hiv_dx race_combined hiv_risk agegroup 587! ccd4c ctimeyr days year mn quarter time first_cd4cgp result_vl_log10; 588 by rfa_id testdate year; 589 run; NOTE: There were 57534 observations read from the data set WORK.FIRSTVISIT. NOTE: The data set WORK.AVEGVL_YOUTH has 57534 observations and 17 variables. NOTE: DATA statement used (Total process time): real time 0.04 seconds cpu time 0.03 seconds 590 591 592 data youth_year; 593 set avegvl_youth; 594 if year=1999 then group = "1" ; 595 else if year = 2000 then group = "2"; 596 else if year = 2001 then group = "3"; 597 else if year = 2002 then group = "4"; 598 else if year = 2003 then group = "5"; 599 else if year = 2004 then group = "6"; 600 else if year = 2005 then group = "7"; 601 else if year = 2006 then group = "8"; 602 else if year = 2007 then group = "9"; 603 else if year = 2008 then group = "10"; 604 else if year = 2009 then group = "11"; 605 else if year = 2010 then group = "12"; 606 else if year = 2011 then group = "13"; 607 else if year = 2012 then group = "14"; 608 else if year = 2013 then group = "15"; 609 else if year = 2014 then group = "16"; 610 else if year = 2015 then group = "17"; 611 else if year = 2016 then group = "18"; 612 else if year = 2017 then group = "19"; 613 else if year = 2018 then group = "20"; 614 else if year = 2019 then group = "21"; 615 else if year = 2020 then group = "22"; 616 rename group = yr; 617 run; NOTE: There were 57534 observations read from the data set WORK.AVEGVL_YOUTH. NOTE: The data set WORK.YOUTH_YEAR has 57534 observations and 18 variables. NOTE: DATA statement used (Total process time): real time 0.04 seconds cpu time 0.03 seconds 618 619 ************************************* 1st Proc Mixed Code 619! *****************************************************; 620 ************************************* Unstructured 620! *****************************************************; 621 622 623 proc sort data = youth_year out = avegvl_youth_sort nodupkey; 624 by rfa_id testdate year result_vl_log10; 625 RUN; NOTE: There were 57534 observations read from the data set WORK.YOUTH_YEAR. NOTE: 207 observations with duplicate key values were deleted. NOTE: The data set WORK.AVEGVL_YOUTH_SORT has 57327 observations and 18 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.04 seconds cpu time 0.04 seconds 626 627 628 PROC MIXED data= avegvl_youth_sort covtest method=reml PLOTS(MAXPOINTS=NONE)noitprint; 629 class rfa_id sex_hars (ref="F") res_at_hiv_dx (ref="Urban") race_combined 629! (ref="Black") 630 hiv_risk (ref="MSM") first_cd4cgp (ref="> 500") agegroup(ref="20-24"); 631 model result_vl_log10= year ccd4c ctimeyr sex_hars res_at_hiv_dx race_combined 631! hiv_risk first_cd4cgp 632 agegroup ccd4c*sex_hars ccd4c*res_at_hiv_dx ccd4c*race_combined ccd4c*hiv_risk 632! ccd4c*first_cd4cgp 633 ccd4c*agegroup ctimeyr*sex_hars ctimeyr*res_at_hiv_dx ctimeyr*race_combined 633! ctimeyr*hiv_risk 634 ctimeyr*first_cd4cgp ctimeyr*agegroup/ solution cl outp = pred_un ; 635 random intercept year / type= un subject=rfa_id; 636 lsmeans sex_hars res_at_hiv_dx race_combined hiv_risk first_cd4cgp agegroup /diff 636! adjust= tukey; 637 title 'Mixed Model Results For Viral Load'; 638 RUN; NOTE: 16629 observations are not included because of missing values. NOTE: The data set WORK.PRED_UN has 0 observations and 0 variables. WARNING: Data set WORK.PRED_UN was not replaced because new file is incomplete. NOTE: PROCEDURE MIXED used (Total process time): real time 10.39 seconds cpu time 10.10 seconds ... View more

@jiltao Hello,   So I am still working on this issue. I round the dependent variables to just one decimal place after the decimal. I also recoded the years for example 1999 and put for example, 1, 2, 3, 4, etc.It still did not work. It also removed the warning but the OUTP=data set is empty. With no columns nor rows.   Courtney Jacks ... View more

Thank you. This worked. ... View more

Yes, the LSMEASN output the result.  I am very new to SAS so I hope I am not confusing myself. I can upload my results. My SAS code is below. On the class line I added all my fixed variables and reference one value. For example race = race_combined (ref "Black"). In the result I get Solution for Fixed Effects which compared Black vs White and Black vs Other. The random variable is viral load.  How do I get White vs Other? Will the output be within my "Solution for Fixed Effects ".   I also use LSMEANS and did it also. Is the Solution for FIXED Effects and Least Squares Means the same thing?    ************************************* Proc Mixed Code ***********************************; **************************************** Mixed Model ************************************; *********************************Viral Load by Year for Youth********************************; ods rtf file = "C:\Users\cjacks1\Downloads\Data\Youthprocmixedmodelstest.rtf"; data avegvl_youth; set Firstvisit; keep rfa_id test_year testdate year sex_hars res_at_hiv_dx race_combined hiv_risk baseline_cd4 agegroup ccd4c ctimeyr days year mn quarter time presentvl result_vl_log10; by rfa_id test_year testdate year; if result_vl>=0 then presentvl=1 ; *else if result_vl="." then delete; run; *Code incldues and removes repeated viral load that were averaged by year; proc sql; create table youthavgvl_yr as select *, mean(case when presentvl =1 then result_vl_log10 else . end) as avgvlyryouth from avegvl_youth group by rfa_id, year; quit; ************************************* 1st Proc Mixed Code *****************************************************; ************************************* Youth Part 1 *****************************************************; *sort data set with average viral load by rfa_id time and average viral load by year; *proc sort data = youthavgvl_yr out= youthavgvl_yr_sorted nodupkey; *remove duplicates; *by rfa_id year time avgvlyryouth; *run; *ods rtf; *Proc mix to look at youth mean viral load by residence, cd4, sex, race, and gender ; * multilevel (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 500") agegroup(ref="20-24"); *PROC MIXED data= youthavgvl_yr_sorted covtest noitprint method=reml PLOTS(MAXPOINTS=NONE); *class rfa_id sex_hars (ref="F") res_at_hiv_dx (ref="Urban") race_combined (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 500") agegroup(ref="20-24"); *model avgvlyryouth = year ccd4c ctimeyr sex_hars res_at_hiv_dx race_combined hiv_risk baseline_cd4 agegroup/ solution outp = pred; * random int year / subject=rfa_id Type= un vcorr; *title 'Mixed Model Results For Viral Load Trend Over Time For Youth Visits (Reference 1)'; *RUN; *ods rtf close; *ccd4c*sex_hars ccd4c*res_at_hiv_dx ccd4c*race_combined ccd4c*hiv_risk ccd4c*baseline_cd4 ccd4c*agegroup ctimeyr*sex_hars ctimeyr*res_at_hiv_dx ctimeyr*race_combined ctimeyr*hiv_risk ctimeyr*baseline_cd4 ctimeyr*agegroup ************************************* Youth Proc Mixed Models *****************************************************; *CJacks notes; *3 proc mixed models where used to determine which TYPE= was the best for the data analysis of mean vl over time; *TYPE= UN, CS, and AR(1); *sort data set with average viral load by rfa_id time and average viral load by year; proc sort data = youthavgvl_yr out= youthavgvl_yr_sorted nodupkey; *remove duplicates; by rfa_id year time avgvlyryouth; run; *When I ran the procedure without adding intercept or int after random the output showed everything but with it some outputs where cut out; PROC MIXED data= youthavgvl_yr_sorted covtest noitprint method=reml PLOTS(MAXPOINTS=NONE); class sex_hars (ref="F") res_at_hiv_dx (ref="Urban") race_combined (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 500") agegroup(ref="20-24"); model avgvlyryouth= year ccd4c ctimeyr sex_hars res_at_hiv_dx race_combined hiv_risk baseline_cd4 agegroup ccd4c*sex_hars ccd4c*res_at_hiv_dx ccd4c*race_combined ccd4c*hiv_risk ccd4c*baseline_cd4 ccd4c*agegroup ctimeyr*sex_hars ctimeyr*res_at_hiv_dx ctimeyr*race_combined ctimeyr*hiv_risk ctimeyr*baseline_cd4 ctimeyr*agegroup/ solution outp = pred_un ; *random intercept year/ Type= un subject=rfa_id; random year / type= un subject= rfa_id; lsmeans sex_hars res_at_hiv_dx race_combined hiv_risk baseline_cd4 agegroup /diff; title 'Mixed Model Test for Youth Unstructured'; RUN; ods rtf close; Output Log:   483 *CJacks notes; 484 *3 proc mixed models where used to determine which TYPE= was the best 484! for the data analysis of mean vl over time; 485 *TYPE= UN, CS, and AR(1); 486 *sort data set with average viral load by rfa_id time and average 486! viral load by year; 487 488 proc sort data = youthavgvl_yr out= youthavgvl_yr_sorted nodupkey; 488! *remove duplicates; 489 by rfa_id year time avgvlyryouth; 490 run; NOTE: There were 57534 observations read from the data set WORK.YOUTHAVGVL_YR. NOTE: 10467 observations with duplicate key values were deleted. NOTE: The data set WORK.YOUTHAVGVL_YR_SORTED has 47067 observations and 19 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.04 seconds cpu time 0.04 seconds 491 *When I ran the procedure without adding intercept or int after 491! random the output showed everything but with it some outputs where 492 cut out; 493 PROC MIXED data= youthavgvl_yr_sorted covtest noitprint method=reml 493! PLOTS(MAXPOINTS=NONE); 494 class sex_hars (ref="F") res_at_hiv_dx (ref="Urban") 494! race_combined (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 494! 500") agegroup(ref="20-24"); 495 model avgvlyryouth= year ccd4c ctimeyr sex_hars res_at_hiv_dx 495! race_combined hiv_risk baseline_cd4 496 agegroup ccd4c*sex_hars ccd4c*res_at_hiv_dx 496! ccd4c*race_combined ccd4c*hiv_risk ccd4c*baseline_cd4 497 ccd4c*agegroup ctimeyr*sex_hars ctimeyr*res_at_hiv_dx 497! ctimeyr*race_combined ctimeyr*hiv_risk 498 ctimeyr*baseline_cd4 ctimeyr*agegroup/ solution outp = 498! pred_un ; 499 *random intercept year/ Type= un subject=rfa_id; 500 random year / type= un subject= rfa_id; 501 lsmeans sex_hars res_at_hiv_dx race_combined hiv_risk 501! baseline_cd4 agegroup /diff; 502 title 'Mixed Model Test for Youth Unstructured'; 503 RUN; NOTE: 7898 observations are not included because of missing values. NOTE: The data set WORK.PRED_UN has 47067 observations and 26 variables. NOTE: PROCEDURE MIXED used (Total process time): real time 7.01 seconds cpu time 6.75 seconds 504 ods rtf close; ... View more

Hello,   So after speaking with my PI this is not what I am looking for. I need to to estimates for the fixed effects with more than 2 levels in sas. Do you know how I can achieve this? With LSMEANS computes least squares means (LS-means) of fixed effects.  ... View more

Hello, Okay. I will look into that. The response variable is the viral load which was converted to log_10. I can not send the data set but I will take a look at what you suggested. ... View more

Hello,   I am so sorry. I missed that part of the reply. My Output window was empty but I did have the Result. I attached it to the reply as a word document. The code log is below again: 346 ************************************* 1st Proc Mixed Code 346! *****************************************************; 347 ************************************* Youth Part 1 347! *****************************************************; 348 *sort data set with average viral load by rfa_id time and average 348! viral load by year; 349 *proc sort data = youthavgvl_yr out= youthavgvl_yr_sorted nodupkey; 349! *remove duplicates; 350 *by rfa_id year time avgvlyryouth; 351 *run; 352 353 *ods rtf; 354 *Proc mix to look at youth mean viral load by residence, cd4, sex, 354! race, and gender ; 355 * multilevel (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 355! 500") agegroup(ref="20-24"); 356 *PROC MIXED data= youthavgvl_yr_sorted covtest noitprint method=reml 356! PLOTS(MAXPOINTS=NONE); 357 *class rfa_id sex_hars (ref="F") res_at_hiv_dx (ref="Urban") 357! race_combined (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 357! 500") agegroup(ref="20-24"); 358 *model avgvlyryouth = year ccd4c ctimeyr sex_hars res_at_hiv_dx 358! race_combined hiv_risk baseline_cd4 agegroup/ solution outp = pred; 359 * random int year / subject=rfa_id Type= un vcorr; 360 *title 'Mixed Model Results For Viral Load Trend Over Time For 360! Youth Visits (Reference 1)'; 361 *RUN; 362 *ods rtf close; 363 364 *ccd4c*sex_hars ccd4c*res_at_hiv_dx ccd4c*race_combined 364! ccd4c*hiv_risk ccd4c*baseline_cd4 ccd4c*agegroup ctimeyr*sex_hars 364! ctimeyr*res_at_hiv_dx ctimeyr*race_combined ctimeyr*hiv_risk 364! ctimeyr*baseline_cd4 ctimeyr*agegroup 365 366 367 ************************************* Youth Proc Mixed Models 367! *****************************************************; 368 *CJacks notes; 369 *3 proc mixed models where used to determine which TYPE= was the best 369! for the data analysis of mean vl over time; 370 *TYPE= UN, CS, and AR(1); 371 *sort data set with average viral load by rfa_id time and average 371! viral load by year; 372 373 proc sort data = youthavgvl_yr out= youthavgvl_yr_sorted nodupkey; 373! *remove duplicates; 374 by rfa_id year time avgvlyryouth; 375 run; NOTE: There were 57534 observations read from the data set WORK.YOUTHAVGVL_YR. NOTE: 10467 observations with duplicate key values were deleted. NOTE: The data set WORK.YOUTHAVGVL_YR_SORTED has 47067 observations and 19 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.04 seconds cpu time 0.04 seconds 376 *When I ran the procedure without adding intercept or int after 376! random the output showed everything but with it some outputs where 377 cut out; 378 PROC MIXED data= youthavgvl_yr_sorted covtest noitprint method=reml 378! PLOTS(MAXPOINTS=NONE); 379 class sex_hars (ref="F") res_at_hiv_dx (ref="Urban") 379! race_combined (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 379! 500") agegroup(ref="20-24"); 380 model avgvlyryouth= year ccd4c ctimeyr sex_hars res_at_hiv_dx 380! race_combined hiv_risk baseline_cd4 381 agegroup ccd4c*sex_hars ccd4c*res_at_hiv_dx 381! ccd4c*race_combined ccd4c*hiv_risk ccd4c*baseline_cd4 382 ccd4c*agegroup ctimeyr*sex_hars ctimeyr*res_at_hiv_dx 382! ctimeyr*race_combined ctimeyr*hiv_risk 383 ctimeyr*baseline_cd4 ctimeyr*agegroup/ solution outp = 383! pred_un ; 384 random intercept year/ Type= un subject=rfa_id; 385 *random year / type= un subject= rfa_id; 386 lsmeans sex_hars res_at_hiv_dx race_combined hiv_risk 386! baseline_cd4 agegroup /diff; 387 title 'Mixed Model Test for Youth Unstructured'; 388 RUN; NOTE: 7898 observations are not included because of missing values. NOTE: The data set WORK.PRED_UN has 0 observations and 0 variables. WARNING: Data set WORK.PRED_UN was not replaced because new file is incomplete. NOTE: PROCEDURE MIXED used (Total process time): real time 1.21 seconds cpu time 0.92 seconds 389 ods rtf close;   ... View more

Hello,   I added the year to the class statement in the proc mixed model and for year there are 21 levels.    Courtney Jacks ... View more

Hello,   Yes. The log out put is below for that structure.   268 proc sort data = youthavgvl_yr out= youthavgvl_yr_sorted nodupkey; 268! *remove duplicates; 269 by rfa_id year time avgvlyryouth; 270 run; NOTE: There were 57534 observations read from the data set WORK.YOUTHAVGVL_YR. NOTE: 10467 observations with duplicate key values were deleted. NOTE: The data set WORK.YOUTHAVGVL_YR_SORTED has 47067 observations and 19 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.04 seconds cpu time 0.03 seconds 271 *When I ran the procedure without adding intercept or int after 271! random the output showed everything but with it some outputs where 272 cut out; 273 PROC MIXED data= youthavgvl_yr_sorted covtest noitprint method=reml 273! PLOTS(MAXPOINTS=NONE); 274 class sex_hars (ref="F") res_at_hiv_dx (ref="Urban") 274! race_combined (ref="Black") hiv_risk (ref="MSM") baseline_cd4 (ref="> 274! 500") agegroup(ref="20-24"); 275 model avgvlyryouth= year ccd4c ctimeyr sex_hars res_at_hiv_dx 275! race_combined hiv_risk baseline_cd4 276 agegroup ccd4c*sex_hars ccd4c*res_at_hiv_dx 276! ccd4c*race_combined ccd4c*hiv_risk ccd4c*baseline_cd4 277 ccd4c*agegroup ctimeyr*sex_hars ctimeyr*res_at_hiv_dx 277! ctimeyr*race_combined ctimeyr*hiv_risk 278 ctimeyr*baseline_cd4 ctimeyr*agegroup/ solution outp = 278! pred_un ; 279 random intercept year/ Type= un subject=rfa_id; 280 *random year / type= un subject= rfa_id; 281 lsmeans sex_hars res_at_hiv_dx race_combined hiv_risk 281! baseline_cd4 agegroup /diff; 282 title 'Mixed Model Test for Youth Unstructured'; 283 RUN; NOTE: 7898 observations are not included because of missing values. NOTE: The data set WORK.PRED_UN has 0 observations and 0 variables. NOTE: PROCEDURE MIXED used (Total process time): real time 1.21 seconds cpu time 0.88 seconds ... View more

  Hello very close. I am sorry for the confusion.  Model 1 is the TYPE= UN and Model 2 = CS.  For both models I am trying to use the random intercept and time which equal year on my model.  When I use:    random intercept year / subject=rfa_id type=un I do not get any outputs. It seems as if the code stops. For the compound symmetry type (model 2)  I get a result.     ... View more

Thank you so much for you help in advance. I have be trouble shooting this for a couple days. ... View more