About amin1234

amin1234 · ‎11-01-2019

Got it. Thank you!! @MichaelL_SAS

amin1234 · ‎11-01-2019

Thanks @MichaelL_SAS . When I treat the control group as treated, so that there's enough patients to be matched without replacement I still get the same error. However, when I set the caliper to missing (caliper = .) or remove it entirely, it works. Do you know any reason why that is the case?

amin1234 · ‎11-01-2019

Thanks, Reeza. That's just a typo when I was typing the code in the forum.

amin1234 · ‎10-31-2019

Error: A feasible optimal fixed ratio matching that has the specified parameters does not exist. I am trying to do propensity score matching but I keep getting an error saying "A feasible optimal fixed ratio matching that has the specified parameters does not exist". When I change the keyword OPTIMAL to GREEDY everything works fine. Below is my code; PROC PSMATCH DATA = dataset REGION = CS; CLASS drug_group gender age_cat; PS MODEL drug_group(TREATED = 'Medication') = gender age_cat education health_index; MATCH METHOD = OPTIMAL(K=1) EXACT = (gender age_cat) STAT = LPS CALIPER = 0.2; ASSESS LPS VAR = (age_cat education health_index) / WEIGHT = NONE PLOTS =(BOXPLOT BARCHART); OUTPUT OUT(OBS=ALL) = match_data LPS = _lps MATCHID = _matchid; RUN; I have more patients in the 'Medication' group than the control group. I've tried changing the caliper but that didn't help. Any help is appreciated. Thank you!

amin1234 · ‎07-13-2018

@Reeza Thanks for your reply. I don't think it's the indentation. When the SELECTION= option is added to the model statement, the predicted values are not missing which is kind of strange.

amin1234 · ‎07-12-2018

proc logistic data=stat1.safety plots(only)=(effect oddsratio); class region (ref="Asia") size (ref="1")/ param=ref; model unsafe (event="1") = Weight Size Region; store out=issafe; run; data checkSafety; length Region $9.; input Weight Size Region $ 5-13; datalines; 4 1 N America 3 1 Asia 5 3 Asia 5 2 N America ; run; proc plm restore=issafe; score data=checksafety out=safechecked / ilink; run; proc print data=safechecked; run; Hello Everyone, above is my code. I have attached the data set as well. I am getting missing values for the predicted values in the safechecked data set in proc plm. any ideas why the predicted variables are missing?

amin1234 · ‎06-08-2018

Thank you! @ballardw @novinosrin @PaigeMiller

amin1234 · ‎06-08-2018

It's a character variable.

amin1234 · ‎06-08-2018

I created and user defined format but when I run data step to apply format the log reads Format $disf was not found or could not be loaded. I am using SAS University Edition. Engine V9. Below is the full code. Any ideas will be appreciated. libname abc "/folders/myfolders/xyz"; Proc import datafile="/folders/myfolders/xyz/document.xlsx" out=doc1 dbms=xlsx; run; proc format; value disf 0='No' 1='Yes'; run; data doc2; set doc1; format diseased disf.; run;

amin1234 · ‎03-15-2018

Thank you all for your responses and ideas! This is how I finally solved it. -------------------------------------------------------------------------------------- %MACRO domean; %DO I = 1 %TO 100; proc surveyselect data=baseline_followup out=controlmac&i method= srs sampsize=250; run; data controlmac&i; modify controlmac&i; Ycat=0; run; data casecohort&i; set case controlmac&i; run; ods trace on; proc freq data=casecohort&i order=formatted; table xcat*ycat/relrisk; run; ods trace off; ods output RelativeRisks=Output&i; proc freq data=casecohort&i order=formatted; table xcat*ycat/relrisk; run; proc print data=Output&i noobs; run; %END; %MEND domean; %domean data allrelrisk; set output1-output100; run; data onlyodds; set allrelrisk; where studytype not like 'Co%)'; run; proc means mean data=onlyodds; run;

amin1234 · ‎03-08-2018

Thank you @pau13rown for your reply. Yes, I can generate 100 random samples. It combines all of them into one dataset. So i can run a proc freq in addition with a by statement to see the frequencies for each replicate. However, I combine the new 100 random samples with another dataset. Replicate values are missing. and so i do not know how to calculate the odds ratio of that. I will appreciate it if you can post a sample code of any method or ideas.

amin1234 · ‎03-08-2018

I am using proc surveyselect to select a random sample of 250 people from the dataset called baseline_followup. I then modify the new random sample to assign everyone a value of 0 for the Ycat variable. I merge the new dataset i named control2 with existing dataset called case. I then go ahead to find the odds ratio of the variables xcat and ycat. is there a way to run this same code 100 times and find the average odds ratio? because surveyselect will always randomly selected different people. So I want to calculate the 100 different odds ratios and find the average. Any help is appreciated! below is the code proc surveyselect data=baseline_followup out=control2 method= srs sampsize=250; run; data control2; modify control2; Ycat=0; run; data casecontrol2; set case control2; run; proc freq data=casecontrol2 order=formatted; table xcat*ycat/relrisk; run;

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Re: PS Match Optimal Matching

Re: PS Match Optimal Matching

Re: PS Match Optimal Matching

PS Match Optimal Matching

Re: Missing predicted values using proc plm after proc logistic

Missing predicted values using proc plm after proc logistic

Re: Format $[name] was not found or could not be loaded

Re: Format $[name] was not found or could not be loaded

Format $[name] was not found or could not be loaded

Re: running a code multiple times on a random sample

Re: running a code multiple times on a random sample

Re: PS Match Optimal Matching

Re: PS Match Optimal Matching

Re: PS Match Optimal Matching

PS Match Optimal Matching

Re: Missing predicted values using proc plm after proc logistic

Missing predicted values using proc plm after proc logistic

Re: Format $[name] was not found or could not be loaded

Re: Format $[name] was not found or could not be loaded

Format $[name] was not found or could not be loaded

Re: running a code multiple times on a random sample

Re: running a code multiple times on a random sample

running a code multiple times on a random sample