About Wolverine

Wolverine · ‎04-20-2022

Thank you ballardw! Using the code you provided as a guide, I was able to produce almost exactly the output I need. Your explanation about exporting to Excel helped me to better understand the process, and the tip about listing multiple variables in the paired statement is especially helpful given how many comparison I have to run. At this point, there is just 1 remaining issue: the output file is in alphabetical order by variable name, rather than the order that it should be in for the output table. So going back to the sashelp.class data, what if I wanted Age-Weight and the then Age-Height? I created a variable list in the proper order (a portion is shown below). Is there a (relatively) easy way to specify that they should be in the same order as the var list? Ideally, I'd like it to show SVI_high_flag - max_FLAG_PersonalCancerHistory SVI_high_flag - max_FLAG_Dxs_FamCa SVI_low_flag - max_FLAG_PersonalCancerHistory SVI_low_flag - max_FLAG_Dxs_FamCa Etc, in that order. The only idea I have on how to do this is to take the list from the difference column, put it in Excel, and manually sort it into the correct order. Then I would add a column with the correct sort order, import the Excel file, merge it to the "want" data file, and then sort to the correct order. Obviously that would be tedious. Any better solutions? %let SVI_var_list = max_FLAG_PersonalCancerHistory max_FLAG_Dxs_FamCa; PROC TTEST plots=none data=temp.SVI_hyst_output_SAS_dum; paired SVI_high_flag * (&SVI_var_list.) SVI_low_flag * (&SVI_var_list.) SVI_SES_high_flag * (&SVI_var_list.) SVI_SES_low_flag * (&SVI_var_list.) SVI_HHcomp_high_flag * (&SVI_var_list.) SVI_HHcomp_low_flag * (&SVI_var_list.); RUN;

Wolverine · ‎04-18-2022

That populates the Excel file, but it creates 3 separate tabs for each pair of variables (statistics, confidence intervals, and t-tests). I'd really just like 1 tab with about 45 lines, each with the 5 columns I indicated above.

Wolverine · ‎04-18-2022

I have a series of about 45 t-tests I'm trying to run (I've only shown 2 here). All I really need is the mean, 95% confidence intervals, and p-value for each. I'd like to export them to an Excel file with the pair name in Column A, the mean in B, 95% confidence intervals in C and D, and p-value in E. This is what I have so far, but the SAS output still has more information than I need, and it results in a blank Excel file. ods graphics on; title1 "T-tests"; PROC TTEST plots=none data=temp.SVI_hyst_output_SAS_dum; paired age_cat1_lt40*SVI_high_flag age_cat1_lt40*SVI_low_flag; RUN; ODS Excel file="Z:\Programming and analysis\ttest_v&version. RAW.xlsx" OPTIONS(embedded_titles="YES" embedded_footnotes="YES" start_at="1,2" frozen_headers="YES" ); TITLE1 "Ttest TEST V(&version.)"; TITLE2 "&sysdate."; RUN; ODS Excel close; ods graphics off;

Wolverine · ‎03-30-2022

I'm working with medical administrative data, and I'm trying to flag patients who have had certain diagnoses or medical procedures. I've tried searching online and I've come across variations of do-loops or arrays, but I haven't been able to figure out how to apply them to my specific data. So far I've been using a data step and listing each variable. This works, but obviously it's unwieldy and not a good long-term solution. I've only shown 2 lists here, but the final version will have about 20. Also note that some of the codes are stems, so that O03 includes O031, O032, O035, etc. That's why I used "in:". %let EPL_list = ("O021","O03"); %let excl_list_pm70154d = ("59820","59812","59821","0UDB"); DATA temp.Index_cases; SET comb.med_comm_2018_2021; IF PRINCIPAL_DIAGNOSIS_CODE in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_1 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_2 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_3 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_4 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_5 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_6 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_7 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_8 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_9 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_10 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_11 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_12 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_13 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_14 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_15 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_16 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_17 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_18 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_19 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_20 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_21 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_22 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_23 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_24 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_25 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_26 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_27 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_28 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_29 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_30 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_31 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_32 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_33 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_34 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_35 in: (&EPL_list.) THEN EPL_flag = 1; ELSE IF DIAGNOSIS_CODE_36 in: (&EPL_list.) THEN EPL_flag = 1; ELSE EPL_flag = 0; IF PROCEDURE_CODE in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_1 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_2 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_3 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_4 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_5 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_6 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_7 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_8 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_9 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_10 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_11 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_12 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_13 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_14 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_15 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_16 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_17 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_18 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_19 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_20 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_21 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_22 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_23 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_24 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE IF ICD_PROCEDURE_CODE_25 in: (&excl_list_pm70154d.) THEN excl_list_pm70154d = 1; ELSE excl_list_pm70154d = 0; RUN;

Wolverine · ‎11-16-2021

It doesn't look like the Base library is there anymore: proc options option=fmtsearch; run; SAS (r) Proprietary Software Release 9.4 TS1M6 FMTSEARCH=(WORK LIBRARY) Specifies the order in which format catalogs are searched. NOTE: PROCEDURE OPTIONS used (Total process time): real time 0.03 seconds cpu time 0.01 seconds But when I tried to use the code you suggested to add it back in, I got an error. I tried it another way, but that didn't work either. 194 options append(fmtsearch=base); ---------------------- 13 ERROR 13-12: Unrecognized SAS option name APPEND(FMTSEARCH=BASE). 195 proc options append(fmtsearch=base); ------ 22 76 ERROR 22-322: Syntax error, expecting one of the following: ;, ADB, APF, DB2, DDB, DEFINE, EXPAND, GETRESTRICT, GROUP, HELP, HEXVALUE, HOST, IDM, IMS, ISP, LISTGROUPS, LISTINSERTAPPEND, LISTOPTSAVE, LISTRESTRICT, LOGNUMBERFORMAT, LONG, NOEXPAND, NOLOGNUMBERFORMAT, OPTION, PORTABLE, PWDBLOTOFF, RESTRICT, SHORT, SHOWCHAINS, VALUE. ERROR 76-322: Syntax error, statement will be ignored. 196 run;

Wolverine · ‎11-16-2021

I've been developing a piece of syntax for a week or so, and the formatting has been working fine. Today, I'm suddenly getting errors such as: "ERROR: The format FMT_1_43F was not found or could not be loaded." The formats file is in the "base" directory, and according to the log, is being loaded correctly: LIBNAME base "Z:\Data sources\MVC Analytic Table Data 10.14.21"; NOTE: Libref BASE was successfully assigned as follows: Engine: V9 Physical Name: Z:\Data sources\MVC Analytic Table Data 10.14.21 proc format library=base.formats; run; NOTE: PROCEDURE FORMAT used (Total process time): real time 0.05 seconds cpu time 0.03 seconds I opened the formats file and all of the individual formats appear to be set up correctly, so I don't think the file has been corrupted. This seems more like a software glitch, so I shut down SAS and restarted it, but that didn't make any difference. I would also like to reboot the computer, but I'm remotely logged into a virtual machine so I don't have the ability to do that.

Wolverine · ‎11-05-2021

In the syntax above, "HEDIS_DX_code" should have been changed to "Code".

Wolverine · ‎11-05-2021

I'm working with medical claims data. For each healthcare encounter, up to 25 different diagnosis codes can be present. There are about 30 different health conditions that I need to flag where ever they show up within the data (it doesn't matter which of the 25 diagnosis variables it matches). Each health condition has several (usually 3-7) different diagnosis codes. The list of health condition codes were given to me in an Excel file with a separate tab for each health condition of interest. I then imported each of those tabs as a separate SAS file. In the example file below, I only added 5 diagnosis variables and 2 health conditions for the sake of clarity. The initial data file doesn't have the flag variables, and the output file should have the flag variables. HEALTHCARE_ENCOUNTER_ID icd_dx1 icd_dx2 icd_dx3 icd_dx4 icd_dx5 CANCER_FLAG PREGNANCY_FLAG 12345 9993 2255 3366 4477 5588 1 0 23456 2358 5899 8881 7777 8850 0 1 34567 8546 5468 4811 8883 9991 1 1 45678 8326 . . . . 0 0 CODE DESCRIPTION 9991 Cervical cancer 9992 Pelvic cancer 9993 Breast cancer CODE DESCRIPTION 8881 Normal pregnancy 8882 Atopic pregnancy 8883 Preclampsia I haven't gotten very far with my syntax. What I have so far attempts to compare the range of diagnosis codes against the list of codes for each condition. This is within a macro (where &sheet. represents the condition name), so it will create a separate file for each condition, and then I will have to merge all the files together (along with all healthcare episodes that didn't match on any of the conditions). It's clunky and I'm not sure if a range will work in a Proc SQL step: PROC SQL; Create table temp.flag_&sheet. as Select * From temp.healthcare_encounters WHERE icd_dx1-25 in (select HEDIS_DX_code from temp.Hyst_Codes_&sheet.); QUIT;

Wolverine · ‎02-16-2021

The zip code is a 5-digit numeric number. And yes, the file has 1 record per person. So when I say only the first record has zip codes, I mean that zip codes appear for only the very first person in the file. For everyone else, the zip code variables are blank.

Wolverine · ‎02-15-2021

They've finalized the layout, and it's really not much different than before. So I ran this code and it's very close to what I need. The only problem is that the zip code variables are only populated for the first record. They are blank for everyone else. Hopefully it's an easy fix! /* Section 1.1 -- Preferentially select records with full middle name, then initial, then blank. LENGTH returns a value of 1 for blank, whereas LENGHTN returns a value of 0.*/ DATA temp.MIDBall_Medicaid_linked_servdate; SET temp.MIDBall_Medicaid_linked_servdate; /* If there were multiple middle names, it would not be possible to determine if MNRank=1,2,3, so the value of lengthn was used as the sort key. */ MNRank=LENGTHN(MIDDLE_NAME); RUN; /* Section 1.2 -- Sort on appropriate variables. */ PROC SORT data=temp.MIDBall_Medicaid_linked_servdate out=temp.MIDB_Medicaid_servdatedd_srt; BY SSN descending MNRank; RUN; /* BASE DATASET:END */ /* AFTER Section 1.2 */ /* ZIP DATASET:START */ proc sort data=temp.MIDBall_Medicaid_linked_servdate out=tmp1(keep=ssn hsys_MRN_ID MIDBZip); by ssn hsys_MRN_ID MIDBZip; run; data tmp2; set tmp1; length suffix $2; by ssn hsys_MRN_ID; if first.hsys_MRN_ID then do; cntABC=0; cntNUM+1; end; cntABC+1; suffix=cats(cntNUM,byte(64+cntABC)); run; proc transpose data=tmp2 out=zip(keep=ssn MIDBZip_:) prefix=MIDBZip_; var MIDBZip; by ssn; ID suffix; run; /* ZIP DATASET:END */ /* PERSONALINFO DATASET:START */ data tmp3(drop=middlename MIDBZip cnt); set temp.MIDB_Medicaid_servdatedd_srt; retain middlename; by ssn descending MNRank; if first.ssn then do middlename=MIDDLE_NAME; cnt=1; end; else do; cnt+1; end; MIDDLE_NAME=middlename;/* To overwrite with a long middle name */ run; proc sort data=tmp3 out=personal(keep=FIRST_NAME--ssn) force nodupkey; by ssn; run; /* PERSONALINFO DATASET:END */ /* TRANSPOSE BY VARIABLES:START */ proc sort data=temp.MIDB_Medicaid_linked_servdatedd out=trn(keep=SSN health_sys MRN hsys_MRN_ID); by ssn; run; proc sort data=trn force nodup; by ssn; run; proc transpose data=trn out=trn_hsys(keep=ssn health_sys_:) prefix=health_sys_; var health_sys; by ssn; run; proc transpose data=trn out=trn_mrn(keep=ssn mrn_:) prefix=mrn_; var mrn; by ssn; run; proc transpose data=trn out=trn_mrnid(keep=ssn hsys_MRN_ID_:) prefix=hsys_MRN_ID_; var hsys_MRN_ID; by ssn; run; /* TRANSPOSE:END */ /* MERGE ALL */ data temp.transposed; merge personal trn_: Zip; by ssn; run;

Wolverine · ‎02-12-2021

Thank you for updating the syntax. But before we go any further, I should let you know that they asked me to stop working on this temporarily, as there may be more changes to the layout🙄 We're collaborating with multiple agencies, so it's hard to figure out a layout that will work for everyone. But I did run your code, and I got this error message: 141 /* TRANSPOSE BY VARIABLES:START */ 142 proc sort data=temp.MIDB_Medicaid_linked_servdatedd(keep=ssn--hsys_MRN_ID) out=trn; ERROR: Starting variable ssn of double-dash list has been defined after the ending variable hsys_MRN_ID. 143 by ssn; 144 run;

Wolverine · ‎02-10-2021

Just to give some background info, I'm passing the final dataset onto another group of researchers after I'm done with my part of the process. Unfortunately, they have made a change about how they want the output file to look. They now want to retaining the link between zip and health system. And since there may be multiple zip codes per health system, even if there are repeats. I've renamed them 1A, 1B, 2A, 2B, etc: BENEFICIARY_ID FIRST_NAME MIDDLE_NAME LAST_NAME Sex DOB SSN health_sys_1 MRN_1 hsys_MRN_ID_1 health_sys_2 MRN_2 hsys_MRN_ID_2 health_sys_3 MRN_3 hsys_MRN_ID_3 MIDBZip_1A MIDBZip_1B MIDBZip_2A MIDBZip_2B 12345678 John Q Public M 1/1/2010 987654321 Mercy 2222222 Mercy_2222222 Saint 333333 Saint_333333 34567 34577 34568 34577 Also, there is at least one example I found where a person has a middle initial in one record and a full middle name in another. So I created a ranking system for that. I've never actually used PROC TRANSPOSE before, and this seems like a very complicated data file to start with! Between that and the changes I mentioned above, I'm having a hard time trying to figure out how to modify the code you posted accordingly. Below is what I have so far, and when I run it, I get notes in the log like this: "NOTE: Invalid numeric data, MIDDLE_NAME='H' , at line 119 column 20". In other words, SAS seems to think that MIDDLE_NAME should be numeric but of course it's finding text instead (in this case, a person with the middle initial H). /* Section 1.1 -- Preferentially select records with full middle name, then initial, then blank. LENGTH returns a value of 1 for blank, whereas LENGHTN returns a value of 0.*/ DATA temp.MIDB_Medicaid_linked_servdatedd; SET temp.MIDB_Medicaid_linked_servdatedd; IF LENGTHN(MIDDLE_NAME) > 1 THEN MNRank = 1; IF LENGTHN(MIDDLE_NAME) = 1 THEN MNRank = 2; IF LENGTHN(MIDDLE_NAME) = 0 THEN MNRank = 3; RUN; /* Section 1.2 -- Sort on appropriate variables. */ PROC SORT data=temp.MIDB_Medicaid_linked_servdatedd out=temp.MIDB_Medicaid_servdatedd_srt; BY SSN descending MNRank; RUN; /* Section 1.3 -- PERSONALINFO DATASET:START */ DATA temp.tmp3(drop=MIDDLE_NAME MIDBzip cnt); SET temp.MIDB_Medicaid_servdatedd_srt; RETAIN MIDDLE_NAME MIDBzip; BY SSN descending MNRank; if first.SSN then do MIDDLE_NAME=mn; cnt=1; end; else do; cnt+1; end; if mn='' then mn=MIDDLE_NAME; RUN;

Wolverine · ‎02-08-2021

This is what I have: FIRST_NAME MIDDLE_NAME LAST_NAME Sex DOB SSN health_sys MRN hsys_MRN_ID MIDBZip John Q Public M 1/1/2010 987654321 Mercy 2222222 Mercy_2222222 34567 John Q Public M 1/1/2010 987654321 Mercy 2222222 Mercy_2222222 34577 John Public M 1/1/2010 987654321 Saint 333333 Saint_333333 34568 John Public M 1/1/2010 987654321 Saint 333333 Saint_333333 34577 And this is what I want: FIRST_NAME MIDDLE_NAME LAST_NAME Sex DOB SSN health_sys_1 MRN_1 hsys_MRN_ID_1 health_sys_2 MRN_2 hsys_MRN_ID_2 health_sys_3 MRN_3 hsys_MRN_ID_3 MIDBZip_A MIDBZip_B MIDBZip_C John Q Public M 1/1/2010 987654321 Mercy 2222222 Mercy_2222222 Saint 333333 Saint_333333 34567 34577 34568 Note that the zip code variables are A, B, C rather than 1, 2, 3 because I just need to know that the person was at that zip code at some point -- it doesn't have to be linked to a particular health system. In fact, zip code 34577 shows up for both health systems, but it should only appear once in the output record. Also note that I want to retain Middle Name, but sometimes it's blank. So I want to preferentially select it from records where it's present.

Wolverine · ‎11-20-2020

I accepted FreelanceReinhard's solution because it's simple and easy to apply, and it serves my purposes quite well for this particular data. But I will make a note of Reeza's macro, as I anticipate it could be useful in the future for larger/more complex datasets. Thanks!

Wolverine · ‎11-19-2020

This seems like it should be quite easy to do, but I haven't found a way yet. I have a large file (millions of records) with names, dates of birth, addresses, etc, and I want to know the missing/non-missing percentages for each of these variables. I don't want to run proc freq, as this will give me a huge list of every name in the dataset. My work-around so far has been to recode these types of variables into dichotomous variables (ie, 0=missing and 1=non-missing), and then run freqs. But that's time consuming and tedious. Isn't there an option in proc freq or another procedure to do this automatically?

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