topic Cluster analysis with character data in SAS Procedures

Cluster analysis with character data

dwhitney — Wed, 18 Dec 2019 15:58:57 GMT

I have a dataset with over 4M individuals categorized into 2 groups: CP1=0 and CP1=1. The data is the in the wide format (each row is a single individual). Each row (person) has anywhere from 0 to 80 medications; the variable name is Gnrc_Nm1 to Gnrc_Nm80, and the data for these variables are the "distinct" drug name in character format.

I would like to do 2 things in order:

First, I would like to identify the number of individuals per group (CP1) that has each of the distinct drug names. I imagine I would have to do some procedure that looks across Gnrc_Nm1 to Gnrc_Nm80 per person and then summarizes per group for each drug name. Each person has a distinct drug name, so no worries about duplicates per person (i.e., if someone had FLUOCINONIDE 3x, they will only have it once in Gnrc_Nmx). How would you recommend I go about this?

Second, I would like to do a cluster analysis to identify the top 10 most common clusters for each group. I cannot figure out how to do this with the data in the wide format, the variables Gnrc_Nm1 to Gnrc_Nm80, and the data for these variables as character. Any idea on how to go about this?

Below is an example of the data using proc print:

Obs Patid CP1 _LABEL_ Gnrc_Nm1 Gnrc_Nm2 Gnrc_Nm3 Gnrc_Nm4 Gnrc_Nm5 Gnrc_Nm6 Gnrc_Nm7 Gnrc_Nm8 Gnrc_Nm9 Gnrc_Nm10 Gnrc_Nm11 Gnrc_Nm12 Gnrc_Nm13 Gnrc_Nm14 Gnrc_Nm15 Gnrc_Nm16 Gnrc_Nm17 Gnrc_Nm18 Gnrc_Nm19 Gnrc_Nm20 Gnrc_Nm21 Gnrc_Nm22 Gnrc_Nm23 Gnrc_Nm24 Gnrc_Nm25 Gnrc_Nm26 Gnrc_Nm27 Gnrc_Nm28 Gnrc_Nm29 Gnrc_Nm30 Gnrc_Nm31 Gnrc_Nm32 Gnrc_Nm33 Gnrc_Nm34 Gnrc_Nm35 Gnrc_Nm36 Gnrc_Nm37 Gnrc_Nm38 Gnrc_Nm39 Gnrc_Nm40 Gnrc_Nm41 Gnrc_Nm42 Gnrc_Nm43 Gnrc_Nm44 Gnrc_Nm45 Gnrc_Nm46 Gnrc_Nm47 Gnrc_Nm48 Gnrc_Nm49 Gnrc_Nm50 Gnrc_Nm51 Gnrc_Nm52 Gnrc_Nm53 Gnrc_Nm54 Gnrc_Nm55 Gnrc_Nm56 Gnrc_Nm57 Gnrc_Nm58 Gnrc_Nm59 Gnrc_Nm60 Gnrc_Nm61 Gnrc_Nm62 Gnrc_Nm63 Gnrc_Nm64 Gnrc_Nm65 Gnrc_Nm66 Gnrc_Nm67 Gnrc_Nm68 Gnrc_Nm69 Gnrc_Nm70 Gnrc_Nm71 Gnrc_Nm72 Gnrc_Nm73 Gnrc_Nm74 Gnrc_Nm75 Gnrc_Nm76 Gnrc_Nm77 Gnrc_Nm78 Gnrc_Nm79 Gnrc_Nm80 FUdate CP1 CP2 ID1 ID2 ASD1 ASD2 Epil1 Epil2 Yrdob sex Race USreg YRsd age12345678

1	0	Generic Name	FLUOCINONIDE	OMEPRAZOLE																							2016-01-01	0	0	0	0	0	0	0	0	1960	F	W	1	2016	56
2	0	Generic Name	HYDROCORTISONE																								2016-12-31	0	0	0	0	0	0	0	0	1957	M	W	2	2016	59
3	1	Generic Name	AMOXICILLIN/POTASSIUM CLAV	LEVOTHYROXINE SODIUM																							2015-01-01	0	0	0	0	0	0	0	0	1957	F	H	1	2015	58
4	0	Generic Name	ALBUTEROL SULFATE	ALENDRONATE SODIUM	AMLODIPINE/VALSARTAN	AMOXICILLIN	ATENOLOL	ATORVASTATIN CALCIUM	CITALOPRAM HYDROBROMIDE	CLOPIDOGREL BISULFATE	FENOFIBRATE NANOCRYSTALLIZED	FENOFIBRIC ACID (CHOLINE)	FLUTICASONE PROPIONATE	FLUTICASONE/SALMETEROL	FUROSEMIDE	GABAPENTIN	GLIPIZIDE	LORAZEPAM	MONTELUKAST SODIUM	NEO/POLYMYX B SULF/DEXAMETH	NIFEDIPINE	PANTOPRAZOLE SODIUM	PENTOXIFYLLINE	ROFLUMILAST	TIOTROPIUM BROMIDE	ZOSTER VACCINE LIVE/PF	2014-01-01	0	0	0	0	0	0	0	0	1938	F	W	1	2014	76
5	1	Generic Name	AMOXICILLIN/POTASSIUM CLAV	TOBRAMYCIN																							2015-05-01	0	0	0	0	0	0	0	0	1969	M	U	3	2015	46
6	1	Generic Name	BROMFENAC SODIUM	CIPROFLOXACIN HCL	LATANOPROST	TIMOLOL MALEATE	TRIAMCINOLONE ACETONIDE																				2014-01-01	0	0	0	0	0	0	0	0	1928	M	H	1	2014	86
7	0	Generic Name	AZITHROMYCIN																								2016-11-30	0	0	0	0	0	0	0	0	1978	F	H	3	2016	38
8	0	Generic Name	ADAPALENE/BENZOYL PEROXIDE	CLINDAMYCIN PHOSPHATE	DEXTROAMPHETAMINE/AMPHETAMINE	L-NORGEST-ETH ESTR/ETHIN ESTRA																					2015-07-01	0	0	0	0	0	0	0	0	1985	F	W	4	2015	30

Re: Cluster analysis with character data

PaigeMiller — Wed, 18 Dec 2019 16:08:50 GMT

Please provide a portion of your data according to these instructions:

https://communities.sas.com/t5/SAS-Communities-Library/How-to-create-a-data-step-version-of-your-data-AKA-generate/ta-p/258712

Re: Cluster analysis with character data

dwhitney — Wed, 18 Dec 2019 16:25:59 GMT

Here is a copy and paste after following the first set of instructions from the link you sent.

data WORK.PHARM1117_PMDESCRIPTIVES1;
  infile datalines dsd truncover;

input Patid:19. _NAME_:$8. _LABEL_:$40. Gnrc_Nm1:$50. Gnrc_Nm2:$50. Gnrc_Nm3:$50. Gnrc_Nm4:$50. Gnrc_Nm5:$50. Gnrc_Nm6:$50. Gnrc_Nm7:$50. Gnrc_Nm8:$50. Gnrc_Nm9:$50. Gnrc_Nm10:$50. Gnrc_Nm11:$50. Gnrc_Nm12:$50. Gnrc_Nm13:$50. Gnrc_Nm14:$50. Gnrc_Nm15:$50.
Gnrc_Nm16:$50. Gnrc_Nm17:$50. Gnrc_Nm18:$50. Gnrc_Nm19:$50. Gnrc_Nm20:$50. Gnrc_Nm21:$50. Gnrc_Nm22:$50. Gnrc_Nm23:$50. Gnrc_Nm24:$50. Gnrc_Nm25:$50. Gnrc_Nm26:$50. Gnrc_Nm27:$50. Gnrc_Nm28:$50. Gnrc_Nm29:$50. Gnrc_Nm30:$50. Gnrc_Nm31:$50. Gnrc_Nm32:$50. G
nrc_Nm33:$50. Gnrc_Nm34:$50. Gnrc_Nm35:$50. Gnrc_Nm36:$50. Gnrc_Nm37:$50. Gnrc_Nm38:$50. Gnrc_Nm39:$50. Gnrc_Nm40:$50. Gnrc_Nm41:$50. Gnrc_Nm42:$50. Gnrc_Nm43:$50. Gnrc_Nm44:$50. Gnrc_Nm45:$50. Gnrc_Nm46:$50. Gnrc_Nm47:$50. Gnrc_Nm48:$50. Gnrc_Nm49:$50. Gn
rc_Nm50:$50. Gnrc_Nm51:$50. Gnrc_Nm52:$50. Gnrc_Nm53:$50. Gnrc_Nm54:$50. Gnrc_Nm55:$50. Gnrc_Nm56:$50. Gnrc_Nm57:$50. Gnrc_Nm58:$50. Gnrc_Nm59:$50. Gnrc_Nm60:$50. Gnrc_Nm61:$50. Gnrc_Nm62:$50. Gnrc_Nm63:$50. Gnrc_Nm64:$50. Gnrc_Nm65:$50. Gnrc_Nm66:$50. Gnr
c_Nm67:$50. Gnrc_Nm68:$50. Gnrc_Nm69:$50. Gnrc_Nm70:$50. Gnrc_Nm71:$50. Gnrc_Nm72:$50. Gnrc_Nm73:$50. Gnrc_Nm74:$50. Gnrc_Nm75:$50. Gnrc_Nm76:$50. Gnrc_Nm77:$50. Gnrc_Nm78:$50. Gnrc_Nm79:$50. Gnrc_Nm80:$50. FUdate:YYMMDD10. CP1:32. CP2:32. ID1:32. ID2:32.
ASD1:32. ASD2:32. Epil1:32. Epil2:32. Yrdob:5. sex:$1. Race:$1. USreg:32. YRsd:32. age:32.;
  format Patid 19. FUdate YYMMDD10. Yrdob 5.;
  label Patid="Patient Id" _NAME_="NAME OF FORMER VARIABLE" _LABEL_="LABEL OF FORMER VARIABLE" Yrdob="Year of Birth" sex="Gender Code" Race="Race Code";
datalines;
33003282022 Gnrc_Nm Generic Name FLUOCINONIDE OMEPRAZOLE                                                                                                                                                             2016-01-01 0 0 0 0 0 0 0 0 1960 F W 1 2016
56
33003282023 Gnrc_Nm Generic Name HYDROCORTISONE                                                                                                                                                               2016-12-31 0 0 0 0 0 0 0 0 1957 M W 2 2016 59
33003282043 Gnrc_Nm Generic Name AMOXICILLIN/POTASSIUM CLAV LEVOTHYROXINE SODIUM                                                                                                                                                             2015-01-01 0 0 0 0
0 0 0 0 1957 F H 1 2015 58
33003282049 Gnrc_Nm Generic Name ALBUTEROL SULFATE ALENDRONATE SODIUM AMLODIPINE/VALSARTAN AMOXICILLIN ATENOLOL ATORVASTATIN CALCIUM CITALOPRAM HYDROBROMIDE CLOPIDOGREL BISULFATE FENOFIBRATE NANOCRYSTALLIZED FENOFIBRIC ACID (CHOLINE) FLUTICASONE PROPIONATE
FLUTICASONE/SALMETEROL FUROSEMIDE GABAPENTIN GLIPIZIDE LORAZEPAM MONTELUKAST SODIUM NEO/POLYMYX B SULF/DEXAMETH NIFEDIPINE PANTOPRAZOLE SODIUM PENTOXIFYLLINE ROFLUMILAST TIOTROPIUM BROMIDE ZOSTER VACCINE LIVE/PF
                                                                    2014-01-01 0 0 0 0 0 0 0 0 1938 F W 1 2014 76
33003282054 Gnrc_Nm Generic Name AMOXICILLIN/POTASSIUM CLAV TOBRAMYCIN                                                                                                                                                             2015-05-01 0 0 0 0 0 0 0 0
1969 M U 3 2015 46
33003282072 Gnrc_Nm Generic Name BROMFENAC SODIUM CIPROFLOXACIN HCL LATANOPROST TIMOLOL MALEATE TRIAMCINOLONE ACETONIDE
              2014-01-01 0 0 0 0 0 0 0 0 1928 M H 1 2014 86
33003282074 Gnrc_Nm Generic Name AZITHROMYCIN                                                                                                                                                               2016-11-30 0 0 0 0 0 0 0 0 1978 F H 3 2016 38
33003282079 Gnrc_Nm Generic Name ADAPALENE/BENZOYL PEROXIDE CLINDAMYCIN PHOSPHATE DEXTROAMPHETAMINE/AMPHETAMINE L-NORGEST-ETH ESTR/ETHIN ESTRA
                                      2015-07-01 0 0 0 0 0 0 0 0 1985 F W 4 2015 30
33003282082 Gnrc_Nm Generic Name SIMVASTATIN                                                                                                                                                               2014-01-01 0 0 0 0 0 0 0 0 1949 F W 2 2014 65
33003282095 Gnrc_Nm Generic Name AMOXICILLIN AMPICILLIN TRIHYDRATE DICLOFENAC SODIUM METFORMIN HCL METOPROLOL TARTRATE OFLOXACIN PREDNISOLONE ACETATE
                                        2014-01-01 0 0 0 0 0 0 0 0 1930 F W 2 2014 84
;;;;
NOTE: There were 10 observations read from the data set WOR.PHARM1117_PMDESCRIPTIVES1.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds

Re: Cluster analysis with character data

ballardw — Wed, 18 Dec 2019 22:21:07 GMT

Please double check whether the source of the code actually wraps lines in the middle of the datalines. I might suggest pasting the code into a box opened with {I} instead of the running man icon as that may be setting line length limit that is causing the data step to have invalid data in many places.

Another option would be to consider only using 10 of the Gnrc_nm varaibles. If the FUdate CP1 CP2 ID1 ID2

ASD1 ASD2 Epil1 Epil2 Yrdob sex Race USreg YRsd age are not needed for the cluster definitions drop them.

data export;

set yourdata (keep = Patid Gnrc_nm1 - Gncrc_nm10);

run;

for example and turn that into the data step. The method for determining clusters for 10 variables would be the same just different results.

Re: Cluster analysis with character data

dwhitney — Wed, 18 Dec 2019 22:17:36 GMT

The data do not wrap around like this in SAS. It must be a copy and paste issue.

Below I copied and pasted using the {i} function as suggested. I also attached the same code in Word format that seems to be a little bit more organized.

Let me know if this helps. Thank you for your time!

data WORK.PHARM1117_PMDESCRIPTIVES1;
  infile datalines dsd truncover;

input Patid:19. _NAME_:$8. _LABEL_:$40. Gnrc_Nm1:$50. Gnrc_Nm2:$50. Gnrc_Nm3:$50. Gnrc_Nm4:$50. Gnrc_Nm5:$50. Gnrc_Nm6:$50. Gnrc_Nm7:$50. Gnrc_Nm8:$50. Gnrc_Nm9:$50. Gnrc_Nm10:$50. Gnrc_Nm11:$50. Gnrc_Nm12:$50. Gnrc_Nm13:$50. Gnrc_Nm14:$50. Gnrc_Nm15:$50.
Gnrc_Nm16:$50. Gnrc_Nm17:$50. Gnrc_Nm18:$50. Gnrc_Nm19:$50. Gnrc_Nm20:$50. Gnrc_Nm21:$50. Gnrc_Nm22:$50. Gnrc_Nm23:$50. Gnrc_Nm24:$50. Gnrc_Nm25:$50. Gnrc_Nm26:$50. Gnrc_Nm27:$50. Gnrc_Nm28:$50. Gnrc_Nm29:$50. Gnrc_Nm30:$50. Gnrc_Nm31:$50. Gnrc_Nm32:$50. G
nrc_Nm33:$50. Gnrc_Nm34:$50. Gnrc_Nm35:$50. Gnrc_Nm36:$50. Gnrc_Nm37:$50. Gnrc_Nm38:$50. Gnrc_Nm39:$50. Gnrc_Nm40:$50. Gnrc_Nm41:$50. Gnrc_Nm42:$50. Gnrc_Nm43:$50. Gnrc_Nm44:$50. Gnrc_Nm45:$50. Gnrc_Nm46:$50. Gnrc_Nm47:$50. Gnrc_Nm48:$50. Gnrc_Nm49:$50. Gn
rc_Nm50:$50. Gnrc_Nm51:$50. Gnrc_Nm52:$50. Gnrc_Nm53:$50. Gnrc_Nm54:$50. Gnrc_Nm55:$50. Gnrc_Nm56:$50. Gnrc_Nm57:$50. Gnrc_Nm58:$50. Gnrc_Nm59:$50. Gnrc_Nm60:$50. Gnrc_Nm61:$50. Gnrc_Nm62:$50. Gnrc_Nm63:$50. Gnrc_Nm64:$50. Gnrc_Nm65:$50. Gnrc_Nm66:$50. Gnr
c_Nm67:$50. Gnrc_Nm68:$50. Gnrc_Nm69:$50. Gnrc_Nm70:$50. Gnrc_Nm71:$50. Gnrc_Nm72:$50. Gnrc_Nm73:$50. Gnrc_Nm74:$50. Gnrc_Nm75:$50. Gnrc_Nm76:$50. Gnrc_Nm77:$50. Gnrc_Nm78:$50. Gnrc_Nm79:$50. Gnrc_Nm80:$50. FUdate:YYMMDD10. CP1:32. CP2:32. ID1:32. ID2:32.
ASD1:32. ASD2:32. Epil1:32. Epil2:32. Yrdob:5. sex:$1. Race:$1. USreg:32. YRsd:32. age:32.;
  format Patid 19. FUdate YYMMDD10. Yrdob 5.;
  label Patid="Patient Id" _NAME_="NAME OF FORMER VARIABLE" _LABEL_="LABEL OF FORMER VARIABLE" Yrdob="Year of Birth" sex="Gender Code" Race="Race Code";
datalines;
33003282022 Gnrc_Nm Generic Name FLUOCINONIDE OMEPRAZOLE                                                                                                                                                             2016-01-01 0 0 0 0 0 0 0 0 1960 F W 1 2016
56
33003282023 Gnrc_Nm Generic Name HYDROCORTISONE                                                                                                                                                               2016-12-31 0 0 0 0 0 0 0 0 1957 M W 2 2016 59
33003282043 Gnrc_Nm Generic Name AMOXICILLIN/POTASSIUM CLAV LEVOTHYROXINE SODIUM                                                                                                                                                             2015-01-01 0 0 0 0
0 0 0 0 1957 F H 1 2015 58
33003282049 Gnrc_Nm Generic Name ALBUTEROL SULFATE ALENDRONATE SODIUM AMLODIPINE/VALSARTAN AMOXICILLIN ATENOLOL ATORVASTATIN CALCIUM CITALOPRAM HYDROBROMIDE CLOPIDOGREL BISULFATE FENOFIBRATE NANOCRYSTALLIZED FENOFIBRIC ACID (CHOLINE) FLUTICASONE PROPIONATE
FLUTICASONE/SALMETEROL FUROSEMIDE GABAPENTIN GLIPIZIDE LORAZEPAM MONTELUKAST SODIUM NEO/POLYMYX B SULF/DEXAMETH NIFEDIPINE PANTOPRAZOLE SODIUM PENTOXIFYLLINE ROFLUMILAST TIOTROPIUM BROMIDE ZOSTER VACCINE LIVE/PF
                                                                    2014-01-01 0 0 0 0 0 0 0 0 1938 F W 1 2014 76
33003282054 Gnrc_Nm Generic Name AMOXICILLIN/POTASSIUM CLAV TOBRAMYCIN                                                                                                                                                             2015-05-01 0 0 0 0 0 0 0 0
1969 M U 3 2015 46
33003282072 Gnrc_Nm Generic Name BROMFENAC SODIUM CIPROFLOXACIN HCL LATANOPROST TIMOLOL MALEATE TRIAMCINOLONE ACETONIDE
              2014-01-01 0 0 0 0 0 0 0 0 1928 M H 1 2014 86
33003282074 Gnrc_Nm Generic Name AZITHROMYCIN                                                                                                                                                               2016-11-30 0 0 0 0 0 0 0 0 1978 F H 3 2016 38
33003282079 Gnrc_Nm Generic Name ADAPALENE/BENZOYL PEROXIDE CLINDAMYCIN PHOSPHATE DEXTROAMPHETAMINE/AMPHETAMINE L-NORGEST-ETH ESTR/ETHIN ESTRA
                                      2015-07-01 0 0 0 0 0 0 0 0 1985 F W 4 2015 30
33003282082 Gnrc_Nm Generic Name SIMVASTATIN                                                                                                                                                               2014-01-01 0 0 0 0 0 0 0 0 1949 F W 2 2014 65
33003282095 Gnrc_Nm Generic Name AMOXICILLIN AMPICILLIN TRIHYDRATE DICLOFENAC SODIUM METFORMIN HCL METOPROLOL TARTRATE OFLOXACIN PREDNISOLONE ACETATE
                                        2014-01-01 0 0 0 0 0 0 0 0 1930 F W 2 2014 84
;;;;
NOTE: There were 10 observations read from the data set WOR.PHARM1117_PMDESCRIPTIVES1.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds

Re: Cluster analysis with character data

Ksharp — Thu, 19 Dec 2019 12:11:53 GMT

You could try COSINE to measure the similarity between two string , and build a recommendation system via it.

@Rick_SAS wrote a blog about it to measure the similarity between recipes .

Re: Cluster analysis with character data

dwhitney — Thu, 19 Dec 2019 13:48:06 GMT

Thank you for the suggestion. I am working on it now.

Looking back at my original post, I think I may have been misleading. I used the term "cluster" but I do not mean that I want to do PROC CLUSTER analysis. I would like to do principal component analysis to identify groups ("clusters") of medications common to CP1=0 and CP1=1.

I don't know if this changes how people may provide direction.

Sorry for the mix up.

Re: Cluster analysis with character data

Ksharp — Fri, 20 Dec 2019 11:31:21 GMT

PCA also need X variables which have numeric value,better continuous value .

The problem is how you get these X variables.