1 / 23

Lesson 8 - Topics

Lesson 8 - Topics. Creating SAS datasets from procedures Using ODS and data steps to make reports Using PROC RANK Programs 14-15 in course notes LSB 4:11;5:3. Making SAS Datasets From Procedures Output from SAS PROCs can be put into SAS datasets:

jessica-mitchell
Télécharger la présentation

Lesson 8 - Topics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Lesson 8 - Topics • Creating SAS datasets from procedures • Using ODS and data steps to make reports • Using PROC RANK • Programs 14-15 in course notes • LSB 4:11;5:3

  2. Making SAS Datasets From Procedures Output from SAS PROCs can be put into SAS datasets: 1. To do further processing of the information from the output 2. To reformat output to make a report 3. To restructure original SAS dataset or create new variables

  3. Ways to Put Output into SAS Datasets • Using OUTPUT statement available from many procedures • Using ODS OUTPUT statement – any output table can be put into a SAS dataset

  4. Report We Want to Generate Quartiles of Weight by Gender and Center sex clinic N P25 P50 P75 Male A 9 180.0 190.0 208.0 Male B 16 158.3 174.8 218.3 Male C 29 178.0 199.5 220.5 Male D 11 172.0 184.5 194.0 Female A 6 125.0 143.5 160.5 Female B 9 150.0 164.5 184.0 Female C 6 132.5 134.3 138.5 Female D 6 131.0 137.5 148.5

  5. Program 14 LIBNAME class ‘C:\SAS_Files'; * Will use SAS dataset version of TOMHS data; DATA wt; SET class.tomhsp (KEEP=ptid age sex clinic wtbl wt12 ); wtchg = wt12 - wtbl; RUN; PROCFORMAT; VALUEsexF 1 = ‘Male’ 2=‘Female’; RUN;

  6. Create report by sex and clinic of univariate info; PROCSORTDATA = wt; BY sex clinic; PROCUNIVARIATEDATA = wt NOPRINT; BY sex clinic; VAR wt12 ; OUTPUTOUT=univinfo N = n Q1 = p25 MEDIAN = p50 Q3 = P75 ; Dataset univinfo will have one observation for each combination of sex and clinic. Name of new dataset Statistic name = variable name

  7. PROCPRINTDATA = univinfo; FORMAT sex sexF.; RUN; Obs sex clinic n p75 p50 p25 1 Male A 9 208.00 190.00 180.00 2 Male B 16 218.25 174.75 158.25 3 Male C 29 220.50 199.50 178.00 4 Male D 11 194.00 184.50 172.00 5 Female A 6 160.50 143.50 125.00 6 Female B 9 184.00 164.50 150.00 7 Female C 6 138.50 134.25 132.50 8 Female D 6 148.50 137.50 131.00

  8. PROCPRINTDATA = univinfo NOOBS; VAR sex clinic n p25 p50 p75; FORMAT p25 p50 p75 6.1 ; TITLE'Quartiles of Weight by Gender/Center'; RUN; Quartiles of Weight by Gender/Center sex clinic N P25 P50 P75 Male A 9 180.0 190.0 208.0 Male B 16 158.3 174.8 218.3 Male C 29 178.0 199.5 220.5 Male D 11 172.0 184.5 194.0 Female A 6 125.0 143.5 160.5 Female B 9 150.0 164.5 184.0 Female C 6 132.5 134.3 138.5 Female D 6 131.0 137.5 148.5

  9. Using ODS to Send Output to a SAS Dataset Syntax: ODSOUTPUT output-table = new-data-set; * Output quantile table to a dataset; ODSOUTPUT quantiles = qwt; PROCUNIVARIATEDATA = wt ; VAR wtbl wt12 ; RUN; ODSOUTPUT CLOSE ; PROCPRINTDATA=qwt; RUN;

  10. Display of Output Dataset Obs Varname Quantile Estimate 1 wtbl 100% Max 279.30 2 wtbl 99% 274.15 3 wtbl 95% 246.40 4 wtbl 90% 237.40 5 wtbl 75% Q3 215.15 6 wtbl 50% Median 192.65 7 wtbl 25% Q1 165.90 8 wtbl 10% 141.50 9 wtbl 5% 137.40 10 wtbl 1% 130.25 11 wtbl 0% Min 128.50 12 wt12 100% Max 271.50 13 wt12 99% 271.50 14 wt12 95% 239.00 15 wt12 90% 227.00 16 wt12 75% Q3 202.50 17 wt12 50% Median 180.00 18 wt12 25% Q1 153.50 19 wt12 10% 133.00 20 wt12 5% 130.00 21 wt12 1% 123.00 22 wt12 0% Min 123.00 Would like to put side-by-side

  11. DATA wtbl wt12 ; SET qwt; if varname = 'wtbl' then output wtbl; else if varname = 'wt12' then output wt12; RUN; PROC DATASETS ; MODIFY wtbl; RENAME estimate = wtbl; MODIFY wt12; RENAME estimate = wt12; RUN; DATA all; MERGE wtbl wt12; DROP varname; RUN; PROC PRINT; Separate the data into 2 datasets PROC DATASETS used for changing variable names Put 2 datasets side-by-side

  12. Obs Quantile wtbl wt12 1 100% Max 279.30 271.50 2 99% 274.15 271.50 3 95% 246.40 239.00 4 90% 237.40 227.00 5 75% Q3 215.15 202.50 6 50% Median 192.65 180.00 7 25% Q1 165.90 153.50 8 10% 141.50 133.00 9 5% 137.40 130.00 10 1% 130.25 123.00 11 0% Min 128.50 123.00

  13. ODS OUTPUT ParameterEstimates (persist=proc) = betas; PROC REGDATA=WT; MODEL dbpchg = wtchg age sex; RUN; PROC REGdata=wt; MODEL sbpchg = wtchg age sex; RUN; ODS OUTPUT CLOSE; PROC PRINT DATA=betas; RUN;

  14. Display of Output Dataset - Report Obs Dependent Variable Estimate StdErr tValue Probt 1 dbpchg Intercept -0.059 6.431 -0.01 0.99 2 dbpchg wtchg 0.175 0.073 2.38 0.02 3 dbpchg age -0.101 0.112 -0.91 0.37 4 dbpchg sex -2.622 1.572 -1.67 0.10 5 sbpchg Intercept -3.849 13.304 -0.29 0.77 6 sbpchg wtchg 0.364 0.152 2.40 0.02 7 sbpchg age -0.042 0.231 -0.18 0.86 8 sbpchg sex -4.118 3.253 -1.27 0.21

  15. Display of Output Dataset Using BY Statement PROC PRINT; VAR variable estimate stderr tvalue probt; BY dependent NOTSORTED; FORMAT estimate 7.3 stderr 7.3 probt pvalue5.2 ; Dependent=dbpchg Obs Variable Estimate StdErr tValue Probt 1 Intercept -0.059 6.431 -0.01 0.99 2 wtchg 0.175 0.073 2.38 0.02 3 age -0.101 0.112 -0.91 0.37 4 sex -2.622 1.572 -1.67 0.10 Dependent=sbpchg Obs Variable Estimate StdErr tValue Probt 5 Intercept -3.849 13.304 -0.29 0.77 6 wtchg 0.364 0.152 2.40 0.02 7 age -0.042 0.231 -0.18 0.86 8 sex -4.118 3.253 -1.27 0.21

  16. PROC RANK • Used to divide observations into equal size categories based on values of a variable • Creates a new variable containing the categories • New variable is added to the dataset or to a new dataset • Example: Divide weight change into 5 equal categories (Quinitiles)

  17. PROC RANK SYNTAX PROCRANKDATA = dataset OUT = outdataset GROUPS = # of categories VARvarname; RANKSnewvarname; Most of the time you can set OUT to be the same dataset specified in DATA. PROC RANK writes no output

  18. PROGRAM 15 LIBNAME class ‘C:\SAS_Files'; DATA wtchol; SET class.tomhsp (KEEP=ptid clinic sex wtbl wt12 cholbl chol12); wtchg = wt12 - wtbl; cholchg = chol12 - cholbl; RUN; *This PROC will add a new variable to dataset which is the tertile of weight change. The new variable will be 0,1,or 2; PROCRANKDATA = wtchol GROUPS=3OUT = wtchol; VAR wtchg; RANKS twtchg; Name of new variable

  19. PARTIAL LOG 8 DATA wtchol; 9 SET class.tomhsp (KEEP=ptid clinic sex wtbl wt12 cholbl chol12); 10 wtchg = wt12 - wtbl; 11 cholchg = chol12 - cholbl; 12 RUN; NOTE: There were 100 observations read from the data set CLASS.TOMHSP. NOTE: The data set WORK.WTCHOL has 100 observations and 9 variables. PROC RANK DATA = wtchol GROUPS=3 OUT = wtchol; 20 VAR wtchg; RANKS twtchg; 21 RUN; NOTE: The data set WORK.WTCHOL has 100 observations and 10 variables.

  20. PROCFREQDATA = wtchol; TABLES twtchg; RUN; OUTPUT: Rank for Variable wtchg Cumulative Cumulative twtchg Frequency Percent Frequency Percent ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 0 31 33.70 31 33.70 1 30 32.61 61 66.30 2 31 33.70 92 100.00 Frequency Missing = 8

  21. PROCPRINTDATA = wtchol (obs=20); VAR ptid wtchg twtchg; TITLE'Partial Listing of Datset wtchol with new variable added'; RUN; Partial Listing of Datset wtchol with new variable added Obs PTID wtchg twtchg 1 A00083 -12.00 1 2 A00301 . . 3 A00312 -9.50 1 4 A00354 -21.00 0 5 A00400 . . 6 A00504 -9.25 1 7 A00608 . . 8 A00720 -18.50 0 9 A00762 -5.25 2 10 A00811 -6.75 1

  22. PROCMEANSN MEAN MIN MAXMAXDEC=2; VAR cholchg wtchg; CLASS twtchg; TITLE'Mean Cholesterol Change by Tertile of Weight Change'; RUN;

  23. Mean Cholesterol Change by Tertile of Weight Change The MEANS Procedure Rank for Variable N wtchg Obs Variable N Mean Minimum Maximum -------------------------------------------------------------------------- 0 31 cholchg 30 -13.43 -55.00 47.00 wtchg 31 -22.51 -36.50 -14.30 1 30 cholchg 30 -4.70 -37.00 26.00 wtchg 30 -10.21 -14.00 -6.80 2 31 cholchg 31 -0.74 -52.00 45.00 wtchg 31 -1.82 -6.50 13.00 -------------------------------------------------------------------------- Could graph this data in an x-y plot (3 points) Cutpoints for tertiles

More Related