Ann Arbor ASA Up and Running Series: SAS Sponsored by the Ann Arbor Chapter of the American Statistical Association and the Department of Statistics of.

Ann Arbor ASAUp and Running Series:

SAS

Sponsored by the Ann Arbor Chapter of the American Statistical Association and the Department of Statistics of the University of Michigan

Contents• Starting SAS• User Interface• Libraries• Syntax• Getting Data into SAS• Examining Data• Manipulating Data• Descriptive Statistics• Graphing Data• Statistics in SAS

Up and Running Series: SAS2

Starting SAS

Start SAS 9.3 (English)

Up and Running Series: SAS3

User Interface

Log

Comments, warnings, etc.

Program Editor:

Write and submit commands

Output (not seen)

Explorer/ Results

Up and Running Series: SAS 4

Libraries

• SAS requires the creation of Library folders to save the data– Libraries are accessed through LIBNAME command

• Four Libraries are defined by default, at the start of SAS– Maps– SASHELP: holds help info and sample datasets– SASUSER: holds settings, etc.– WORK: default temporary Library for each session

• All data stored in this folder will be deleted at the end of each SAS session

• It is recommended the creation of permanent files/Libraries

Up and Running Series: SAS5

Libraries

• Create a folder called ‘my_files’ on your desktop.

• Run this command in SAS: LIBNAME a "C:\Users\uniquename\Desktop\my_files";

• Refer to datasets in that folder by with the prefix ‘a.datasetname’.

• TIP: Use memorable names for libraries, rather than ‘a’ (e.g., ‘raw’, ‘final’, ‘time1’, etc)

Up and Running Series: SAS6

Syntax

• SAS divides commands into two groups– DATA step

• create/alter datasets– PROC (Procedures)

• perform statistical analyses or generate reports.

• Some exceptions to the rule:– DATA step can be used to generate reports– PROC IMPORT creates a data set– PROC SORT alters data sets

(without telling you!)

Up and Running Series: SAS7

• PROC IMPORT– Allows the reading of standard file types– Allows the reading of plain text, with user-specified

delimiters (i.e., the characters which separate the data)

– WARNING – SAS changed PROC IMPORT for Excel and Access files, in 64-bit SAS

• DATA step– Allows the reading of non-standard file types, complex

file structures, and unusual delimiters.

Getting data into SAS

Up and Running Series: SAS8

DATA step

• SAS syntax can be used to read in raw data files (.txt, .csv files), specifying which variables to read in, which ones are text/numeric, combining multiple rows into one case, etc.

• However, this is a more advanced topic.– Follow up with an Intro class from CSCAR, or by

going through examples from the literature

(e.g., ‘The Little SAS Book’).

Up and Running Series: SAS10

Examining Data

• VIEWTABLE Window– Select dataset icon in Explorer

• PROC CONTENTS– Produces a listing of data set information, including

the variables and their properties

• PROC PRINT– Prints a subset of variables or cases to the output

window

Up and Running Series: SAS11

VIEWTABLE Window

Up and Running Series: SAS12

PROC CONTENTS

• In the Editor window, type:

PROC CONTENTS data=a.class2;run;

• Highlight the syntax• Submit for processing

– Click on icon of ‘running-man’– Right click on selected syntax

Submit Selection

Up and Running Series: SAS13

PROC CONTENTS

Up and Running Series: SAS14

PROC PRINT

• In the Editor window, type:PROC PRINT data=a.class2;run;

• Submit for processing

Up and Running Series: SAS15

PROC PRINT

Up and Running Series: SAS16

Manipulating Data

• Usually done within a data step– Match data sets using a shared key variable– Create new variables, or drop/rename existing

variables– Take one or more subsets of the data– Sort the data by specific variable(s).

• Overwrite existing or create new datasets– PROC SORT– Adding/Removing variables– Merging Datasets

Up and Running Series: SAS17

PROC SORT

• In the Editor window, type:

PROC SORT data=a.class2 out=a.class2sorted;

by age descending weight height;run;

• Submit for processing

• WARNING: PROC SORT alters data– Store in a new dataset

out=‘newdatasetname’;

Up and Running Series: SAS18

PROC SORT

Up and Running Series: SAS19

Adding/Removing variables

• Create new data set, compute new variables, remove unwanted variables

DATA a.class2metric (drop=weight height sex age);

set a.class2;

height_cm=height*2.54;

weight_kg=weight/2.2;

label height_cm=‘Height in CM’

weight_kg=‘Weight in Kilograms’;run;

PROC PRINT data=a.class2metric;

run;• Submit for processing

Up and Running Series: SAS20

Adding/Removing variables

Up and Running Series: SAS21

Merging Datasets

• Data sets must be sorted by the same key variable(s)

proc sort data=a.class2;

by name;

proc sort data=a.class2metric;

by name;

data classmerged;

merge a.class2 a.class2metric;

by name;run;

• Submit for processing

Up and Running Series: SAS22

Merging Datasets

Up and Running Series: SAS23

Merging Datasets

Up and Running Series: SAS24

Descriptive Statistics

• PROC FREQ– Produces a table of counts and percentages– For cross-tabulations, statistical tests can also

be performed; e.g., independence testing

• PROC MEANS– Produces descriptive statistics such as mean,

standard deviation, minimum, maximum

Up and Running Series: SAS25

PROC FREQ

• In the Editor window, type proc freq data=a.class2;

tables age*sex;run;

• Submit for processing

Up and Running Series: SAS26

PROC FREQ

Up and Running Series: SAS27

PROC MEANS

• In the Editor window, type proc means data=a.class2;

var age weight height;

run;

• Submit for processing

Up and Running Series: SAS28

PROC MEANS

Up and Running Series: SAS29

Graphing DataPROC GPLOT

• Simple bivariate scatterplot• Separate lines• Multiple variables scatterplot• Options

Up and Running Series: SAS30

PROC GPLOT

• Simple bivariate scatterplot:proc gplot data=a.class2;

symbol1 value=dot interpol=rl;plot weight*height;

run;

• Submit for processing

Up and Running Series: SAS31

PROC GPLOT - Log

Up and Running Series: SAS32

PROC GPLOT

Up and Running Series: SAS33

• To graph separate lines for each level of a categorical variable, type:

proc gplot data=a.class2;

symbol1 value=dot interpol=rl;

plot weight*height = sex;

run;

• Submit for processing

PROC GPLOT

Up and Running Series: SAS34

PROC GPLOT

Up and Running Series: SAS35

• Multiple variables on the same graph:proc gplot data=a.class2;

symbol1 value=dot interpol=rl color=blue;

symbol2 value=dot interpol=rl color=red;

plot weight * age;plot2 height * age;

run; quit;

• Submit for processing

PROC GPLOT

Up and Running Series: SAS36

PROC GPLOT

Up and Running Series: SAS37

value=___

• Any character enclosed in single quotes

• Special characters– dot– plus sign– star– square– ...and many others

interpol=___

• RL / RQ / RC– linear– quadratic – cubic – regression curves

• JOIN– connects consecutive

points (line graph)• BOX

PROC GPLOT

Up and Running Series: SAS 38

Statistics in SAS

• PROC CORR– Correlational analyses

• PROC REG– Statistical Regression

• PROC UNIVARIATE– To assess normality of regression residuals

Up and Running Series: SAS39

PROC CORR

• Compute bivariate correlation coefficients

proc corr data = a.class2;var age;with height weight;

run;

Up and Running Series: SAS40

PROC CORR

Up and Running Series: SAS41

PROC REG• Run a regression on merged ‘class’ dataset

– Save residuals and predicted values in an output dataset

– Request residual plotproc reg data=a.classmerged;

model height_cm=age weight / partial; output out=reg_data p=predict r=resid

rstudent=rstudent; plot rstudent. * height_cm;

run;quit;

• Notes – the quit command terminates the regression procedure; otherwise it keeps running; the output data set will be in the work library, since no library was specified.Up and Running Series: SAS 42

PROC REG

Up and Running Series: SAS43

PROC REG

Up and Running Series: SAS44

PROC REG

Up and Running Series: SAS45

PROC REG

Up and Running Series: SAS46

PROC UNIVARIATE

• Assess normality of regression residuals stored in the output dataset from PROC REG:

proc univariate data=reg_data;var rstudent;histogram;qqplot / normal (mu=est

sigma=est);run;quit;

Up and Running Series: SAS47

PROC UNIVARIATE

Up and Running Series: SAS 48

PROC UNIVARIATE

Up and Running Series: SAS 49

PROC UNIVARIATE

Up and Running Series: SAS 50

QUESTIONS

Up and Running Series: SAS51

Winter 2013 Training from CSCARhttp://cscar.research.umich.edu/workshops/

Introduction to SAS® - January 28,30, February 1,4,6,8, 2013

Intermediate Topics in SPSS: Data Management and Macros - February 5,7, 2013

Intermediate Topics in SPSS: Advanced Statistical Models - February 12,14, 2013

Intermediate SAS® - February 25,27, March 1, 2013

Regression Analysis - March 11,13,15, 2013

Applications of Hierarchical Linear Models - March 18,20,22, 2013

Statistical Analysis with R - March 19,21, 2013

Introduction to NVivo - April 3, 2013

Applied Structural Equation Modeling - April 10,11,12, 2013

Up and Running Series: SAS 52

Further Resources

• The Little SAS Book: A Primer• UCLA site

– software tutorials, classes and lectures on statistical methods – an incredible site! http://www.ats.ucla.edu/stat/

• SAS Documentation: http://support.sas.com/documentation/

Documentation also found in ‘SAS help’ files.

Up and Running Series: SAS53

54

Other Winter 2013 Workshopsfrom Ann Arbor ASA

R  -  January 31, 1-3 PM

Angell Hall Computing Classroom B

(also known as MH444-B)

For more information go to: http://community.amstat.org/annarbor/home

Up and Running Series: SAS

    PLACE   Starbucks State & Liberty, lower level

    TIME    6:00pm – 6:45pm,

     DATE       TOPIC

    24-JAN   Business Meeting     1 -APR  Business Meeting and Election of Officers

For more information go to: http://community.amstat.org/annarbor/home

Chapter Meetings open to all

Up and Running Series: SAS 55