1. Data Analysis Using SAS
SAS Workshop
Data Analysis Using SAS
Hun Myoung Park, Ph.D.
University Information Technology Services
Center for Statistical and Mathematical Computing
Sunday, September 16, 2018
© The Trustees of Indiana University
(812)

2. Outline Descriptive Statistics Chi-Square Test Measure of Association
Data Analysis Using SAS
September 16, 2018
Outline
Descriptive Statistics
Chi-Square Test
Measure of Association
T-TEST
Analysis of Variance
Correlation Analysis
Ordinary Least Squares (OLS)
Binary Logit and Probit Models
Panel Data Models
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3. OUTPUT DELIVERY SYSTEM
Data Analysis Using SAS
September 16, 2018
OUTPUT DELIVERY SYSTEM
ODS controls SAS output (format, styles, etc.)
HTML format is very useful nowadays especially for data conversion and graphics
ODS HTML FILE=‘c:\temp\test.html’;
PROC …; …;
ODS HTML CLOSE;
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4. DESCRIPTIVE STATISTICS
Data Analysis Using SAS
September 16, 2018
DESCRIPTIVE STATISTICS
You MUST describe and examine data sets of interest carefully before conducting analyses.
PROC REPORT
PROC SUMMARY
PROC UNIVARIATE
PROC MEAN
PROC FREQ
PROC TABULATE
PROC PLOT
PROC CHART
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5. Data Analysis Using SAS
September 16, 2018
PROC REPORT
Provide contents and summary statistics of data sets in many flexible ways.
PROC REPORT DATA=sm.airline NOWD HEADLINE HEADSKIP;
COLUMN airline year cost output fuel;
DEFINE airline / ORDER;
DEFINE year / ORDER;
DEFINE cost / ANALYSIS MEAN;
DEFINE output / ANALYSIS MEAN;
DEFINE fuel / ANALYSIS MEAN;
BREAK AFTER airline/ OL SUMMARIZE SKIP;
RBREAK AFTER / DOL SUMMARIZE;
RUN;
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6. PROC SUMMARY Provides descriptive statistics of variables.
Data Analysis Using SAS
September 16, 2018
PROC SUMMARY
Provides descriptive statistics of variables.
PROC SUMMARY DATA=sm.cancer PRINT;
VAR cigar bladder lung kidney;
RUN;
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Center for Statistical and Mathematical Computing

7. Data Analysis Using SAS
September 16, 2018
PROC MEANS
Like PROC SUMMARY, this procedure provides various descriptive statistics.
PROC MEANS DATA=sm.grade7;
VAR stat math;
PROC MEANS DATA=sm.grade7 N SUM MEAN VAR;
Conduct one sample t-test
PROC MEANS DATA=sm.grade7 T STD STDERR;
RUN;
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Center for Statistical and Mathematical Computing

8. PROC UNIVARIATE Provides various descriptive statistics
Data Analysis Using SAS
September 16, 2018
PROC UNIVARIATE
Provides various descriptive statistics
PROC UNIVARIATE DATA=sm.airline;
VAR cost output;
RUN;
Conducts normality test and one sample t-test
PROC UNIVARIATE DATA=sm.airline NORMAL PLOT;
VAR cost;
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Center for Statistical and Mathematical Computing

9. PROC UNIVARIATE (Q-Q) Provides Q-Q Plots
Data Analysis Using SAS
September 16, 2018
PROC UNIVARIATE (Q-Q)
Provides Q-Q Plots
PROC UNIVARIATE DATA=sm.airline;
VAR cost;
QQPLOT cost /NORMAL;
RUN;
PROC CAPABILITY provides P-P Plot as well
PROC CAPABILITY DATA=sm.airline NORMAL;
PPPLOT cost /NORMAL;
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Center for Statistical and Mathematical Computing

10. PROC FREQ Produces frequency tables of variables listed.
Data Analysis Using SAS
September 16, 2018
PROC FREQ
Produces frequency tables of variables listed.
PROC FREQ DATA=sm.airline;
TABLES airline year;
Produces contingency tables or cross-tables using * between variables.
PROC FREQ DATA=sm.cancer;
TABLES area*smoke / NOROW;
RUN;
NOROW, NOCOL, and NOPERCENT do not display row, column, total percents from each cell, respectively.
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Center for Statistical and Mathematical Computing

11. Data Analysis Using SAS
September 16, 2018
PROC TABULATE
PROC TABULATE produces various statistics in a table form.
TABULATE can control formats and table forms in a sophisticated way.
Useful when summarizing and examining data sets.
PROC TABULATE DATA=sm.airline F=12.3;
CLASS airline;
VAR cost;
TABLE airline,cost*(N MEAN STD)*(F=9.2);
LABEL cost='Cost of Ariline';
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Center for Statistical and Mathematical Computing

12. PROC PLOT Produces a plot of two variables PROC PLOT DATA=sm.cancer;
Data Analysis Using SAS
September 16, 2018
PROC PLOT
Produces a plot of two variables
PROC PLOT DATA=sm.cancer;
PLOT lung*cigar;
RUN;
PLOT lung*cigar=‘%’
kidney*cigar=“*” / OVERLAY;
University Information Technology Services
Center for Statistical and Mathematical Computing

13. Data Analysis Using SAS
September 16, 2018
PROC CHART
Produces various vertical and horizontal charts with many options.
PROC CHART DATA=sm.cancer;
HBAR cigar /TYPE=PERCENT;
VBAR lung / GROUP = smoke TYPE=MEAN;
BLOCK area / GROUP = smoke TYPE=MEAN SUMVAR=lung NOHEADER SYMBOL='X';
RUN;
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Center for Statistical and Mathematical Computing

14. Data Analysis Using SAS
September 16, 2018
CHI-SQUARE TEST 1
Chi-square test examines if two variables are independent.
PROC FREQ conducts chi-square test with the /CHISQ option.
PROC FREQ DATA=sm.cancer;
TABLES area*smoke /CHISQ;
The expected frequency of each cell should be greater than 5; otherwise, chi-square test is not reliable.
TABLES area*smoke /CHISQ EXPECTED;
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Center for Statistical and Mathematical Computing

15. Data Analysis Using SAS
September 16, 2018
CHI-SQUARE TEST 2
Measure of association tells the strength of relationship.
MEASURES is needed.
PROC FREQ DATA=sm.cancer;
TABLES area*smoke /CHISQ MEASURES;
RUN;
Both variables are ordinal, read gamma (-1~1)
Otherwise (at least one variable is nominal), read lambda (0~1).
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Center for Statistical and Mathematical Computing

16. T-TEST 1 T-test compares group means
Data Analysis Using SAS
September 16, 2018
T-TEST 1
T-test compares group means
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Center for Statistical and Mathematical Computing

17. Data Analysis Using SAS
September 16, 2018
T-TEST 2
One sample t-test examines if the means of a variables is 0 or a constant hypothesized.
Use PROC TTEST, UNIVARIATE, and MEANS.
TITLE2 'One Sample T-Test';
PROC TTEST H0=20 ALPHA=.01 DATA=sm.cancer;
VAR lung;
PROC UNIVARIATE MU0=20 VARDEF=DF NORMAL ALPHA=.01 DATA=sm.cancer;
RUN;
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Center for Statistical and Mathematical Computing

18. T-TEST 3 PAIRED statement for paired t-tests
Data Analysis Using SAS
September 16, 2018
T-TEST 3
PAIRED statement for paired t-tests
Data should be arranged in the wide format.
PROC TTEST DATA=sm.cancer;
PAIRED lung*kidney;
RUN;
Use operators (* and :)
PROC TTEST H0=3 DATA=sm.cancer;
PAIRED (lung)*(kidney bladder);
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Center for Statistical and Mathematical Computing

19. T-TEST 4 Independent sample t-test. Data arranged in the long form.
Data Analysis Using SAS
September 16, 2018
T-TEST 4
Independent sample t-test.
PROC TTEST H0=0 ALPHA=.05 DATA=sm.cancer;
CLASS smoke;
VAR lung;
Data arranged in the long form.
Check F-test for equal variance. Read Pooled T in case of equal variance.
PROC TTEST COCHRAN DATA=sm.cancer;
CLASS west;
VAR kidney;
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Center for Statistical and Mathematical Computing

20. ANALYSIS OF VARIANCE 1 Use PROC ANOVA, GLM, and MIXED
Data Analysis Using SAS
September 16, 2018
ANALYSIS OF VARIANCE 1
Use PROC ANOVA, GLM, and MIXED
PROC ANOVA DATA=sm.cancer;
CLASS smoke;
MODEL lung=smoke;
PROC GLM DATA=sm.cancer;
PROC MIXED DATA=sm.cancer; ;
RUN;
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Center for Statistical and Mathematical Computing

21. Data Analysis Using SAS
September 16, 2018
ANALYSIS OF VARIANCE 2
PROC ANOVA can handle balanced data while GLM and MIXED can handle balanced and unbalanced data.
GLM and MIXED are generally recommended for complex models.
PROC GLM DATA=sm.cancer;
CLASS smoke area;
MODEL lung=smoke area /SS3;
RUN;
University Information Technology Services
Center for Statistical and Mathematical Computing

22. Data Analysis Using SAS
September 16, 2018
CORRELATION ANALYSIS
Karl Pearson correlation coefficients for interval variables
PROC CORR DATA=sm.airline PEARSON COV;
VAR cost output fuel load;
RUN;
For ordinal variables, add SPEARMAN and/or KENDALL options to CORR statement instead of PEARSON.
PROC CORR DATA=sm.airline SPEARMAN KENDALL;
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Center for Statistical and Mathematical Computing

23. ORDINARY LEAST SQUARES 1
Data Analysis Using SAS
September 16, 2018
ORDINARY LEAST SQUARES 1
Classical linear regression model or ordinary least squares (OLS).
Has many strong assumptions such as linearity, constant variance, and independent variables that are not related to errors.
Use PROC REG with the MODEL statement.
PROC REG DATA=sm.airline;
MODEL cost = output fuel load;
RUN;
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Center for Statistical and Mathematical Computing

24. ORDINARY LEAST SQUARES 2
Data Analysis Using SAS
September 16, 2018
ORDINARY LEAST SQUARES 2
Imposing restrictions
PROC REG DATA=sm.airline;
MODEL cost = output fuel load /NOINT;
MODEL cost = output fuel load;
RESTRICT load=1;
Hypothesis Test (Wald Test)
TEST output=0;
RUN;
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Center for Statistical and Mathematical Computing

25. ORDINARY LEAST SQUARES 3
Data Analysis Using SAS
September 16, 2018
ORDINARY LEAST SQUARES 3
Get residuals, DW for AR(1)
PROC REG DATA=sm.airline;
MODEL cost = output fuel load /R DW;
RUN;
Check multicollinearity.
MODEL cost = output fuel load /COLLIN VIF TOL;
Serious multicollinearity if tolerance level < (1-R2) or .1, VIF> 10; Eigenvalue <.01, Condition index <50, or proportion of variation > .8
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Center for Statistical and Mathematical Computing

26. ORDINARY LEAST SQUARES 4
Data Analysis Using SAS
September 16, 2018
ORDINARY LEAST SQUARES 4
OLS has strong assumptions that are easily violated in the real world.
PROC NLIN for nonlinear models
PROC SYSLIN for equation systems with errors correlated
PROC AUTOREG and ARIMA for autocorrelation
PROC LOGISTIC and QLIM for categorical dependent variables
University Information Technology Services
Center for Statistical and Mathematical Computing

27. Data Analysis Using SAS
September 16, 2018
LOGIT/PROBIT MODELS 1
Use PROC LOGISTIC, PROBIT, QLIM, GENMOD to fit Logit and Probit Models
PROC LOGISTIC DESCENDING DATA = sm.trust;
MODEL trust = educate income age male;
PROC PROBIT DATA = sm.trust;
MODEL trust = educate income age male /DIST=LOGISTIC;
PROC QLIM DATA=sm.trust;
MODEL trust = educate income age male /DISCRETE(DIST=LOGIT);
PROC GENMOD DATA = sm.trust DESC;
MODEL trust = educate income age male /DIST=BINOMIAL LINK=LOGIT;
RUN;
LOGISTIC produces opposite sigens
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Center for Statistical and Mathematical Computing

28. LOGIT/PROBIT MODELS 2 Compute odd ratios using the UNITS statement
Data Analysis Using SAS
September 16, 2018
LOGIT/PROBIT MODELS 2
Compute odd ratios using the UNITS statement
PROC LOGISTIC DATA = sm.trust;
MODEL trust(EVENT='1') = educate income age male;
UNITS educate=SD income=SD age=SD;
RUN;
For a unit increase in x, the odds of having 1 are expected to change by a factor of odd ratios =exp(b_hat*sd).
Marginal effects need computation.
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Center for Statistical and Mathematical Computing

29. LOGIT/PROBIT MODELS 3 Estimate Probit models
Data Analysis Using SAS
September 16, 2018
LOGIT/PROBIT MODELS 3
Estimate Probit models
PROC PROBIT DATA = sm.trust;
MODEL trust = educate income age male;
PROC LOGISTIC DATA = sm.trust DESC;
MODEL trust = educate income age male /LINK=PROBIT;
PROC QLIM DATA=sm.trust;
MODEL trust = educate income age male /DISCRETE (DIST=NORMAL);
RUN;
Logistic and QLIM are recommended
University Information Technology Services
Center for Statistical and Mathematical Computing

30. Data Analysis Using SAS
September 16, 2018
PANEL DATA MODELS 1
Fixed effect model assumes different intercepts among groups or periods.
Fixed effect model is in fact a dummy variable least squares model.
Random effect model assumes different variances among groups or periods.
In SAS, PROC PANEL and TSCSREG fit fixed and random effect models.
PROC PANEL is preferred.
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Center for Statistical and Mathematical Computing

31. PANEL DATA MODELS 2 A dummy variable least squares model.
Data Analysis Using SAS
September 16, 2018
PANEL DATA MODELS 2
A dummy variable least squares model.
PROC REG DATA=sm.airline;
MODEL cost = g1-g5 output fuel load;
RUN;
Fixed effect model using PROC PANEL that fits the adjusted within effect model
PROC PANEL DATA=masil.airline;
ID airline year;
MODEL cost = output fuel load /FIXONE;
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Center for Statistical and Mathematical Computing

32. PANEL DATA MODELS 3 Random effect model using PROC PANEL and TSCSREG
Data Analysis Using SAS
September 16, 2018
PANEL DATA MODELS 3
Random effect model using PROC PANEL and TSCSREG
PROC PANEL DATA=sm.airline;
ID airline year;
MODEL cost = output fuel load /RANONE;
RUN;
PROC TSCSREG DATA=sm.airline;
University Information Technology Services
Center for Statistical and Mathematical Computing

33. Data Analysis Using SAS
September 16, 2018
FACTOR ANALYSIS 1
Extract a small number of factors (latent variables) out of many manifest variables (observed variables).
PROC FACTOR DATA=sm.survey;
VAR q1-q20;
RUN;
Rotation methods (e.g., VARIMAX, PARSIMAX, EQUAMAX, and PROMAX) in ROTATE= or R= and the number of factors in NFACTORS= or N=.
PROC FACTOR DATA=sm.survey ROTATE=VARIMAX NFACTORS=3;
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Center for Statistical and Mathematical Computing

34. Data Analysis Using SAS
September 16, 2018
FACTOR ANALYSIS 2
Method of extracting factors such as principal component analysis-default method, maximum likelihood (ML), and principal factor analysis (PRINIT).
PROC FACTOR DATA=sm.survey METHOD=ML R=PROMAX N=3;
VAR q1-q20;
Store factor scores using OUT=. Variables Factor1, Factor2, Factor3, … are created in the data set.
PROC FACTOR DATA=sm.survey M=ML R=VARIMAX N=3 OUT=sm.surveyScore;
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Center for Statistical and Mathematical Computing

35. Data Analysis Using SAS
September 16, 2018
RELIABILITY TEST
PROC CORR produces Chronbach‘s coefficient alpha statistic with ALPHA.
PROC CORR DATA=sm.survey ALPHA NOMISS;
VAR q1-q20;
RUN;
NOMISS excludes observations with missing values.
Alpha larger than .8 indicates high reliability of measurement.
Section labeled as “Cronbach Coefficient Alpha with Deleted Variable” lists alpha if the variable is removed.
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36. REFERENCES University Information Technology Services
Data Analysis Using SAS
September 16, 2018
REFERENCES
Long, J. Scott Regression Models for Categorical and Limited Dependent Variables. Sage.
Muller, Keith E., and Bethel A. Fetterman Regression and ANOVA: An Integrated Approach Using SAS Software. Cary, NC: SAS Institute.
Stokes, Maura E., Charles S. Davis, and Gary G. Koch Categorical Data Analysis Using the SAS System, 2nd ed.. Cary, NC: SAS Institute.
Walker, Glenn A Common Statistical Methods for Clinical Research with SAS Examples. Cary, NC: SAS Institute.
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