SAS Analysis Examples Replication C8. * SAS Analysis Examples Replication for ASDA 2nd Edition * Berglund April 2017 * Chapter 8 ;
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1 SAS Analysis Examples Replication C8 * SAS Analysis Examples Replication for ASDA 2nd Edition * Berglund April 2017 * Chapter 8 ; libname ncsr "P:\ASDA 2\Data sets\ncsr\" ; data c8_ncsr ; set ncsr.ncsr_sub_13nov2015 ; run ; proc format ; value af 1='18-29' 2='30-44' 3='45-59' 4='60+' ; value sf 1='M' 2='F' ; value edf 1='0-11' 2='12' 3='13-15' 4='16+' ; value mf 1='Currently Married' 2='Previously Married' 3='Never Married' ; value yn 1='Yes' 0='No' ; run ; ods rtf style=normalprinter bodytitle ; title "Example 8.1: Examining Predictors of a Lifetime Major Depressive Episode in the NCS-R Data. " ; proc surveyfreq ; strata sestrat ; cluster seclustr ; weight ncsrwtlg ; tables (ag4cat sex ald ed4cat mar3cat)*mde /row chisq(secondorder) ; format ag4cat af. sex sf. ed4cat edf. mar3cat mf. mde yn. ; run ; title "Numbers for Table 8.6" ; proc surveylogistic data=c8_ncsr ; strata sestrat ; cluster seclustr ; weight ncsrwtlg ; class ag4cat (ref=first) sex (ref=last) ed4cat (ref=first) mar3cat (ref=first) / param=ref ; model mde (event='yes') =ag4cat sex ald ed4cat mar3cat ; format ag4cat af. sex sf. ed4cat edf. mar3cat mf. mde yn.; output out=predicted p=predprob ; run ; ods text ="Margins Plot and GOF test not easily available in SAS, for how to do margins plot see from SAS tech support" ; title "Interaction Testing for Preliminary Model Predicting MDE Outcome " ; proc surveylogistic data=c8_ncsr ; strata sestrat ; cluster seclustr ; weight ncsrwtlg ; class ag4cat (ref=first) sex (ref=last) ed4cat (ref=first) mar3cat (ref=first) / param=ref ; model mde (event='yes') =ag4cat sex ald ed4cat mar3cat ag4cat*sex ald*sex ed4cat*sex mar3cat*sex ; format ag4cat af. sex sf. ed4cat edf. mar3cat mf. mde yn.; run ; title "Numbers for Table 8.9" ; title2 "Logistic Regression" ; proc surveylogistic data=c8_ncsr ; strata sestrat ; cluster seclustr ; weight ncsrwtlg ; class ag4cat (ref=first) sex (ref=last) ed4cat (ref=first) mar3cat (ref=first) / param=ref ; model ald (event='yes') =ag4cat sex ed4cat mar3cat ; format ag4cat af. sex sf. ed4cat edf. mar3cat mf. ald yn. ; run ; title2 "Probit Regression" ; proc surveylogistic data=c8_ncsr ; strata sestrat ; cluster seclustr ; weight ncsrwtlg ; class ag4cat (ref=first) sex (ref=last) ed4cat (ref=first) mar3cat (ref=first) / param=ref ; model ald (event='yes') =ag4cat sex ed4cat mar3cat / link=probit ; format ag4cat af. sex sf. ed4cat edf. mar3cat mf. ald yn. ; run ; title2 "CLOGLOG Regression" ; proc surveylogistic data=c8_ncsr ; strata sestrat ; cluster seclustr ; weight ncsrwtlg ; class ag4cat (ref=first) sex (ref=last) ed4cat (ref=first) mar3cat (ref=first) / param=ref ; model ald (event='yes') =ag4cat sex ed4cat mar3cat / link=cloglog ; format ag4cat af. sex sf. ed4cat edf. mar3cat mf. ald yn.; run ; ods rtf close ; 1
2 Example 8.1: Examining Predictors of a Lifetime Major Depressive Episode in the NCS-R Data. The SURVEYFREQ Procedure Data Summary Number of Strata 42 Number of Clusters 84 Number of Observations 9282 Number of Observations Used 5692 Number of Obs with Nonpositive Weights 3590 Sum of Weights ag4cat mde Weighted Table of ag4cat by mde Wgt Freq Row Row No Yes No Yes No Yes No Yes No Yes Rao-Scott Chi-Square Test Pearson Chi-Square Design Correction First-Order Chi-Square Second-Order Chi-Square DF 2.71 Pr > ChiSq <.0001 F Value Num DF 2.71 Den DF Pr > F <.0001 Sample Size = 5692 SEX mde Weighted Table of SEX by mde Wgt Freq Row Row M No Yes F No Yes
3 SEX mde Weighted Table of SEX by mde Wgt Freq No Yes Row Row Rao-Scott Chi-Square Test Pearson Chi-Square Design Correction First-Order Chi-Square Second-Order Chi-Square DF 1 Pr > ChiSq <.0001 F Value Num DF 1 Den DF 42 Pr > F <.0001 Sample Size = 5692 ald mde Weighted Table of ald by mde Wgt Freq Row Row 0 No Yes No Yes No Yes Rao-Scott Chi-Square Test Pearson Chi-Square Design Correction First-Order Chi-Square Second-Order Chi-Square DF 1 Pr > ChiSq <.0001 F Value Num DF 1 Den DF 42 Pr > F <.0001 Sample Size = 5692 ED4CAT mde Weighted Table of ED4CAT by mde Wgt Freq Row Row 0-11 No
4 ED4CAT mde Weighted Table of ED4CAT by mde Wgt Freq Row Row Yes No Yes No Yes No Yes No Yes Rao-Scott Chi-Square Test Pearson Chi-Square Design Correction First-Order Chi-Square Second-Order Chi-Square DF 2.89 Pr > ChiSq F Value Num DF 2.89 Den DF Pr > F Sample Size = 5692 MAR3CAT mde Table of MAR3CAT by mde Weighted Wgt Freq Row Row Currently Married No Yes Previously Married No Yes Never Married No Yes No Yes Rao-Scott Chi-Square Test Pearson Chi-Square Design Correction First-Order Chi-Square
5 Rao-Scott Chi-Square Test Second-Order Chi-Square DF 1.93 Pr > ChiSq <.0001 F Value Num DF 1.93 Den DF Pr > F <.0001 Sample Size =
6 Numbers for Table 8.6 The SURVEYLOGISTIC Procedure Model Information Data Set WORK.C8_NCSR Response Variable mde Major Depressive Episode 1=Yes 0=No Number of Response Levels 2 Stratum Variable SESTRAT SAMPLING ERROR STRATUM Number of Strata 42 Cluster Variable SECLUSTR SAMPLING ERROR CLUSTER Number of Clusters 84 Weight Variable NCSRWTLG NCSR sample part 2 weight Model Binary Logit Optimization Technique Fisher's Scoring Variance Adjustment Degrees of Freedom (DF) Variance Estimation Method Taylor Series Variance Adjustment Degrees of Freedom (DF) Number of Observations Read 9282 Number of Observations Used 5692 Sum of Weights Read 5692 Sum of Weights Used 5692 Ordered Value mde Response Profile Weight 1 No Yes Probability modeled is mde='yes'. Note: 3590 observations having nonpositive frequencies or weights were excluded since they do not contribute to the analysis. Class Class Level Information Value Design Variables ag4cat SEX F 1 M 0 ED4CAT MAR3CAT Currently Married 0 0 Never Married 1 0 Previously Married 0 1 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. 6
7 Criterion Model Fit Statistics Only and Covariates AIC SC Log L Testing Global Null Hypothesis: BETA=0 Test F Value Num DF Den DF Pr > F Likelihood Ratio <.0001 Score <.0001 Wald <.0001 NOTE: Second-order Rao-Scott design correction applied to the Likelihood Ratio test. Type 3 Analysis of Effects Effect F Value Num DF Den DF Pr > F ag4cat <.0001 SEX <.0001 ald <.0001 ED4CAT MAR3CAT <.0001 Parameter Analysis of Maximum Likelihood Estimates Estimate Standard Error t Value Pr > t <.0001 ag4cat ag4cat ag4cat <.0001 SEX F <.0001 ald <.0001 ED4CAT ED4CAT ED4CAT MAR3CAT Never Married MAR3CAT Previously Married <.0001 NOTE: The degrees of freedom for the t tests is 42. Effect Odds Ratio Estimates Point Estimate 95% Confidence Limits ag4cat vs ag4cat vs ag4cat 60+ vs SEX F vs M ald ED4CAT 12 vs ED4CAT vs ED4CAT 16+ vs MAR3CAT Never Married vs Currently Married MAR3CAT Previously Married vs Currently Married NOTE: The degrees of freedom in computing the confidence limits is 42. 7
8 Association of Predicted Probabilities and Observed Responses Concordant 61.5 Somers' D Discordant 36.8 Gamma Tied 1.7 Tau-a Pairs c Margins Plot and GOF test not easily available in SAS 8
9 Interaction Testing for Preliminary Model Predicting MDE Outcome The SURVEYLOGISTIC Procedure Model Information Data Set WORK.C8_NCSR Response Variable mde Major Depressive Episode 1=Yes 0=No Number of Response Levels 2 Stratum Variable SESTRAT SAMPLING ERROR STRATUM Number of Strata 42 Cluster Variable SECLUSTR SAMPLING ERROR CLUSTER Number of Clusters 84 Weight Variable NCSRWTLG NCSR sample part 2 weight Model Binary Logit Optimization Technique Fisher's Scoring Variance Adjustment Degrees of Freedom (DF) Variance Estimation Method Taylor Series Variance Adjustment Degrees of Freedom (DF) Number of Observations Read 9282 Number of Observations Used 5692 Sum of Weights Read 5692 Sum of Weights Used 5692 Ordered Value mde Response Profile Weight 1 No Yes Probability modeled is mde='yes'. Note: 3590 observations having nonpositive frequencies or weights were excluded since they do not contribute to the analysis. Class Class Level Information Value Design Variables ag4cat SEX F 1 M 0 ED4CAT MAR3CAT Currently Married 0 0 Never Married 1 0 Previously Married 0 1 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. 9
10 Criterion Model Fit Statistics Only and Covariates AIC SC Log L Testing Global Null Hypothesis: BETA=0 Test F Value Num DF Den DF Pr > F Likelihood Ratio <.0001 Score <.0001 Wald <.0001 NOTE: Second-order Rao-Scott design correction applied to the Likelihood Ratio test. Note: Joint Tests Effect F Value Num DF Den DF Pr > F ag4cat <.0001 SEX ald <.0001 ED4CAT MAR3CAT ag4cat*sex ald*sex SEX*ED4CAT SEX*MAR3CAT Under full-rank parameterizations, Type 3 effect tests are replaced by joint tests. The joint test for an effect is a test that all the parameters associated with that effect are zero. Such joint tests might not be equivalent to Type 3 effect tests under GLM parameterization. Parameter Analysis of Maximum Likelihood Estimates Estimate Standard Error t Value Pr > t <.0001 ag4cat ag4cat ag4cat SEX F ald <.0001 ED4CAT ED4CAT ED4CAT MAR3CAT Never Married MAR3CAT Previously Married ag4cat*sex F ag4cat*sex F ag4cat*sex 60+ F ald*sex F SEX*ED4CAT F SEX*ED4CAT F SEX*ED4CAT F SEX*MAR3CAT F Never Married SEX*MAR3CAT F Previously Married NOTE: The degrees of freedom for the t tests is
11 Association of Predicted Probabilities and Observed Responses Concordant 61.4 Somers' D Discordant 36.4 Gamma Tied 2.2 Tau-a Pairs c
12 Data Set Numbers for Table 8.9 Logistic Regression The SURVEYLOGISTIC Procedure Model Information WORK.C8_NCSR Response Variable ald Alcohol Dependence 1=Yes 0=No Number of Response Levels 2 Stratum Variable SESTRAT SAMPLING ERROR STRATUM Number of Strata 42 Cluster Variable SECLUSTR SAMPLING ERROR CLUSTER Number of Clusters 84 Weight Variable NCSRWTLG NCSR sample part 2 weight Model Optimization Technique Variance Adjustment Binary Logit Fisher's Scoring Degrees of Freedom (DF) Variance Estimation Method Taylor Series Variance Adjustment Degrees of Freedom (DF) Number of Observations Read 9282 Number of Observations Used 5692 Sum of Weights Read 5692 Sum of Weights Used 5692 Ordered Value ald Response Profile Weight 1 No Yes Probability modeled is ald='yes'. Note: 3590 observations having nonpositive frequencies or weights were excluded since they do not contribute to the analysis. Class Class Level Information Value Design Variables ag4cat SEX F 1 M 0 ED4CAT MAR3CAT Currently Married 0 0 Never Married 1 0 Previously Married 0 1 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. 12
13 Criterion Model Fit Statistics Only and Covariates AIC SC Log L Testing Global Null Hypothesis: BETA=0 Test F Value Num DF Den DF Pr > F Likelihood Ratio <.0001 Score <.0001 Wald <.0001 NOTE: Second-order Rao-Scott design correction applied to the Likelihood Ratio test. Type 3 Analysis of Effects Effect F Value Num DF Den DF Pr > F ag4cat <.0001 SEX <.0001 ED4CAT MAR3CAT Parameter Analysis of Maximum Likelihood Estimates Estimate Standard Error t Value Pr > t <.0001 ag4cat ag4cat ag4cat <.0001 SEX F <.0001 ED4CAT ED4CAT ED4CAT MAR3CAT Never Married MAR3CAT Previously Married NOTE: The degrees of freedom for the t tests is 42. Effect Odds Ratio Estimates Point Estimate 95% Confidence Limits ag4cat vs ag4cat vs ag4cat 60+ vs SEX F vs M ED4CAT 12 vs ED4CAT vs ED4CAT 16+ vs MAR3CAT Never Married vs Currently Married MAR3CAT Previously Married vs Currently Married NOTE: The degrees of freedom in computing the confidence limits is
14 Association of Predicted Probabilities and Observed Responses Concordant 65.0 Somers' D Discordant 31.5 Gamma Tied 3.5 Tau-a Pairs c
15 Data Set Numbers for Table 8.9 Probit Regression The SURVEYLOGISTIC Procedure Model Information WORK.C8_NCSR Response Variable ald Alcohol Dependence 1=Yes 0=No Number of Response Levels 2 Stratum Variable SESTRAT SAMPLING ERROR STRATUM Number of Strata 42 Cluster Variable SECLUSTR SAMPLING ERROR CLUSTER Number of Clusters 84 Weight Variable NCSRWTLG NCSR sample part 2 weight Model Optimization Technique Variance Adjustment Binary Probit Fisher's Scoring Degrees of Freedom (DF) Variance Estimation Method Taylor Series Variance Adjustment Degrees of Freedom (DF) Number of Observations Read 9282 Number of Observations Used 5692 Sum of Weights Read 5692 Sum of Weights Used 5692 Ordered Value ald Response Profile Weight 1 No Yes Probability modeled is ald='yes'. Note: 3590 observations having nonpositive frequencies or weights were excluded since they do not contribute to the analysis. Class Class Level Information Value Design Variables ag4cat SEX F 1 M 0 ED4CAT MAR3CAT Currently Married 0 0 Never Married 1 0 Previously Married 0 1 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. 15
16 Criterion Model Fit Statistics Only and Covariates AIC SC Log L Testing Global Null Hypothesis: BETA=0 Test F Value Num DF Den DF Pr > F Likelihood Ratio <.0001 Score <.0001 Wald <.0001 NOTE: Second-order Rao-Scott design correction applied to the Likelihood Ratio test. Type 3 Analysis of Effects Effect F Value Num DF Den DF Pr > F ag4cat <.0001 SEX <.0001 ED4CAT MAR3CAT Parameter Analysis of Maximum Likelihood Estimates Estimate Standard Error t Value Pr > t <.0001 ag4cat ag4cat ag4cat <.0001 SEX F <.0001 ED4CAT ED4CAT ED4CAT MAR3CAT Never Married MAR3CAT Previously Married NOTE: The degrees of freedom for the t tests is 42. Association of Predicted Probabilities and Observed Responses Concordant 64.9 Somers' D Discordant 31.4 Gamma Tied 3.8 Tau-a Pairs c
17 Data Set Numbers for Table 8.9 CLOGLOG Regression The SURVEYLOGISTIC Procedure Model Information WORK.C8_NCSR Response Variable ald Alcohol Dependence 1=Yes 0=No Number of Response Levels 2 Stratum Variable SESTRAT SAMPLING ERROR STRATUM Number of Strata 42 Cluster Variable SECLUSTR SAMPLING ERROR CLUSTER Number of Clusters 84 Weight Variable NCSRWTLG NCSR sample part 2 weight Model Optimization Technique Variance Adjustment Binary Cloglog Fisher's Scoring Degrees of Freedom (DF) Variance Estimation Method Taylor Series Variance Adjustment Degrees of Freedom (DF) Number of Observations Read 9282 Number of Observations Used 5692 Sum of Weights Read 5692 Sum of Weights Used 5692 Ordered Value ald Response Profile Weight 1 No Yes Probability modeled is ald='yes'. Note: 3590 observations having nonpositive frequencies or weights were excluded since they do not contribute to the analysis. Class Class Level Information Value Design Variables ag4cat SEX F 1 M 0 ED4CAT MAR3CAT Currently Married 0 0 Never Married 1 0 Previously Married 0 1 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. 17
18 Criterion Model Fit Statistics Only and Covariates AIC SC Log L Testing Global Null Hypothesis: BETA=0 Test F Value Num DF Den DF Pr > F Likelihood Ratio <.0001 Score <.0001 Wald <.0001 NOTE: Second-order Rao-Scott design correction applied to the Likelihood Ratio test. Type 3 Analysis of Effects Effect F Value Num DF Den DF Pr > F ag4cat <.0001 SEX <.0001 ED4CAT MAR3CAT Parameter Analysis of Maximum Likelihood Estimates Estimate Standard Error t Value Pr > t <.0001 ag4cat ag4cat ag4cat <.0001 SEX F <.0001 ED4CAT ED4CAT ED4CAT MAR3CAT Never Married MAR3CAT Previously Married NOTE: The degrees of freedom for the t tests is 42. Association of Predicted Probabilities and Observed Responses Concordant 64.9 Somers' D Discordant 31.4 Gamma Tied 3.7 Tau-a Pairs c
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DATA a; INFILE 'downs.dat' ; INPUT AgeL AgeU BirthOrd Cases Births ; MidAge = (AgeL + AgeU)/2 ; Rate = 1000*Cases/Births; (epidemiologically correct: a prevalence rate) LogRate = Log10( (Cases+0.5)/Births