ࡱ> #` {]bjbjmm ;ZT%mmm8ndjn!hpoo"(o(o(oqqq$؃h@ qOq|qqq (o(o'"kkkqR(o(okqkkj"k(on Wmozpk80hkԆ߀pԆkԆk|qqkqqqqq Oqqqhqqqq!!!8*Z!!!*Z@^ SAS t-test Commands /********************************************** This example shows how to import an Excel File, set up missing value codes and create a permanent SAS data set. It also shows boxplots, two-sample t-tests, paired t-tests and one-sample t-tests. Filename: ttest.sas **********************************************/ OPTIONS FORMCHAR="|----|+|---+=|-/\<>*"; /*Import the data from Excel*/ PROC IMPORT OUT= WORK.owen DATAFILE= "d:\510\2007\data\Owen.xls" DBMS=EXCEL2000 REPLACE; GETNAMES=YES; RUN; /*Create a new permanent SAS data set*/ libname b510 "d:\510\"; data b510.owen; set owen; if vit_a = 99 then vit_a = .; if head_cir = 99 then head_cir = .; if fatfold = 99 then fatfold = .; if b_weight = 999 then b_weight= .; if mot_age = 99 then mot_age = .; if b_order = 99 then b_order = .; if m_height = 999 then m_height=.; if f_height = 999 then f_height=.; bwt_g = b_weight*10; if bwt_g not=. and bwt_g < 2500 then lowbwt=1; if bwt_g >=2500 then lowbwt=0; log_fatfold = log(fatfold); htdiff = f_height - m_height; run; /*Simple Descriptive Statistics on all Numeric Variables*/ proc means data=b510.owen; run; The MEANS Procedure Variable Label N Mean Std Dev Minimum Maximum ----------------------------------------------------------------------------------------------- FAM_NUM_ FAM_NUM 1006 4525.11 1634.03 2000.00 7569.00 CHILDNUM CHILDNUM 1006 1.3359841 0.5716672 1.0000000 3.0000000 AGE AGE 1006 44.0248509 16.6610452 12.0000000 73.0000000 SEX SEX 1006 1.4890656 0.5001291 1.0000000 2.0000000 RACE RACE 1006 1.2823062 0.4503454 1.0000000 2.0000000 W_RANK W_RANK 1006 2.2127237 0.9024440 1.0000000 4.0000000 INCOME_C INCOME_C 1006 1581.31 974.2279710 80.0000000 6250.00 HEIGHT HEIGHT 1001 99.0429570 11.4300111 70.0000000 130.0000000 WEIGHT WEIGHT 1000 15.6290800 3.6523446 8.2400000 41.0800000 HEMO HEMO 1006 12.4606362 1.1578850 6.2000000 24.1000000 VIT_C VIT_C 1006 1.1302187 0.6599121 0.1000000 3.5000000 VIT_A VIT_A 763 36.0380079 8.8951237 15.0000000 78.0000000 HEAD_CIR HEAD_CIR 999 49.3763764 2.0739057 39.0000000 56.0000000 FATFOLD FATFOLD 993 4.4562941 1.6683194 2.6000000 42.0000000 B_WEIGHT B_WEIGHT 986 325.0517241 59.5162936 91.0000000 544.0000000 MOT_AGE MOT_AGE 981 29.2660550 6.2603025 17.0000000 51.0000000 B_ORDER B_ORDER 980 2.9479592 2.1939526 1.0000000 16.0000000 M_HEIGHT M_HEIGHT 980 163.7632653 6.3663343 122.0000000 199.0000000 F_HEIGHT F_HEIGHT 975 178.2194872 7.3821354 152.0000000 210.0000000 bwt_g 986 3250.52 595.1629357 910.0000000 5440.00 lowbwt 986 0.1075051 0.3099115 0 1.0000000 log_fatfold 993 1.4599658 0.2396859 0.9555114 3.7376696 htdiff 972 14.4218107 8.7834139 -12.0000000 56.0000000 bmi 998 15.8124399 1.6634700 11.0247934 26.2912000 ----------------------------------------------------------------------------------------------- /*Descriptive Statistics for each level of SEX using a CLASS statement. No sorting is necessary.*/ proc means data=b510.owen; class sex; var bwt_g bmi fatfold log_fatfold; run; The MEANS Procedure N SEX Obs Variable Label N Mean Std Dev Minimum Maximum ---------------------------------------------------------------------------------------------------------- 1 514 bwt_g 497 3340.56 565.3268435 1360.00 5170.00 bmi 510 15.8982386 1.6074313 11.3795135 26.2912000 FATFOLD FATFOLD 507 4.2518738 0.9720458 2.6000000 10.2000000 log_fatfold 507 1.4247028 0.2076417 0.9555114 2.3223877 2 492 bwt_g 489 3159.00 611.1350784 910.0000000 5440.00 bmi 488 15.7227732 1.7171565 11.0247934 24.4485835 FATFOLD FATFOLD 486 4.6695473 2.1489049 2.6000000 42.0000000 log_fatfold 486 1.4967524 0.2643232 0.9555114 3.7376696 ---------------------------------------------------------------------------------------------------------- /*Descriptive Statistics for each level of SEX using a BY statement Data set must first be sorted BY SEX.*/ proc sort data=b510.owen; by sex; run; proc means data=b510.owen; by sex; var bwt_g weight fatfold log_fatfold; run; -------------------------------------------- SEX=1 --------------------------------------------- The MEANS Procedure Variable Label N Mean Std Dev Minimum Maximum ---------------------------------------------------------------------------------------------- bwt_g 497 3340.56 565.3268435 1360.00 5170.00 bmi 510 15.8982386 1.6074313 11.3795135 26.2912000 FATFOLD FATFOLD 507 4.2518738 0.9720458 2.6000000 10.2000000 log_fatfold 507 1.4247028 0.2076417 0.9555114 2.3223877 ---------------------------------------------------------------------------------------------- -------------------------------------------- SEX=2 --------------------------------------------- Variable Label N Mean Std Dev Minimum Maximum ---------------------------------------------------------------------------------------------- bwt_g 489 3159.00 611.1350784 910.0000000 5440.00 bmi 488 15.7227732 1.7171565 11.0247934 24.4485835 FATFOLD FATFOLD 486 4.6695473 2.1489049 2.6000000 42.0000000 log_fatfold 486 1.4967524 0.2643232 0.9555114 3.7376696 ---------------------------------------------------------------------------------------------- /*Boxplots of continuous variables by SEX. First sort BY SEX*/ /*Note: If data are already sorted by SEX, SAS will not resort*/ proc sort data=b510.owen; by sex; run; proc boxplot data=b510.owen; plot bwt_g*sex / boxstyle=schematic; plot bmi*sex / boxstyle=schematic; plot fatfold*sex / boxstyle=schematic; plot log_fatfold*sex / boxstyle=schematic; run;     /*Independent Samples t-test comparing means of continous variables for each level of SEX. No sorting is necessary*/ proc ttest data=b510.owen; class sex; var bwt_g weight log_fatfold; run; The TTEST Procedure Statistics Lower CL Upper CL Lower CL Upper CL Variable SEX N Mean Mean Mean Std Dev Std Dev Std Dev Std Err bwt_g 1 497 3290.7 3340.6 3390.4 532.23 565.33 602.84 25.358 bwt_g 2 489 3104.7 3159 3213.3 575.08 611.14 652.05 27.636 bwt_g Diff (1-2) 108.01 181.57 255.12 563.6 588.49 615.7 37.484 bmi 1 510 15.758 15.898 16.038 1.5145 1.6074 1.7126 0.0712 bmi 2 488 15.57 15.723 15.876 1.6158 1.7172 1.8322 0.0777 bmi Diff (1-2) -0.031 0.1755 0.382 1.5921 1.662 1.7383 0.1052 log_fatfold 1 507 1.4066 1.4247 1.4428 0.1956 0.2076 0.2213 0.0092 log_fatfold 2 486 1.4732 1.4968 1.5203 0.2487 0.2643 0.2821 0.012 log_fatfold Diff (1-2) -0.102 -0.072 -0.043 0.2271 0.2371 0.248 0.0151  T-Tests Variable Method Variances DF t Value Pr > |t| bwt_g Pooled Equal 984 4.84 <.0001 bwt_g Satterthwaite Unequal 975 4.84 <.0001 bmi Pooled Equal 996 1.67 0.0958 bmi Satterthwaite Unequal 984 1.66 0.0963 log_fatfold Pooled Equal 991 -4.79 <.0001 log_fatfold Satterthwaite Unequal 920 -4.76 <.0001  Equality of Variances Variable Method Num DF Den DF F Value Pr > F bwt_g Folded F 488 496 1.17 0.0842 bmi Folded F 487 509 1.14 0.1407 log_fatfold Folded F 485 506 1.62 <.0001  /*Paired samples t-test comparing mother's height and father's height*/ proc ttest data=b510.owen; paired f_height*m_height; run; The TTEST Procedure Statistics Lower CL Upper CL Lower CL Upper CL Difference N Mean Mean Mean Std Dev Std Dev Std Dev Std Err F_HEIGHT - M_HEIGHT 972 13.869 14.422 14.975 8.4096 8.7834 9.1923 0.2817 T-Tests Difference DF t Value Pr > |t| F_HEIGHT - M_HEIGHT 971 51.19 <.0001 /*Paired samples t-test comparing mother's height and father's height for each level of SEX. Remember, data must be sorted BY SEX first. Because it was sorted earlier, we do not have to sort again.*/ proc ttest data=b510.owen; by sex; paired f_height*m_height; run; -------------------------------------------- SEX=1 -------------------------------------------- The TTEST Procedure Statistics Lower CL Upper CL Lower CL Upper CL Difference N Mean Mean Mean Std Dev Std Dev Std Dev Std Err F_HEIGHT - M_HEIGHT 494 13.637 14.435 15.233 8.4958 9.0257 9.6266 0.4061 T-Tests Difference DF t Value Pr > |t| F_HEIGHT - M_HEIGHT 493 35.55 <.00 -------------------------------------------- SEX=2 -------------------------------------------- Statistics Lower CL Upper CL Lower CL Upper CL Difference N Mean Mean Mean Std Dev Std Dev Std Dev Std Err F_HEIGHT - M_HEIGHT 478 13.641 14.408 15.175 8.0263 8.5352 9.1136 0.3904 T-Tests Difference DF t Value Pr > |t| F_HEIGHT - M_HEIGHT 477 36.91 <.0001 /*One-sample t-test to test whether mean of htdiff=0, using Proc ttest*/ proc ttest data=b510.owen; var htdiff; run; The TTEST Procedure Statistics Lower CL Upper CL Lower CL Upper CL Variable N Mean Mean Mean Std Dev Std Dev Std Dev Std Err Minimum Maximum htdiff 972 13.869 14.422 14.975 8.4096 8.7834 9.1923 0.2817 -12 56 T-Tests Variable DF t Value Pr > |t| htdiff 971 51.19 <.0001 /*One-sample t-test to test whether mean of htdiff=15 cm, using Proc ttest*/ proc ttest data=b510.owen h0=15; var htdiff; run; The TTEST Procedure Statistics Lower CL Upper CL Lower CL Upper CL Variable N Mean Mean Mean Std Dev Std Dev Std Dev Std Err htdiff 972 13.869 14.422 14.975 8.4096 8.7834 9.1923 0.2817 T-Tests Variable DF t Value Pr > |t| htdiff 971 -2.05 0.0404 /*One-sample t-test to test whether mean of htdiff=0, using Proc Univariate*/ proc univariate data=b510.owen plot normal; var htdiff; histogram; run; The UNIVARIATE Procedure Variable: htdiff Moments N 972 Sum Weights 972 Mean 14.4218107 Sum Observations 14018 Std Deviation 8.78341392 Variance 77.1483601 Skewness 0.31703251 Kurtosis 0.56094005 Uncorrected SS 277076 Corrected SS 74911.0576 Coeff Variation 60.9036833 Std Error Mean 0.28172813 Basic Statistical Measures Location Variability Mean 14.42181 Std Deviation 8.78341 Median 15.00000 Variance 77.14836 Mode 15.00000 Range 68.00000 Interquartile Range 12.00000 Tests for Location: Mu0=0 Test -Statistic- -----p Value------ Student's t t 51.19052 Pr > |t| <.0001 Sign M 445 Pr >= |M| <.0001 Signed Rank S 219928 Pr >= |S| <.0001 Tests for Normality Test --Statistic--- -----p Value------ Shapiro-Wilk W 0.989839 Pr < W <0.0001 Kolmogorov-Smirnov D 0.071494 Pr > D <0.0100 Cramer-von Mises W-Sq 0.364574 Pr > W-Sq <0.0050 Anderson-Darling A-Sq 2.035331 Pr > A-Sq <0.0050 Quantiles (Definition 5) Quantile Estimate 100% Max 56 99% 37 95% 29 90% 25 75% Q3 20 50% Median 15 25% Q1 8 10% 3 5% 0 1% -5 0% Min -12 Extreme Observations ----Lowest---- ----Highest--- Value Obs Value Obs -12 13 40 839 -7 112 41 305 -7 111 41 459 -6 701 52 879 -6 440 56 125 Missing Values -----Percent Of----- Missing Missing Value Count All Obs Obs . 34 3.38 100.00 Histogram # Boxplot 57.5+* 1 0 .* 1 0 . .* 4 0 .** 8 0 .******* 34 | .**************** 76 | 22.5+****************************** 146 +-----+ .*********************************************** 231 *-----* .******************************************* 213 | + | .**************************** 140 +-----+ .******************* 92 | .***** 21 | .* 4 | -12.5+* 1 0 ----+----+----+----+----+----+----+----+----+-- * may represent up to 5 counts Normal Probability Plot 57.5+ * | * | | * | ***+ | ******+ | ******+ 22.5+ ******+ | ******* | ******* | ******* | ********+ |******+++ |*++ -12.5+* +----+----+----+----+----+----+----+----+----+----+ -2 -1 0 +1 +2  /*One-sample t-test to test whether mean of htdiff=15, using Proc Univariate*/ proc univariate data=b510.owen mu0=15; var htdiff; run; Moments N 972 Sum Weights 972 Mean 14.4218107 Sum Observations 14018 Std Deviation 8.78341392 Variance 77.1483601 Skewness 0.31703251 Kurtosis 0.56094005 Uncorrected SS 277076 Corrected SS 74911.0576 Coeff Variation 60.9036833 Std Error Mean 0.28172813 Basic Statistical Measures Location Variability Mean 14.42181 Std Deviation 8.78341 Median 15.00000 Variance 77.14836 Mode 15.00000 Range 68.00000 Interquartile Range 12.00000 Tests for Location: Mu0=0 Test -Statistic- -----p Value------ Student's t t 51.19052 Pr > |t| <.0001 Sign M 445 Pr >= |M| <.0001 Signed Rank S 219928 Pr >= |S| <.0001     PAGE  PAGE 8 Check the test for equality of variances first. 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