ANOVA PROC ANOVA option CLASS variables MODEL dependents

ANOVA 절차(일원 배치법) PROC ANOVA <option> ; CLASS variables ; MODEL dependents = effects </options> ; MEANS effects/options ; 예제 6. 1) /* ANOVA 1. SAS : ONE-WAY LAYOUT */ DATA WEIGHT ; INPUT DIET $ GAIN @@ ; CARDS ; A 5. 6 B 4. 8 C 5. 2 A 6. 0 B 6. 1 C 5. 0 A 5. 7 B 4. 9 C 4. 4 A 6. 4 B 5. 3 C 4. 6 ; RUN ; PROC ANOVA ; CLASS DIET ; MODEL GAIN = DIET ; MEANS DIET ; RUN ; b

ANOVA 절차(이원 배치법) PROC ANOVA <option> ; CLASS variable 1 variable 2 ; MODEL dependents = variable 1 variable 2 </options> ; 예제 6. 2) /* ANOVA 2. SAS : TWO-WAY LAYOUT */ DATA FERTIL ; INPUT BLOCK $ TRTMENT $ YIELD WORTH @@ ; CARDS ; 1 A 32. 6 112 1 B 36. 4 130 1 C 29. 5 106 2 A 4 2. 7 139 2 B 47. 1 143 2 C 32. 9 112 3 A 35. 3 124 3 B 40. 1 134 3 C 33. 6 116 ; RUN ; PROC ANOVA ; CLASS BLOCK TRTMENT ; MODEL YIELD WORTH = BLOCK TRTMENT ; RUN ; b

b 예제 6. 1) /* ANOVA 3. SAS : ONE-WAY LAYOUT : MULTIPLE COMPARISION */ DATA WEIGHT ; INPUT DIET $ GAIN @@ ; CARDS ; A 5. 6 B 4. 8 C 5. 2 A 6. 0 B 6. 1 C 5. 0 A 5. 7 B 6. 1 C 4. 4 A 6. 4 B 5. 3 C 4. 6 ; RUN ; PROC ANOVA ; CLASS DIET ; MODEL GAIN=DIET ; MEANS DIET / LSD DUNCAN TUKEY ALPHA=. 1 ; RUN ;

b 예제 6. 2) /* ANOVA 4. SAS : TWO-WAY LAYOUT : MULTIPLE COMPARISION */ DATA FERTIL ; INPUT BLOCK $ TRTMENT $ YIELD WORTH @@ ; CARDS ; 1 A 32. 6 112 1 B 36. 4 130 1 C 29. 5 106 2 A 4 2. 7 139 2 B 47. 1 143 2 C 32. 9 112 3 A 35. 3 124 3 B 40. 1 134 3 C 33. 6 116 ; RUN ; PROC ANOVA ; CLASS BLOCK TRTMENT ; MODEL YIELD = BLOCK TRTMENT ; MEANS TRTMENT / LSD DUNCAN TUKEY ALPHA=. 1 ; RUN ;

요인계획법 b 이요인 계획법(반복이 있는 이원배치법) b 다요인 계획법 /* ANOVA 5. SAS : TWO-WAY LAYOUT */ DATA DDD ; INPUT GROUP $ DRUG $ SCORE @@ ; CARDS ; N P 50 N R 67 N P 45 N R 60 N P 55 N R 58 N P 52 N R 65 H P 70 H R 51 H P 72 H R 57 H P 68 H R 48 H P 75 H R 55 ; RUN ; PROC ANOVA ; CLASS GROUP DRUG ; MODEL SCORE=GROUP DRUG GROUP*DRUG ; MEANS GROUP DRUG GROUP*DRUG ; RUN ;

예제 6. 4) /* ANOVA 6. SAS : THREE-WAY FACTORIAL DESIGN */ DATA DDD ; INPUT GROUP $ DRUG $ SEX $ SCORE @@ ; CARDS ; N P M 50 N R M 67 N P F 45 N R F 60 N P M 55 N R M 58 N P F 52 N R F 65 H P M 70 H R M 51 H P F 72 H R F 57 H P M 68 H R M 48 H P F 75 H R F 55 ; RUN ; PROC ANOVA ; CLASS SEX GROUP DRUG ; MODEL SCORE=GROUP DRUG SEX*GROUP SEX DRUG GROUP*DRUG ; MEANS GROUP DRUG SEX*GROUP SEX*DRUG GROUP*DRUG ; RUN ;

예제 6. 5) DATA TUMOUR ; INPUT SEX $ TEMP $ W 1 W 2 W 3 @@ ; CARDS ; M 4 18. 15 16. 51 0. 24 M 20 21. 27 23. 30 … ; RUN ; PROC ANOVA ; CLASS SEX TEMP ; MODEL W 1 W 2 W 3 = SEX TEMP SEX*TEMP ; MANOVA H=_ALL_ ; RUN ; b

b 예제 6. 6) 반복측정된 자료의 분석 프로그램 DATA REPEAT ; INPUT GROUP $ PRETEST POSTTEST @@ ; CARDS ; C 80 83 C 85 86 C 83 88 T 82 94 T 87 93 T 84 98 ; RUN ; PROC ANOVA ; CLASS GROUP ; MODEL PRETEST POSTTEST = GROUP ; REPEATED TIME 2(0 1) ; RUN ;

b 예제 ) 대응 비교로 분석한 프로그램 DATA REPEAT ; INPUT GROUP $ PRETEST POSTTEST @@ ; DIFF = POSTTEST-PRETEST ; CARDS ; C 80 83 C 85 86 C 83 88 T 82 94 T 87 93 T 84 98 ; RUN ; PROC TTEST ; CLASS GROUP ; VAR DIFF ; RUN ;

b 예제 ) 반복측정된 자료를 분석하기 위한 프로그램 DATA REPEAT 1 ; INPUT SUBJ GROUP $ TIME TEST @@ ; CARDS; 1 C 1 80 1 C 2 83 2 C 1 85 2 C 2 86 3 C 1 83 3 C 2 88 1 T 1 82 1 T 2 94 2 T 1 87 2 T 2 93 3 T 1 84 3 T 2 98 ; RUN ; PROC ANOVA ; CLASS GROUP SUBJ TIME ; MODEL TEST = GROUP SUBJ(GROUP) TIME GROUP*TIME ; TEST H=GROUP E = SUBJ(GROUP) ; RUN;