! !************************************************************************ ! ! GLIM DATA SETS AND MACROS FOR THE BOOK 'STATISTICAL MODELLING IN GLIM' ! ! Revision 1.1 3/7/89 Amendments to macro XPRM in subfile PIECE !************************************************************************ $RETURN ! $SUBFILE SOLV ! ! DATA FROM SCHOOL OF BEHAVIOURAL SCIENCES,MACQUARIE UNIVERSITY ! $UNITS 24 $DATA TIME EFT$READ 317 59 464 33 525 49 298 69 491 65 196 26 268 29 372 62 370 31 739 139 430 74 410 31 342 48 222 23 219 9 513 128 295 44 285 49 408 87 543 43 298 55 494 58 317 113 407 7 ! $CALC GROUP=%GL(2,12) $FACTOR GROUP 2$ ! ! ! TIME - IS THE TIME TAKEN TO SOLVE FOUR BLOCK DESIGN PROBLEMS ! BY 24 FIFTH-GRADE CHILDREN (12 BOYS + 12 GIRLS) ! EFT - VALUE FOR THE EMBEDDED FIGURES TEST,MEASURE OF DIFFICULTY ! IN ABSTRACTING LOGICAL STRUCTURE OF A PROBLEM FROM ! ITS CONTEXT ! GROUP- CLASSIFICATION BY TYPE OF PROBLEMS PRESENTED FIRST ! I.E. THOSE SOLVED BY ROW (GROUP 1) OR ! FORMATION STRATEGY ! ! $RETURN ! !************************************************************************ ! $SUBFILE BRONCHITIS ! ! CARDIFF CHRONIC BRONCHITIS DATA ! REPRODUCED FROM ! 'INTRODUCTION TO THE USE OF LOGIT MODELS IN GEOGRAPHY' ! BY NEIL WRIGLEY (1976) ! $UNITS 212 $DATA R CIG POLL$ $READ 0 5.15 67.1 1 0.0 66.9 0 2.5 66.7 0 1.75 65.8 0 6.75 64.4 0 0.0 64.4 1 0.0 65.1 1 9.5 66.2 0 0.0 65.9 0 0.75 67.1 0 5.25 67.9 1 8 68.1 1 5.15 67 1 30.0 66.3 0 0.0 65.7 0 0.0 65.2 0 5.25 64.2 0 10.05 64.6 0 0.0 63.5 1 3.4 63.0 0 0.0 62.7 0 .55 62.7 1 9.5 62.1 1 12.5 63.7 0 0.0 63.1 0 3.4 63 0 2.2 62.7 0 6.7 63.1 0 1.1 62.4 0 1.8 64.4 0 0.0 64.2 1 3.6 64.2 0 1.6 63 0 6.2 62.2 0 14.75 62.3 0 .35 63.7 1 13.75 63.8 0 0.0 63.1 1 7.5 62.7 0 1.0 62.9 0 0.0 62.5 1 14.8 61.7 1 3.5 61.6 0 0.0 61.6 0 0.0 61.4 0 .25 61.4 0 1.55 62 1 0.0 61.8 0 0.0 60.9 0 5.9 60.8 0 16.45 60.6 0 2.65 62.9 1 12.5 62.6 0 0.0 62.1 0 14.55 61.7 1 11 61 1 6.75 62.7 0 0.0 62.7 1 0.0 61.7 0 1.75 60.9 0 2.4 60.6 0 10.05 60.4 1 12.75 61.7 0 0.0 61.9 0 5 61.3 0 .6 60.7 0 0.0 60.8 0 .85 60.5 0 .9 59.7 0 .0 59.5 1 8.75 59.6 0 .8 59.1 1 6.6 59.4 0 1.0 58.5 0 0.0 60 1 8.15 59.8 0 0.0 59.7 1 5 59.4 0 2.55 59.2 0 1.2 58.6 0 0.0 60.8 1 11.25 60.4 0 0.0 60.2 0 2 60 0 1.9 59.4 0 .45 59.8 1 0.0 59.7 0 0.0 59.0 1 6.9 59.0 0 2.35 58.6 0 3.95 59.7 0 .6 59.6 1 15 59.4 0 0.0 59.4 0 .95 59.4 0 0.0 59.3 0 1.4 54.2 0 .5 54.0 0 .6 53.8 0 0.0 53.7 0 2.45 53.7 0 1.75 53.1 0 0.0 54.4 0 3.1 54.2 0 10.05 53.9 0 .55 53.2 0 .85 53.2 0 1.1 54.9 0 0.0 54.9 0 0.0 54.5 0 1.45 54.2 0 2.05 54.2 1 10.5 54 0 .5 55.8 1 9.2 55.5 0 .55 55.6 0 0.0 55.5 0 0.96 54.9 0 1 54.6 0 0.0 56.9 0 5.25 56.4 1 0 55.9 0 9 55.8 0 1.6 55.6 1 10.9 57.6 0 0.0 57.7 0 0 57.6 0 2.25 57.8 0 2.65 57.8 0 .55 58.4 0 0 58.2 1 4.5 58 0 15 58.1 0 0 57.9 0 0 57.3 0 4.2 58.3 0 .55 58.1 1 10 57.9 0 0 57.6 0 7.1 57.3 0 3.2 57.1 1 0 58.9 1 6.8 58.6 0 0 58.7 0 0 57.5 0 2.35 57.2 0 24.9 58 0 2.65 57.9 1 3.7 57.2 0 17.1 57.3 0 0 57.5 0 .95 57.2 0 10.05 53.1 0 1.15 53 1 18.25 53 0 10 52.9 0 .75 52.6 0 0 53.1 0 4.2 53 0 .8 52.9 0 .55 52.7 0 .95 52.6 0 0 52.1 0 3.1 54.1 0 .8 53.7 0 1.55 53.1 0 .4 53.3 0 6.2 53 0 .6 53 0 .4 53.9 1 7.5 53.7 0 7.15 53.4 0 .25 53.2 0 3.6 53.4 0 .95 53.2 0 2.8 54.9 1 20.25 54.9 0 .95 54.6 0 4.25 54.1 0 4.15 54.2 0 10 57.4 0 3.4 57.3 0 0.0 57.3 0 3.6 56.7 0 .9 56.5 0 0.0 56.8 0 0 56.6 1 6.4 56.5 0 .95 56.3 0 1.06 56.3 0 13.3 56.2 0 1.1 56.6 0 17.2 55.9 0 1.65 56 1 5 55.8 0 2.1 55.7 0 .6 57 1 8.25 56.7 0 .9 56.4 0 0.0 56.5 1 12.3 55.2 0 1.15 56.9 0 2.2 56.7 0 3.6 56 1 10 55.5 0 0.6 55.3 0 9.5 56.5 0 .7 56.3 1 9 56.1 0 0 55.9 0 .5 55.5 0 .9 55.4 $CALC N=1 ! VARIABLES ! R CHRONIC BRONCHITIS (1=YES,0=NO) ! N (BINOMIAL DENOMINATOR..1 FOR ALL RESPONDENTS) ! CIG CIGARETTE CONSUMPTION ! POLL SMOKE LEVEL OF LOCALITY OF RESPONDENTS HOME $RETURN ! !************************************************************************ ! $SUBFILE GHQ ! !.................................................................. ! Reproduced by permission of the Royal Statistical Society ! Silvapulle, M J (1981), JRSS B, 43, 310-313 !.................................................................. $UNIT 17 $DATA GHQ C NC$ $READ 0 0 18 1 0 8 2 1 1 4 1 0 5 3 0 7 2 0 10 1 0 0 2 42 1 2 14 2 4 5 3 3 1 4 2 1 5 3 0 6 1 0 7 1 0 8 3 0 9 1 0 $CALC I=%GL(17,1) : SEX=%IF(%LE(I,7),1,2) $FACTOR SEX 2$ $CALC N=C+NC$ $RETURN ! !************************************************************************ ! $SUBFILE VASO !.................................................................. ! Reproduced by permission of the Biometrika Trustees ! Finney, D.J. (1947) Biometrika,34,320-334 !.................................................................. ! $UNIT 39$DATA VOL RATE RESP $READ 3.7 .825 1 3.5 1.09 1 1.25 2.5 1 .75 1.5 1 .8 3.2 1 .7 3.5 1 .6 .75 0 1.1 1.7 0 .9 .75 0 .9 .45 0 .8 .57 0 .55 2.75 0 .6 3.0 0 1.4 2.33 1 .75 3.75 1 2.3 1.64 1 3.2 1.6 1 .85 1.415 1 1.7 1.06 0 1.8 1.8 1 .4 2.0 0 .95 1.36 0 1.35 1.35 0 1.5 1.36 0 1.6 1.78 1 .6 1.5 0 1.8 1.5 1 .95 1.9 0 1.9 .95 1 1.6 .4 0 2.7 .75 1 2.35 .03 0 1.1 1.83 0 1.1 2.2 1 1.2 2.0 1 0.8 3.33 1 .95 1.9 0 .75 1.9 0 1.3 1.625 1 ! ! VARIABLES: ! VOL VOLUME OF AIR INSPIRED ! RATE RATE OF AIR INSPIRED ! RESP RESPONSE (1= OCCURENCE OF VASO-CONSTRICTION ! 2=NON-OCCURENCE OF " "" ) $RETURN ! !************************************************************************ ! $SUBFILE TREES ! ! USABLE WOOD IN CHERRY TREES. !.................................................................. ! Reproduced by permission of the Duxbury Press ! Ryan, T., Joiner, B. and Ryan B. (1976) ! Minitab Student Handbook !.................................................................. ! $UNIT 31 $DATA D H V $READ 8.3 70 10.3 8.6 65 10.3 8.8 63 10.2 10.5 72 16.4 10.7 81 18.8 10.8 83 19.7 11.0 66 15.6 11.0 75 18.2 11.1 80 22.6 11.2 75 19.9 11.3 79 24.2 11.4 76 21.0 11.4 76 21.4 11.7 69 21.3 12.0 75 19.1 12.9 74 22.2 12.9 85 33.8 13.3 86 27.4 13.7 71 25.7 13.8 64 24.9 14.0 78 34.5 14.2 80 31.7 14.5 74 36.3 16.0 72 38.3 16.3 77 42.6 17.3 81 55.4 17.5 82 55.7 17.9 80 58.3 18.0 80 51.5 18.0 80 51.0 20.6 87 77.0 ! ! VARIABLES: ! D- DIAMETER (IN INCHES) OF 31 CHERRY TREES ! AT A HEIGHT OF 4.5 FEET FROM THE GROUND ! ! H- HEIGHT IN FEET OF THE TREES ! ! V- VOLUME OF USEABLE WOOD IN CUBIC FEET ! $RETURN ! !************************************************************************ ! $SUBFILE POIS ! ! SURVIVAL TIMES OF ANIMALS AFTER POISONING TREATMENT !.................................................................. ! Reproduced by permission of the Royal Statistical Society ! Box, G.E.P and Cox, D.R. (1964), JRSS B, 26, 211-252 !.................................................................. ! $UNITS 48 $DATA TIME TYPE TREAT $FACTOR TYPE 3 TREAT 4 $READ 0.31 1 1 0.45 1 1 0.46 1 1 0.43 1 1 0.82 1 2 1.1 1 2 0.88 1 2 0.72 1 2 0.43 1 3 0.45 1 3 0.63 1 3 0.76 1 3 0.45 1 4 0.71 1 4 0.66 1 4 0.62 1 4 0.36 2 1 0.29 2 1 0.4 2 1 0.23 2 1 0.92 2 2 0.61 2 2 0.49 2 2 1.24 2 2 0.44 2 3 0.35 2 3 0.31 2 3 0.4 2 3 0.56 2 4 1.02 2 4 0.71 2 4 0.38 2 4 0.22 3 1 0.21 3 1 0.18 3 1 0.23 3 1 0.3 3 2 0.37 3 2 0.38 3 2 0.29 3 2 0.23 3 3 0.25 3 3 0.24 3 3 0.22 3 3 0.3 3 4 0.36 3 4 0.31 3 4 0.33 3 4 ! VARIABLES: ! TIME SURVIVAL TIME OF RATS ! TREAT TREATMENT (1-4) ! TYPE TYPE OF POISON $RETURN ! !************************************************************************ ! $SUBFILE CAR1 ! PETROL CONSUMPTION DATA !.................................................................. ! Reproduced from: ! M.V.Henderson and P.F. Velleman, "Building Multiple Regression Models ! Interactively". BIOMETRICS 37: 391-411. 1981 ! With permission from the Biometric Society. !.................................................................. ! $UNITS 32$ $DATA S C T G DISP HP CB DRAT WT QMT MPG $ $READ 0 6 1 4 160.0 110 4 3.90 2620 16.46 21.0 !MAZDA RX-4 0 6 1 4 160.0 110 4 3.90 2875 17.02 21.0 !MAZDA RX-4 WAGON 1 4 1 4 108.0 93 1 3.85 2320 18.61 22.8 !DATSUN 710 1 4 0 3 258.0 110 1 3.08 3215 19.44 21.4 !HORNET 4 DRIVE 0 8 0 3 360.0 175 2 3.15 3440 17.02 18.7 !HORNET SPORTABOUT 1 6 0 3 225.0 105 1 2.76 3460 20.22 18.1 !VALIANT 0 8 0 3 360.0 245 4 3.21 3570 15.84 14.3 !DUSTER 360 1 4 0 4 146.7 62 2 3.69 3190 20.00 24.4 !MERCEDES 240D 1 4 0 4 140.8 95 2 3.92 3150 22.90 22.8 !MERCEDES 230 1 6 0 4 167.6 123 4 3.92 3440 18.30 19.2 !MERCEDES 280 1 6 0 4 167.6 123 4 3.92 3440 18.90 17.8 !MERCEDES 280C 0 8 0 3 275.8 180 3 3.07 4070 17.40 16.4 !MERCEDES 450SE 0 8 0 3 275.8 180 3 3.07 3730 17.60 17.3 !MERCEDES 450SL 0 8 0 3 275.8 180 3 3.07 3780 18.00 15.2 !MERCEDES 450SLC 0 8 0 3 472.0 205 4 2.93 5250 17.98 10.4 !CADILLAC FLEETWOOD 0 8 0 3 460.0 215 4 3.00 5425 17.82 10.4 !LINCOLN CONTINENTAL 0 8 0 3 440.0 230 4 3.23 5345 17.42 14.7 !IMPERIAL 1 4 1 4 78.7 66 1 4.08 2200 19.47 32.4 !FIAT 128 1 4 1 4 75.7 52 2 4.93 1615 18.52 30.4 !HONDA CIVIC 1 4 1 4 71.1 65 1 4.22 1835 19.90 33.9 !TOYOTA COROLLA 1 4 0 3 120.1 97 1 3.70 2465 20.01 21.5 !TOYOTA CORONA 0 8 0 3 318.0 150 2 2.76 3520 16.87 15.5 !DODGE CHALLENGER 0 8 0 3 304.0 150 2 3.15 3435 17.30 15.2 !AMC JAVELIN 0 8 0 3 350.0 245 4 3.73 3840 15.41 13.3 !CHEVROLET CAMARO Z-28 0 8 0 3 400.0 175 2 3.08 3845 17.05 19.2 !PONTIAC FIREBIRD 1 4 1 4 79.0 66 1 4.08 1935 18.90 27.3 !FIAT X1-9 0 4 1 5 120.3 91 2 4.43 2140 16.70 26.0 !PORSCHE 914-2 1 4 1 5 95.1 113 2 3.77 1513 16.90 30.4 !LOTUS EUROPA 0 8 1 5 351.0 264 4 4.22 3170 14.50 15.8 !FORD PANTERA L 0 6 1 5 145.0 175 6 3.62 2770 15.50 19.7 !FERRARI DINO 1973 0 8 1 5 301.0 335 8 3.54 3570 14.60 15.0 !MASERATI BORA 1 4 1 4 121.0 109 2 4.11 2780 18.60 21.4 !VOLVO 142E $CA WT=WT/1000 ! S SHAPE OF ENGINE (1 = STRAIGHT,0 = VEE) ! C NO. OF CYLINDERS ! T TRANSMISSION TYPE (0= AUTOMATIC,1=MANUAL) ! G NO. OF GEARS ! DISP ENGINE DISPLACEMENT IN CUBIC INCHES ! HP HORSEPOWER OF CAR ! CB NO. OF CARBURETTOR BARRELS ! DRAT DRIVE RATIO ! WT WEIGHT OF CAR/1000 ! QMT QUARTER-MILE TIME ! MPG PETROL CONSUMPTION IN MILES PER GALLON $RETURN ! !************************************************************************ ! $SUBFILE KULLBACK ! ! CORONARY HEART DISEASE STUDY !.................................................................. ! Reproduced by permission of the American Statistical Association ! from Ku,H.H. and Kullback,S. ,American Statistician,1974,28,p117 !.................................................................. ! ! $UNITS 16 $DATA R N$ $READ 2 119 3 124 3 50 4 26 3 88 2 100 0 43 3 23 8 127 11 220 6 74 6 49 7 74 12 111 11 57 11 44 $FACTOR CHOL 4 BP 4 $CA CHOL=%GL(4,4) : BP=%GL(4,1) ! VARIABLES: ! N NO. OF SUBJECTS IN EACH GROUP ! R NO. OF SUBJECTS DIAGNOSED AS HAVING CORONARY HEART ! DISEASE ! CHOL SERUM CHOLESTEROL IN MG/100CC ! 1= <200, 2= 200-219,3=220-259,4=260+ ! BP BLOOD PRESSURE IN MM MERCURY ! 1= <127, 2=127-146,3=147-166,4=167+ $RETURN ! !************************************************************************ ! $SUBFILE BYSSINOSIS ! BYSSINOSIS DATA .... ! NO. OF COTTON WORKERS SUFFERING FROM BYSSINOSIS !.................................................................. ! Reproduced by permission of the International Statistical Inst. ! Higgins,J.E. and Koch,G.G.,International Statist. Review,45,p51-62 !.................................................................. ! $UNITS 72 $DATA YES NO$ $READ 3 37 0 74 2 258 25 139 0 88 3 242 0 5 1 93 3 180 2 22 2 145 3 260 0 16 0 35 0 134 6 75 1 47 1 122 0 4 1 54 2 169 1 24 3 142 4 301 8 21 1 50 1 187 8 30 0 5 0 33 0 0 1 33 2 94 0 0 0 4 0 3 2 8 1 16 0 58 1 9 0 0 0 7 0 0 0 30 1 90 0 0 0 4 0 4 31 77 1 141 12 495 10 31 0 1 0 45 0 1 3 91 3 176 0 1 0 0 0 2 5 47 0 39 3 182 3 15 0 1 0 23 0 2 3 187 2 340 0 0 0 2 0 3 $FACT DUST 3 RACE 2 SEX 2 SMOK 2 EMP 3$ $CA DUST=%GL(3,1):RACE=%GL(2,3):SEX=%GL(2,6):SMOK=%GL(2,12) :EMP=%GL(3,24)$ ! ! VARIABLES: ! YES NO. OF COTTON WORKERS SUFFERING FROM BYSSINOSIS ! NO NO. OF COTTON WORKERS NOT SUFFERING FROM BYSSINOSIS ! DUST DUSTINESS OF WORKPLACE(1=HIGH,2=MEDIUM,3=LOW) ! RACE RACE OF WORKER(1=WHITE,2=OTHER) ! SEX SEX OF WORKER(1=MALE,2=FEMALE) ! SMOK SMOKING HABIT(1=SMOKER,2=NON-SMOKER) ! EMP LENGTH OF EMPLOYMENT IN YEARS(1= <10,2=10-20,3= >20YRS) ! $RETURN ! !************************************************************************ ! $SUBFILE VIETNAM ! ! SURVEY OF STUDENT OPINION ON THE VIETNAM WAR, UNIVERSITY OF ! NORTH CAROLINA AT CHAPEL HILL, MAY 1967 ! POLICIES : ! A- DEFEAT POWER OF VIETNAM BY WIDESPREAD BOMBING ! AND LAND INVASION ! B- FOLLOW THE PRESENT POLICY ! ! C- WITHDRAW TROOPS TO STRONG POINTS AND OPEN ! NEGOTIATIONS ON ELECTIONS INVOLVING THE VIETCONG ! D- IMMEDIATE WITHDRAWAL OF ALL U.S. TROOPS ! ! EXPLANATORY VARIABLES : SEX=1 MALE ! =2 FEMALE ! YEAR=1,2,3,4 UNDERGRADUATE ! =5 GRADUATE ! $UNIT 10 ! $DATA A B C D ! $READ ! 175 116 131 17 ! 160 126 135 21 ! 132 120 154 29 ! 145 95 185 44 ! 118 176 345 141 ! ! 13 19 40 5 ! 5 9 33 3 ! 22 29 110 6 ! 12 21 58 10 ! 19 27 128 13 ! ! $FACTOR SEX 2 YEAR 5 $ $CALC SEX=%GL(2,5) : YEAR=%GL(5,1) $ $RETURN ! !************************************************************************ ! $SUBFILE MINERS ! ! DATA ON PNEUMOCONIOSIS FOR COALMINERS !.................................................................. ! Reproduced from ! J.A.Ashford, "An approach to the Analysis of Data for Semi-quantal ! Responses in Biological Response". BIOMETRICS 15: 573-581 1959 ! With permission from the Biometric Society. !.................................................................. ! ! N=NORMAL, M=MILD, S=SEVERE PNEUMOCONIOSIS ! $UNIT 8 $DATA N M S $READ 98 0 0 51 2 1 34 6 3 35 5 8 32 10 9 23 7 8 12 6 10 4 2 5 $FACTOR P 8 $CALC P=%GL(8,1) : YEARS=5.8*%EQ(P,1)+15*%EQ(P,2)+21.5*%EQ(P,3)+27.5*%EQ(P,4)+ 33.5*%EQ(P,5)+39.5*%EQ(P,6)+46*%EQ(P,7)+51.5*%EQ(P,8) $ $RETURN ! !************************************************************************ ! $SUBFILE TOXAEMIA !.................................................................. ! Reproduced by permission of the Royal Statistical Society ! Brown,P.J.,Stone,J. and Ord-Smith,C(1983),Appl. Statist.,32,69-72 !.................................................................. ! $UNITS 15 $DATA HU HN NU NN$READ 28 82 21 286 5 24 5 71 1 3 0 13 50 266 34 785 13 92 17 284 0 15 3 34 278 1101 164 3160 120 492 142 2300 16 92 32 383 63 213 52 656 35 129 46 649 7 40 12 163 20 78 23 245 22 74 34 321 7 14 4 65 $FAC CLASS 5 SMOK 3$ $CAL CLASS=%GL(5,3):SMOK=%GL(3,1)$ ! ! Variables: ! ! SMOK Number of cigarettes smoked per day by mother during ! pregnancy ! CLASS Social class of mother (I to V) ! ! Toxaemic signs exhibited by mother during pregnancy ! ! HU Hypertension and protein urea ! NU protein urea only ! HN Hypertension only ! NN neither sign exhibited ! $RETURN ! !************************************************************************ ! $SUBFILE CLAIMS ! ! CLAIM FREQUENCY DATA FROM BAXTER ET AL (1980) ! Proceedings of the 21st International Congress of Actuaries,11-29 ! $UNIT 64 $DATA N C $ $READ 197 38 264 35 246 20 1680 156 284 63 536 84 696 89 3582 400 133 19 286 52 355 74 1640 233 24 4 71 18 99 19 452 77 85 22 139 19 151 22 931 87 149 25 313 51 419 49 2443 290 66 14 175 46 221 39 1110 143 9 4 48 15 72 12 322 53 35 5 73 11 89 10 648 67 53 10 155 24 240 37 1635 187 24 8 78 19 121 24 692 101 7 3 29 2 43 8 245 37 20 2 33 5 40 4 316 36 31 7 81 10 122 22 724 102 18 5 39 7 68 16 344 63 3 0 16 6 25 8 114 33 $FACTOR DISTRICT 4 CAR 4 AGE 4 $ $CA DIST=%GL(4,16) : CAR=%GL(4,4) : AGE=%GL(4,1) $ ! ! AGE IS POLICYHOLDER'S AGE ! $RETURN ! !************************************************************************ ! $SUBFILE QUINE ! $UNITS 146 $DATA DAYS C S A L $ $FACT C 2 S 2 A 4 L 2$ $READ 2 1 1 1 1 11 1 1 1 1 14 1 1 1 1 5 1 1 1 2 5 1 1 1 2 13 1 1 1 2 20 1 1 1 2 22 1 1 1 2 6 1 1 2 1 6 1 1 2 1 15 1 1 2 1 7 1 1 2 2 14 1 1 2 2 6 1 1 3 1 32 1 1 3 1 53 1 1 3 1 57 1 1 3 1 14 1 1 3 2 16 1 1 3 2 16 1 1 3 2 17 1 1 3 2 40 1 1 3 2 43 1 1 3 2 46 1 1 3 2 8 1 1 4 2 23 1 1 4 2 23 1 1 4 2 28 1 1 4 2 34 1 1 4 2 36 1 1 4 2 38 1 1 4 2 3 1 2 1 1 5 1 2 1 2 11 1 2 1 2 24 1 2 1 2 45 1 2 1 2 5 1 2 2 1 6 1 2 2 1 6 1 2 2 1 9 1 2 2 1 13 1 2 2 1 23 1 2 2 1 25 1 2 2 1 32 1 2 2 1 53 1 2 2 1 54 1 2 2 1 5 1 2 2 2 5 1 2 2 2 11 1 2 2 2 17 1 2 2 2 19 1 2 2 2 8 1 2 3 1 13 1 2 3 1 14 1 2 3 1 20 1 2 3 1 47 1 2 3 1 48 1 2 3 1 60 1 2 3 1 81 1 2 3 1 2 1 2 3 2 0 1 2 4 2 2 1 2 4 2 3 1 2 4 2 5 1 2 4 2 10 1 2 4 2 14 1 2 4 2 21 1 2 4 2 36 1 2 4 2 40 1 2 4 2 6 2 1 1 1 17 2 1 1 1 67 2 1 1 1 0 2 1 1 2 0 2 1 1 2 2 2 1 1 2 7 2 1 1 2 11 2 1 1 2 12 2 1 1 2 0 2 1 2 1 0 2 1 2 1 5 2 1 2 1 5 2 1 2 1 5 2 1 2 1 11 2 1 2 1 17 2 1 2 1 3 2 1 2 2 4 2 1 2 2 22 2 1 3 1 30 2 1 3 1 36 2 1 3 1 0 2 1 3 2 1 2 1 3 2 5 2 1 3 2 7 2 1 3 2 8 2 1 3 2 16 2 1 3 2 27 2 1 3 2 0 2 1 4 2 10 2 1 4 2 14 2 1 4 2 27 2 1 4 2 30 2 1 4 2 41 2 1 4 2 69 2 1 4 2 25 2 2 1 1 10 2 2 1 2 11 2 2 1 2 20 2 2 1 2 33 2 2 1 2 0 2 2 2 1 1 2 2 2 1 5 2 2 2 1 5 2 2 2 1 5 2 2 2 1 5 2 2 2 1 5 2 2 2 1 7 2 2 2 1 7 2 2 2 1 11 2 2 2 1 15 2 2 2 1 5 2 2 2 2 6 2 2 2 2 6 2 2 2 2 7 2 2 2 2 14 2 2 2 2 28 2 2 2 2 0 2 2 3 1 2 2 2 3 1 2 2 2 3 1 3 2 2 3 1 5 2 2 3 1 8 2 2 3 1 10 2 2 3 1 12 2 2 3 1 14 2 2 3 1 1 2 2 3 2 1 2 2 4 2 3 2 2 4 2 3 2 2 4 2 5 2 2 4 2 9 2 2 4 2 15 2 2 4 2 18 2 2 4 2 22 2 2 4 2 22 2 2 4 2 37 2 2 4 2 $RETURN ! !************************************************************************ ! $SUBFILE STAN ! ! STANFORD HEART TRANSPLANT DATA.. AITKIN,LAIRD & FRANCIS(1983) !.................................................................. ! Reproduced by permission of the American Statistical Association ! Crowley, J and Hu,M. (1977) ! Journal of the American Statistical Association, 72, 27-36 !.................................................................. ! $UNIT 65 $DATA ID ZA ZB AGE SURG ACC DIED SURV NMM HLA MM REJ $READ 3 0 1 54 0 0 1 15 2 0 1.11 0 4 0 1 40 0 35 1 3 3 0 1.66 0 7 0 1 50 0 50 1 624 4 0 1.32 1 10 0 1 42 0 11 1 46 2 0 .61 1 11 0 1 47 0 25 1 127 1 0 .36 0 13 0 1 54 0 16 1 61 3 0 1.89 1 14 0 1 54 0 36 1 1350 1 0 .87 1 16 0 1 49 0 27 1 312 2 0 1.12 1 18 0 1 56 0 19 1 24 3 0 2.05 0 20 0 1 55 0 17 1 10 3 1 2.76 1 21 0 1 43 0 7 1 1024 2 0 1.13 1 22 0 1 42 0 11 1 39 3 0 1.38 1 23 0 1 42 0 2 1 730 3 0 .96 1 24 0 1 58 0 82 1 136 3 1 1.62 1 25 0 1 30 0 24 0 1775 2 0 1.06 0 28 0 1 54 0 70 1 1 2 0 .47 0 30 0 1 44 0 15 1 836 4 0 1.58 1 32 0 1 64 0 16 1 60 4 0 .69 1 33 0 1 48 0 50 0 1536 3 0 .91 0 34 0 1 40 0 22 0 1549 2 0 .38 0 36 0 1 48 0 45 1 54 2 0 2.09 1 37 0 1 61 0 18 1 47 3 1 .87 1 38 0 1 41 0 4 1 0 3 0 .87 0 40 0 1 48 1 40 0 1367 4 0 .75 0 41 0 1 45 1 57 0 1264 2 0 .98 0 45 0 1 36 0 0 1 44 1 0 0.00 0 46 0 1 48 1 1 1 993 2 0 .81 1 47 0 1 47 0 20 1 51 3 0 1.38 1 49 0 1 36 1 35 0 1106 4 0 1.35 0 51 0 1 48 0 31 1 253 4 1 1.08 1 55 0 1 52 0 9 1 51 2 0 1.51 1 56 0 1 38 0 66 0 875 4 0 .98 0 58 0 1 48 1 20 1 322 2 1 1.82 1 59 0 1 41 1 77 0 838 2 0 .19 0 60 0 1 49 0 2 1 65 3 0 .66 1 63 0 1 32 0 26 0 815 3 1 1.93 0 64 0 1 48 1 32 1 551 1 0 .12 0 65 0 1 51 0 13 1 64 2 0 1.12 1 67 0 1 19 0 56 1 228 3 0 1.02 0 68 0 1 45 0 2 1 65 3 1 1.68 1 69 0 1 47 0 9 0 660 2 0 1.20 0 70 0 1 53 0 4 1 25 3 1 1.68 1 71 0 1 47 0 30 0 954 3 0 0.97 0 72 0 1 26 0 3 0 591 3 1 1.46 0 73 0 1 56 0 26 1 63 3 1 2.16 1 74 0 1 29 0 4 1 12 1 0 0.61 0 76 0 1 52 1 45 0 498 3 1 1.70 0 78 0 1 48 0 209 0 304 3 0 0.81 0 79 0 1 53 0 66 1 29 2 0 1.08 1 80 0 1 46 1 25 0 455 3 0 1.41 0 81 0 1 52 0 5 0 438 4 1 1.94 0 83 0 1 53 0 31 1 48 4 0 3.05 0 84 0 1 42 0 36 1 297 4 0 0.60 1 86 0 1 48 0 7 0 388 3 1 1.44 0 87 0 1 46 0 59 1 50 2 0 2.25 1 88 0 1 54 0 30 0 338 3 0 0.68 0 89 0 1 51 0 138 1 68 4 1 1.33 1 90 0 1 52 1 159 1 26 3 1 0.82 0 92 0 1 44 0 309 0 29 1 0 0.16 0 93 0 1 47 0 27 0 236 2 0 0.33 0 94 0 1 43 1 3 1 161 3 0 1.20 1 96 0 1 26 0 12 0 166 2 0 0.46 0 97 0 1 23 0 20 0 109 3 1 1.78 0 98 0 1 28 0 95 0 13 4 1 0.77 0 100 0 1 35 1 37 0 1 3 0 0.67 0 !~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ! ! ID ID number of patient ! ZA Censor variate for pretransplant survival. ! 1=died before transplant ! 0=transplanted or still waiting for transplant ! ZB Censor variate for waiting time to transplant ! 1=transplanted ! 0=died before transplant or still waiting for tplnt ! AGE Age at acceptance into program in years ! SURG Prior surgery (0=none,1=previous open heart surgery) ! ACC Days since January 1st,1967 to acceptance into program ! DIED Censor variate(0=Alive,1=dead) ! SURV Survival time of patient in days ! NMM Number of mismatches ! HLA HLA score ! MM Mismatch score ! REJ Rejection ! ! Recode zero survival times to 0.5 ! $CA SURV=SURV+0.5*%EQ(SURV,0)$ ! $RETURN ! !************************************************************************ ! $SUBFILE GEHAN !.................................................................. ! Reproduced by permission of the Biometrika Trustees ! Gehan, E.A (1965), Biometrika,52,203-223 !.................................................................. $UNITS 42 ! REMISSION TIMES IN ACUTE LEUKEMIA $DATA T $READ 1 1 2 2 3 4 4 5 5 8 8 8 8 11 11 12 12 15 17 22 23 6 6 6 6 7 9 10 10 11 13 16 17 19 20 22 23 25 32 32 34 35 $DATA W $READ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 0 0 1 1 0 0 0 1 1 0 0 0 0 0 ! $CA G=%GL(2,21)$FACTOR G 2 $ ! VARIABLES: ! T REMISSION TIMES IN WEEKS ! W CENSOR VARIATE (1=UNCENSORED OBSN, 0=CENSORED OBSN) ! G GROUP TREATMENT(1=PLACEBO,2=6-MERCAPTOPURINE(6-MP)) ! $RETURN ! !************************************************************************ ! $SUBFILE FEIGL ! !.................................................................. ! Reproduced from: ! P. Feigl and M. Zelen, "Estimation of Exponential Probabilities ! with Concomitant Information". BIOMETRICS 21: 826-838 1965 ! With permission from the Biometric Society. !.................................................................. ! ! SURVIVAL TIMES IN WEEKS OF PATIENTS WITH ACUTE MYELOGENEOUS ! LEUKAEMIA. COVARIATES WBC - WHITE BLOOD CELL COUNT IN THOUSANDS ! AND AG-FACTOR (1=POS, 2=NEG) $UNIT 33 $DATA TIME WBC $READ 65 2.3 156 0.75 100 4.3 134 2.6 16 6.0 108 10.5 121 10.0 4 17.0 39 5.4 143 7.0 56 9.4 26 32.0 22 35.0 1 100.0 1 100.0 5 52.0 65 100.0 56 4.4 65 3.0 17 4.0 7 1.5 16 9.0 22 5.3 3 10.0 4 19.0 2 27.0 3 28.0 8 31.0 4 26.0 3 21.0 30 79.0 4 100.0 43 100.0 ! $CALC AG=1+%GE(%CU(1),18) $FACTOR AG 2 $ $RETURN ! !************************************************************************ ! $SUBFILE PRENTICE ! ! PRENTICE LUNG CANCER DATA !.................................................................. ! Reproduced by permission of the Biometrika Trustees ! Prentice, R.L (1973), Biometrika,60,279-288 !.................................................................. ! $UNIT 137! $C THE CENSORED OBSERVATIONS APPEAR FIRST! $DATA T W MFD AGE PRIO TREA TYPE STAT $READ 100 0 6 70 1 1 1 7.0 25 0 9 52 2 1 1 8.0 123 0 3 55 1 1 2 4.0 97 0 5 67 1 1 2 6.0 182 0 2 62 1 1 4 9.0 87 0 3 48 1 2 1 8.0 231 0 8 52 2 2 1 5.0 103 0 22 36 2 2 2 7.0 83 0 3 57 1 2 3 9.9 72 1 7 69 1 1 1 6.0 411 1 5 64 2 1 1 7.0 228 1 3 38 1 1 1 6.0 126 1 9 63 2 1 1 6.0 118 1 11 65 2 1 1 7.0 10 1 5 49 1 1 1 2.0 82 1 10 69 2 1 1 4.0 110 1 29 68 1 1 1 8.0 314 1 18 43 1 1 1 5.0 42 1 4 81 1 1 1 6.0 8 1 58 63 2 1 1 4.0 144 1 4 63 1 1 1 3.0 11 1 11 48 2 1 1 7.0 30 1 3 61 1 1 2 6.0 384 1 9 42 1 1 2 6.0 4 1 2 35 1 1 2 4.0 54 1 4 63 2 1 2 8.0 13 1 4 56 1 1 2 6.0 153 1 14 63 2 1 2 6.0 59 1 2 65 1 1 2 3.0 117 1 3 46 1 1 2 8.0 16 1 4 53 2 1 2 3.0 151 1 12 69 1 1 2 5.0 22 1 4 68 1 1 2 6.0 56 1 12 43 2 1 2 8.0 21 1 2 55 2 1 2 4.0 18 1 15 42 1 1 2 2.0 139 1 2 64 1 1 2 8.0 20 1 5 65 1 1 2 3.0 31 1 3 65 1 1 2 7.5 52 1 2 55 1 1 2 7.0 287 1 25 66 2 1 2 6.0 18 1 4 60 1 1 2 3.0 51 1 1 67 1 1 2 6.0 122 1 28 53 1 1 2 8.0 27 1 8 62 1 1 2 6.0 54 1 1 67 1 1 2 7.0 7 1 7 72 1 1 2 5.0 63 1 11 48 1 1 2 5.0 392 1 4 68 1 1 2 4.0 10 1 23 67 2 1 2 4.0 8 1 19 61 2 1 3 2.0 92 1 10 60 1 1 3 7.0 35 1 6 62 1 1 3 4.0 117 1 2 38 1 1 3 8.0 132 1 5 50 1 1 3 8.0 12 1 4 63 2 1 3 5.0 162 1 5 64 1 1 3 8.0 3 1 3 43 1 1 3 3.0 95 1 4 34 1 1 3 8.0 177 1 16 66 2 1 4 5.0 162 1 5 62 1 1 4 8.0 216 1 15 52 1 1 4 5.0 553 1 2 47 1 1 4 7.0 278 1 12 63 1 1 4 6.0 12 1 12 68 2 1 4 4.0 260 1 5 45 1 1 4 8.0 200 1 12 41 2 1 4 8.0 156 1 2 66 1 1 4 7.0 143 1 8 60 1 1 4 9.0 105 1 11 66 1 1 4 8.0 103 1 5 38 1 1 4 8.0 250 1 8 53 2 1 4 7.0 100 1 13 37 2 1 4 6.0 999 1 12 54 2 2 1 9.0 112 1 6 60 1 2 1 8.0 242 1 1 70 1 2 1 5.0 991 1 7 50 2 2 1 7.0 111 1 3 62 1 2 1 7.0 1 1 21 65 2 2 1 2.0 587 1 3 58 1 2 1 6.0 389 1 2 62 1 2 1 9.0 33 1 6 64 1 2 1 3.0 25 1 36 63 1 2 1 2.0 357 1 13 58 1 2 1 7.0 467 1 2 64 1 2 1 9.0 201 1 28 52 2 2 1 8.0 1 1 7 35 1 2 1 5.0 30 1 11 63 1 2 1 7.0 44 1 13 70 2 2 1 6.0 283 1 2 51 1 2 1 9.0 15 1 13 40 2 2 1 5.0 25 1 2 69 1 2 2 3.0 21 1 4 71 1 2 2 2.0 13 1 2 62 1 2 2 3.0 87 1 2 60 1 2 2 6.0 2 1 36 44 2 2 2 4.0 20 1 9 54 2 2 2 3.0 7 1 11 66 1 2 2 2.0 24 1 8 49 1 2 2 6.0 99 1 3 72 1 2 2 7.0 8 1 2 68 1 2 2 8.0 99 1 4 62 1 2 2 8.5 61 1 2 71 1 2 2 7.0 25 1 2 70 1 2 2 7.0 95 1 1 61 1 2 2 7.0 80 1 17 71 1 2 2 5.0 51 1 87 59 2 2 2 3.0 29 1 8 67 1 2 2 4.0 24 1 2 60 1 2 3 4.0 18 1 5 69 2 2 3 4.0 31 1 3 39 1 2 3 8.0 51 1 5 62 1 2 3 6.0 90 1 22 50 2 2 3 6.0 52 1 3 43 1 2 3 6.0 73 1 3 70 1 2 3 6.0 8 1 5 66 1 2 3 5.0 36 1 8 61 1 2 3 7.0 48 1 4 81 1 2 3 1.0 7 1 4 58 1 2 3 4.0 140 1 3 63 1 2 3 7.0 186 1 3 60 1 2 3 9.0 84 1 4 62 2 2 3 8.0 19 1 10 42 1 2 3 5.0 45 1 3 69 1 2 3 4.0 80 1 4 63 1 2 3 4.0 52 1 4 45 1 2 4 6.0 164 1 15 68 2 2 4 7.0 19 1 4 39 2 2 4 3.0 53 1 12 66 1 2 4 6.0 15 1 5 63 1 2 4 3.0 43 1 11 49 2 2 4 6.0 340 1 10 64 2 2 4 8.0 133 1 1 65 1 2 4 7.5 111 1 5 64 1 2 4 6.0 231 1 18 67 2 2 4 7.0 378 1 4 65 1 2 4 8.0 49 1 3 37 1 2 4 3.0 ! $FACTOR PRIOR 2 TREAT 2 TYPE 4 $! ! VARIABLES: ! T SURVIVAL TIME IN DAYS ! STATUS PERFORMANCE STATUS ! 1,2,3 ... COMPLETELY HOSPITALIZED ! 4,5,6 ... PARTIAL CONFINEMENT ! 7,8,9 ... ABLE TO CARE FOR SELF ! MFD MONTHS FROM DIAGNOSIS TO STARTING ON STUDY ! AGE AGE IN YEARS ! PRIOR PRIOR THERAPY (1=NO,2=YES) ! TREAT TYPE OF TREATMENT(1=STANDARD,2=TEST) ! TYPE TYPE OF CANCER (1=SQUAMOUS,2=SMALL, ! 3=ADENO,4=LARGE) ! W CENSOR VARIATE (1=UNCENSORED,0=CENSORED) ! $RETURN ! !************************************************************************ ! $SUBFILE HOST ! !.................................................................. ! Reproduced by permission of McGraw Hill Ryerson Ltd. and ! Open University Educational Enterprises ! Erickson, B.H. and Nosanchuk, T.A. (1977) Understanding Data ! Open University Press, Milton Keynes !.................................................................. ! $UNITS 19 $DATA HBEF HAFT SEX$FACTOR SEX 2$READ 51 58 1 54 65 1 61 86 1 54 77 1 49 74 1 54 59 1 46 46 1 47 50 1 43 37 1 86 82 2 28 37 2 45 51 2 59 56 2 49 53 2 56 90 2 69 80 2 51 71 2 74 88 2 42 43 2 $RETURN ! !************************************************************************ ! $SUBFILE BINOMIAL ! ! FILE WITH VARIOUS BINOMIAL LIKELIHOOD MACROS ! ! $MAC RPROB $DEL LP_ DV_ P_ OF_ X_! $PR 'Profile deviance of ' *N %1 ' = ' %X ' from p = '%a' to '%z $! $CA %G=1+(%Z-%A)/%I : %C=1 : %F=%G$! $VAR %G P_ LP_ DV_$! $CA P_=%A+%CU(%I)-%I : LP_=%LOG(P_/(1-P_)) : X_=%1-%X $OFF OF_$! $OUT$TRA$! $WHILE %F RPRA$! $OUT %POC $TRA I O W F H$! $PLOT DV_ P_ '+' $! $LOOK DV_ P_ $! $OFF$DEL LP_ DV_ P_ OF_$! $$E ! $MAC RPRA $CA OF_=LP_(%C)$FIT X_-1$CA DV_(%C)=%DV : %C=%C+1 : %F=%LE(%C,%G) $! $E ! ! $MACRO LD $DEL DV_ LD_ X_ TH0_! $PRINT 'Profile deviance of LD value (p =' %p ') for ' *n %1 ' from '! %a ' to ' %z$! $CA %G= 1 +(%Z-%A)/%I : %C=1 : %F=%G : %Z1=%A$! $VAR %G DV_ LD_$! $CA TH0_=%LOG(%P/(1-%P)) : X_=%1-%A! $OFF TH0_! $OUT $TRA $! $WHILE %F LDA$! $OUT %POC$TRA I O F W H$! $PLOT DV_ LD_ '+'$! $LOOK DV_ LD_$! $DEL DV_ LD_ X_ TH0_$! $E ! $M LDA $FIT X_ -1 $CA LD_(%C)=%Z1 : DV_(%C)=%DV : %C=%C+1 : %F=%LE(%C,%G) ! : %Z1=%Z1+%I : X_=X_-%I$! $E ! ! $MACRO RELPOT $DEL DV_ TH_ X_$! $PRINT 'Profile deviance of relative potency of '*N %2 ' for '! *N %1 ' from ' %A ' to ' %Z$! $CA %G= 1 +(%Z-%A)/%I : %C=1 : %F=%G : %Z1=%A$! $VAR %G DV_ TH_$! $ARG RELA %1 %2$! $OUT $TRA $! $WHILE %F RELA$! $OUT %POC$TRA I O F W H$! $PLOT DV_ TH_ '+'$! $LOOK DV_ TH_$! $DEL DV_ TH_ X_$! $E ! $M RELA $CAL X_=%1+%Z1*%EQ(%2,2)$FIT X_ $CA TH_(%C)=%Z1 : DV_(%C)=%DV ! : %C=%C+1 : %F=%LE(%C,%G) :%Z1=%Z1+%I$! $E ! $MACRO LOGODDS $DEL DV_ LTH_ OF_ TH_$! $PRINT 'Profile deviance of logodds for ' *n %1 ' from '! %a ' to ' %z$! $CA %G= 1 +(%Z-%A)/%I : %C=1 : %F=%G :%Z1=%A$! $VAR %G DV_ TH_ LTH_ $! $CA LTH_=%A+%CU(%I)-%I$! $OFF OF_$! $ARG LOGA %1$! $OUT $TRA $! $WHILE %F LOGA$! $OUT %POC$TRA I O F W H$! $CA TH_=%EXP(LTH_)! $PLOT DV_ LTH_ '+'$! $LOOK DV_ LTH_ TH_$! $OFF$DEL DV_ LTH_ OF_ TH_$! $E ! $M LOGA $CA OF_= LTH_(%C)*%1$! $FIT $! $CALC DV_(%C)=%DV : %C=%C+1 : %F=%LE(%C,%G) $! $E ! $MACRO BINREL ! ! ! Macro to calculate binomial relative likelihood and its ! normal approximation. ! ! Need to specify 5 scalars: %R ....no. of successes r ! %N ....no. of trials n ! %A ....startpoint of grid ! %Z ....endpoint of grid ! %I ....grid increment ! ! Output: Plot 1) Relative likelihood (+ =exact, *=normal approx.) ! 2) Log relative likelihood ( " " ) ! Table of values of the following quantities: ! P_ grid of values of p = r/n ! R_ relative likelihood for p ! NR_ normal approximation to R_ ! LR_ log relative likelihood for p ! NLR_ normal approximation to LR_ ! ! Restrictions: 0 < %R < %N , 0 < %A < %Z < 1 , %I>0 ! $CA %Z1 = (%R<=0)?(%R>=%N)?(%A<=0)?(%Z>=1)?(%A>=%Z)?(%I<=0)$SW %Z1 BERR$! $DEL R_ LR_ P_ NR_ NLR_$CA %G = 1+(%Z-%A)/%I$! $VAR %G R_ LR_ P_ NR_ NLR_$! $CA P_ = %A+%I*(%CU(1)-1) : %P = %R/%N ! : %Z3 = %R*%LOG(%P)+(%N-%R)*%LOG(1-%P)! : LR_ = %R*%LOG(P_)+(%N-%R)*%LOG(1-P_)-%Z3! : R_ = %EXP(LR_)! : NLR_ = -0.5*%N*((P_-%P)**2)/(%P*(1-%P))! : NR_ = %EXP(NLR_)! $PLOT R_ NR_ P_ '+*'$PR 'Relative likelihood (' *i %r ' out of ' *i %n ! ') + is exact, * is normal approx.';;$! $PLOT LR_ NLR_ P_ '+*'$PR 'Log relative likelihood (' *i %r ' out of '! *i %n ') + is exact, * is normal approx.';;$! $LOOK(S=1) P_ R_ NR_ LR_ NLR_$! $DEL P_ R_ NR_ LR_ NLR_$! $ENDM ! $M BERR ! $PR '*** Error in macro BINREL - one of the following restrictions' '*** has been violated: 0 < %R < %N , 0 < %A < %Z < 1 , %I>0'$EX 2$ $ENDM ! ! $RETURN ! !************************************************************************ ! $SUBFILE EXTVAL ! ! !------------------------------------------------------------------------ ! Author: B. J. Francis, Centre for Applied Statistics, ! University of Lancaster, U. K. ! Main macros: ! EXTVAL Fits the extreme value distribution to survival ! data. Survival times may be right-censored. ! For macro EXTVAL: ! Formal arguments: ! %1 (obligatory) Variate containing the survival ! times, some of which may be right censored. ! %2 (obligatory) Indicator or censor variate. Elements ! take the value 1 if uncensored and 0 if censored. ! Macro arguments: ! MODEL The model formula requested (no default) ! CONV (optional) The convergence criterion(default .001) ! DISP (optional) The $DISP options used after ! convergence (default E) ! CYCLE (optional) Takes the values $CYC$ or $RECY$ ! Determines whether $recycling is used for the ! iterative fitting of the EXTVAL distribution. ! (Default $CYCLE$) ! Scalar Arguments: ! %W Maximum number of iterations (default 15) ! Output: ! EXTVAL:Displays for each iteration ! the estimate of the scale parameter,the ! deviance and the number of degrees of freedom ! On convergence, or after %W (15) iterations,displays ! by default the estimates of the parameters and s.errors ! Example of use: ! $mac model a+b+c $endm ! $mac disp et $endm ! optional ! $use EXTVAL t c$ ! !------------------------------------------------------------------------- ! ! $MAC MESS $PRI '-- Standard errors of estimates'! ' given below are underestimated'! $$E ! $MAC WAR1 $PRI '-- Weights not available. No weights used in fit.'$WEI $$ENDM ! $MAC CONV .0005 $ENDM ! $MAC DISP E $ENDM ! $MAC CYCLE $CYCLE $ENDM ! $MAC EXV1! $CAL %Z6=%Z6-1: %Z6=%GT(%Z6,0)*%Z6! update iteration counter $OUT $TRA$CAL OFV_=%A*%1! update offset variate $USE CYCLE$FIT #MODEL$OUT %Z4$TRA I O W F H$!fit model suppressing usual output $CAL %D=%Z2 - 2*%CU(%2*%LOG(%A*%FV)-%FV)! calculate deviance : %B=%A/%Z7 : %F=%DF-1! calculate correct DF $PRI *5 %D %B *I %F,6$! and print them out $CAL %Z8=%CU(%1*(%FV-%2)) : %Z8=0.5*(%A-%Z1/%Z8)! new increment for shape parameter : %Z8=%IF(%LT(%Z8,-5),-5,%Z8)! should not be less than -5 : %Z9=%LE(-#CONV,%Z8)*%GE(#CONV,%Z8)! $EXI %Z9! test for convergence $CAL %A=%A-%Z8 $$ENDM! update shape parameter ! $MAC EXTVAL! $DEL OFV_ T_! $PR *M 20 '-- Model is ' MODEL $ $TAB THE %1 LARGEST INTO L_$CA %Z7=L_$DEL L_$ $CA T_=%1/%Z7! : %Z1=%CU(%2)! : %Z2=2*%Z1*%LOG(%Z7)! : %Z4=%COC ! store current output channel : %Z6=%IF(%GT(%W,0),%W,15)! max no. of iterations : %A=1 ! $YVA %2 $ERR P$CYC! $SWI %PWF WAR1$OFF OFV_! switch weights off if set $PR 'Extreme Value Fit':$ $PR : ' Deviance shape df'! Print headings : ' parameter'! $ARG EXV1 T_ %2$WHI %Z6 EXV1! use EXV1 until convergence $USE MESS$DIS #DISP$CYC$OFF! $CA %A=%B$DEL T_ OFV_$! $$END ! ! $RETURN ! !************************************************************************ ! $SUBFILE CLOGISTIC ! ! !------------------------------------------------------------------------ ! Main macros: ! LOGISTIC Fits the LOGISTIC distribution to survival ! data. Survival times may be left or right-censored. ! LLOGISTIC Fits the LOG-LOGISTIC distribution to survival ! data. Survival times may be left or right-censored. ! For macro LOGISTIC or LOG-LOGISTIC: ! Formal arguments: ! %1 (obligatory) Variate containing the survival ! times, some of which may be censored. ! %2 (obligatory) Indicator or censor variate. Elements ! take the value 2 if left-censored, 1 if uncensored ! and 0 if right-censored. ! Macro arguments: ! MODEL The model formula requested (no default) ! DISP (optional) The $DISP options used after ! convergence (default E) ! CONV (optional) The convergence criterion(default .001) ! Scalar Arguments: ! %W (optional) Maximum no. of iterations(default 15) ! Output(both macros): ! Displays for each iteration the estimate of the ! shape parameter (sigma), the deviance and the number of ! degrees of freedom. ! On convergence, or after %W (15) iterations,displays ! by default the estimates of the parameters and s.errors ! Scalar output: %d - deviance ! %f - d.f. ! %s - shape parameter (sigma). ! %sc- sigma squared ! Example of use: ! $mac MODEL a+b $endm ! $mac DISP et $endm ! optional ! $use LOGISTIC t c$ !------------------------------------------------------------------------ ! ! Scalars used by macro: ! ! %Z1 - No. of uncensored obns. ! %Z2 - Initial updated estimate of shape parm. ! %Z3 - Switch for convergence or #iterations ! %Z4 - Current output channel ! %Z5 - Iteration counter ! %Z6 - Maximum number of iterations ! %Z7 - Deviance correction for log-logistic ! %Z8 - Increment for updated shape parameter/(at end) S squared ! %Z9 - Switch for distribution message ! !------------------------------------------------------------------------ ! $MAC MESS $PRI '-- Standard errors of estimates'! ' given below are underestimated'! $$E ! $MAC MOD1 $PRI 'LOGISTIC fit' $$ENDM ! $MAC MOD2 $PRI 'LOG-LOGISTIC fit' $$ENDM ! $MAC WAR1 $PRI '-- Prior weights not allowed - No weights used in fit.'$WEI $$E ! $MAC WAR2 $PRI '-- Offset is not allowed - No offsets used in fit.'$OFF$$ENDM ! $MAC CONV .001 $ENDM ! $MAC DISP E $ENDM ! $MAC LOGISTIC ! $DEL TT_$CAL TT_=%1: %Z9=1: %Z7=0$ARG LOG1 %1 %2$USE LOG1$$E ! $MAC LLOGISTIC ! $DEL TT_$CAL TT_=%LOG(%1+%EQ(%1,0)*0.5)$CA %Z9=2:%Z7=2*%CU(%EQ(%2,1)*TT_)$! $ARG LOG1 %1 %2$USE LOG1$$E ! $MAC LOG2 $CAL OFS_=TT_/%S$! $FIT #MODEL$! $CAL P_=%FV/BD_$! : %Z2=%CU((%FV-BR_)*%LP*%S)/%Z1$! : %F=%DF-1$! : %D=%Z7+2*%Z1*%LOG(%S)-2*%CU((BR_*%LOG(P_))+((BD_-BR_)*%LOG(1-P_)))! $OUT %Z4$TRA I O W F H$! $PRI *5 %D %S *I %F,6$! and print them out $EXI %Z3$! $CAL %Z3=%GE(%Z5,%Z6)$EX %Z3$! $OUT $TRA$ $CA %Z8=0.5*(%S-%Z2)! new increment for shape parameter : %Z3=%LE(-#CONV,%Z8)*%GE(#CONV,%Z8)! $CAL %S=%S-%Z8:%Z5=%Z5+1 $$ENDM! update shape parameter ! ! $MAC LOG1 ! $DEL WT_ BR_ BD_ OFS_ P_! $SWI %PWF WAR1$SWI %OSF WAR2$! switch off offset and weights $PRI *M 20 '-- Model is ' MODEL :$! $SWI %Z9 MOD1 MOD2$! $CAL WT_=%EQ(%2,1)! : %Z1=%CU(WT_)! : %Z4=%COC ! store current output channel : %Z5=1 :%Z3=0 ! $PRI : ' Deviance shape df'! Print headings : ' parameter'! $OUT $TRA$! $WEI WT_ $YVA TT_$ERR N$OFF$FIT #MODEL$! get starting values $CAL %S=%SQRT(3*%SC)/%PI$! : %Z6=%IF(%GT(%W,0),%W,15)! max no. of iterations : BD_=WT_+1 : BR_=%NE(%2,0) ! $ERR B BD_$YVA BR_$OFF OFS_$WEI $! $WHI %Z5 LOG2$! $D E$! $CAL OFS_=(%S+1)*%LP-TT_ : %Z8=%S*%S $SCA %Z8 $FIT .$! $USE MESS$DIS #DISP $CYC $OFF $SCA 1$! $DEL WT_ BR_ BD_ TT_ OFS_ P_! $$END ! ! $RETURN !************************************************************************ ! $SUBFILE KAPLAN ! $M KAPLAN ! $DEL TYP_ D0_ D1_ IND_ DT_ DS_ H_ SF_ RS_ ZA_ ZC_! $CA TYP_=(%2==1)$TAB FOR %1 WITH TYP_ USING D1_ BY DT_$! $CA TYP_=(%2==0)$TAB FOR %1 WITH TYP_ USING D0_ BY DT_$! $CA %Z1=%CU(DT_==DT_):%Z4=%CU(%1==%1) ! $CA %Z2=%CU(D1_>0)$CA %Z9=(%Z2==0)$SWI %Z9 KPER$VAR %Z2 ZA_ ZC_$! $VAR %Z1 IND_$CA IND_=%CU(1)-1$CA DS_=%CU(D0_+D1_)! $CA RS_=%Z4-DS_(IND_) : H_=1-D1_/RS_ $! :%Z3=1 : %Z3=SF_=H_*%Z3$! find cu. prod. of H_ and store in SF_ $CA IND_=D1_>0 : IND_=IND_*%CU(IND_) : ZA_(IND_)=SF_: ZC_(IND_)=DT_$! !$DEL TYP_ D0_ D1_ IND_ DT_ DS_ H_ SF_ RS_ $ $PR 'Kaplan-Meier Survivor function estimate'$ $PLOT (S=1) ZA_ ZC_$PR 'survivor function is stored in ZA_'$ $E ! $M KPER ! $PR '***No uncensored death times..macro cannot continue'$! $DEL D1_ D0_ DT_ TYP_$EX 2$ ! $E ! $RETURN ! !************************************************************************ ! $SUBF CNORMAL! ! !------------------------------------------------------------------------------ ! Author: B. J. Francis, Centre for Applied Statistics, ! University of Lancaster, U. K. ! Version 1.1 GLIM 3.77 February 1987 ! Main macros: ! NORM Fits a normal distribution to survival data. Survival ! times may be right censored. ! LNORM Fits a log-normal distribution to survival data. survival ! times may be right censored. ! Formal arguments: (Both macros) ! %1 Value containing the survival times. ! %2 Indicator or censor variate. Elements take the value ! 1 if uncensored and 0 if censored. ! Macro arguments: (Both macros) ! MODEL The model formula requested (obligatory) ! Scalar arguments: (Both macros) ! %W Maximum number of iterations (default is 15) ! OUTPUT: The value of the deviance and its standard error are displayed ! after each successive fit of the model. ! EXAMPLE OF USE: ! $mac model G$endm ! $use norm T C$ ! $use lnorm T C$ !------------------------------------------------------------------------------- ! ! $MAC NORM ! $DEL T_ SR_ HZ_ AYV_$SWI %PWF NCER! $PRI *M 20 '-- Model is ' MODEL! $ARG NORI %1 %2$CA T_=%1:%Z1=0:%Z7=%COC$PR ' Normal Fit'$USE NORI! $DEL AYV_ T_$$ENDM! ! $MAC LNORM! $DEL T_ SR_ HZ_ AYV_$SWI %PWF NCER! $PRI *M 20 '-- Model is ' MODEL! $ARG NORI %1 %2$CA T_=%LOG(%1+0.5*%EQ(%1,0)):%Z1=2*%CU(T_*%2):%Z7=%COC! $PR ' Lognormal Fit'$USE NORI! $DEL AYV_ T_$$ENDM! ! $MAC NORINIT! $CAL %Z2=%CU(%2) : %Z3=%IF(%GT(%W,0),%W,15)! $YVAR T_ $ERR N $OU $TRA $FIT #MODEL $OU %Z7$TRA I O W F H! $CAL %S=%SQRT(%DV/%DF)*1.1! $PR ' Deviance Shape DF':' Parameter'! $ARG NORC T_ %2 $WHILE %Z3 NORC $USE MESS$D E$$ENDM! ! $MAC NORC! $CAL %Z3 =%Z3-1 : %Z3=%GT(%Z3,0)*%Z3! : SR_=(%1-%FV)/%S : HZ_=.3989*%EXP(-(SR_*SR_)/2)/(1-%NP(SR_))! : %D=%CU(%2*SR_*SR_)-2*%CU((1-%2)*%LOG(1-%NP(SR_)))! : %D=2*%Z2*(%LOG(%S)+.91894) +%D+%Z1! $PRI *5 %D %S *-1 %DF$CA %Z4=%Z4-%D! : %Z4=%GE(.0001,%Z4*%Z4)$EX %Z4$CAL %Z4=%D! $OU$TRA $CAL AYV_=%1*(%2) + (1-%2)*(%FV + %S*HZ_)! $YVAR AYV_! $FIT #MODEL $OU %Z7$TRA I O W F H! $CAL %Z5=%CU(%2*((%1-%FV)**2)) : %Z6=%Z2-%CU((1-%2)*SR_*HZ_)! :%S=%SQRT(%IF(%GT(%Z6,0),(%Z5/(%Z6+%EQ(%Z6,0))),(%S*%S)))$! $$ENDM! ! $MAC MESS $PRI '-- Standard errors of estimates'! ' given below are underestimated'! $$E! ! $MAC NCER ! $PRI '---Macro can not be used if prior weights are set.'$! $EXI 2$$ENDM! ! $RETURN! ! !************************************************************************ $SUBFILE PIECEWISE ! ! macros to fit the piecewise exponential survival model ! M. Green Centre for Applied Statistics ! University of Lancaster, U.K. Sept 1985 ! ! macro parameters ! CUTP %1 survival time ! %2 censor indicator 0 - censored ! 1 - uncensored ! %3 cut points for piecewise exponential (output) ! CUTP finds the values of the uncensored survival times ! ! INIB %4 - weight variate (optional) ! INIC ! INIB,INIC initialise the fitting procedure for methods B,C ! %W used to record whether a weight was set in INIB and INIC ! ! FITB %1 censor indicator ! FITC ! FITB,FITC fit the model stored in macro MODEL using method B,C ! %T controls tolerance for terminating iterations ! set at 0.00001 in INIB,INIC. ! %N Maximum no. of iterations set to 10 ! ! RESET %1 cut points ! RESET deletes temporary variates and %1 for method C ! ! PHAZ %1 cut points ! PHAZ produces a plot of log hazard versus log survival time for ! methods B and C only. ! !------------------------------------------------------------------------- ! $macro INIB ! for method B $use INIT %1 %2 %3 $! $cal %T=0.00001 $! tolerance ! total W over i $cal WJ_=0 : WJ_(BLOK)=WJ_(BLOK)+%2 $! ! declare model $cal %W=%a4 $! weight set? $units %z9 $yvar WV_ $error P $link L $weight IWT_ $! $cal %fv=1 $arg spwb %4 $switch %W spwb $$! $endmac ! $macro spwb ! ! macro to expand a weight variate ! %1 input weight variate $cal PW_=%1 $! $use XPCC PW_ $! $endmac ! $macro INIT ! $group NI_=%1 intervals * %3 * $! $cal NI_=NI_-(%1==%3(NI_-1)) : CNI_=%cu(NI_) $! ! expand censor variable $cal %z9=%cu(NI_) $var %z9 TMP_ $! $cal TMP_=0 : TMP_(CNI_)=%2 $assign %2=TMP_ $! ! generate exposure time $cal GAP_=%3-%3(%cu(1)-1) $var %z9 IND_ $! $cal IND_=1 : IND_(CNI_)=1-NI_ : IND_=%cu(IND_) $! $cal TMP_=GAP_(IND_) : TMP_(CNI_)=%1-%3(NI_-1) $! $cal ET_=TMP_ $! ! generate block factor $cal %z1=0 : %z1=%if((NI_>%z1),NI_,%z1) $! $cal IND_(CNI_)=NI_ $assign BLOK=IND_ $! $factor BLOK %z1 $var %z1 HAZ_ WJ_ $! $endmac ! $macro INIC ! $cal %T=0.00001 : %N=10 $! $cal %Z1=%cu(%1==%1) $var %Z1 NI_ D_ $! $cal %Z1=%cu(%3==%3)+1 $var %Z1 ET_ WJ_ HAZ_ GK_ $! $cal ET_=%3(%gl(%Z1-1,1))-%3(%gl(%Z1-1,1)-1) $! $cal ET_(%Z1)=0 $! $cal NI_=0 : D_=0 $! $cal %Z3=0 : %Z2=%Z1 $arg STP2 %1 %3 $while %Z2 STP2 $! $cal %Z3=0 : %Z2=%Z1 $arg STP3 %2 $while %Z2 STP3 $! ! declare model $cal %W=%a4 $! weight set? $error P $link L $weight ITW_ $yvar WV_ $! $cal PW_=1 $arg SPWC %4 $switch %W SPWC $! $cal %fv=1 $use CNDI $! $endmac ! $macro SPWC ! set prior weight $cal PW_=%1 $$endmac ! $macro XPCC ! ! macro to expand constant covariates ! %1,%2,... covariates $cal IND_=0 : IND_(CNI_-NI_+1)=1 : IND_=%cu(IND_) $! $cal %z2=%a1+%a2+%a3+%a4+%a5+%a6+%a7+%a9 : %z1=0 $! $arg XCCL %1 %2 %3 %4 %5 %6 %7 %8 %9 $! $while %z2 XCCL $! $endmac ! $macro XCCL ! $cal %z1=%z1+1 : %z2=%z2-1 $! $cal TMP_=%%z1(IND_) $assign %%z1=TMP_ $! $endmac ! $macro XPRM ! ! macro to expand repeated measurements covariates ! %1 - ID of case ! %2 - time of measurement ! %3 - cut-points ! %4,%5,... covariates $ca %z1=%cu(%1==%1)$var %z1 I_$ca I_=%cu(1)$! $ca FC_=(%1(I_)>%1(I_-1)) : FC_=1-FC_$! $group IT_=%2 intervals * %3 * $! $cal IT_=(IT_-((%2==%3(IT_-1))&(%2/=0))+CNI_(%1-1))*FC_ $! $cal IND_=0 : IND_(IT_)=IND_(IT_)+1$! $cal IND_=%if(%eq(BLOK,1),IND_+1,IND_)$! $cal IND_=%cu(IND_) $delete IT_ FC_ I_$! $cal %z2=%a4+%a5+%a6+%a7+%a8+%a9 : %z1=0 $! $arg XRML %4 %5 %6 %7 %8 %9 $while %z2 XRML $! $endmac ! $macro XRML ! $cal %z1=%z1+1 : %z2=%z2-1 $! $cal TMP_=%%z1(IND_) $assign %%z1=TMP_ $! $endmac ! $macro XPTR ! ! macro to generate treatment factor ! %1 - time of start of treatment ! %2 - cut-points ! %3 - factor (output) $group IT_=%1 intervals * %2 * $! $cal IT_=IT_+CNI_(%cu(1)-1) : IT_=%if(%gt(IT_,%z9),0,IT_) $! $factor %z9 %3 2 $cal %3=0 : %3(CNI_-NI_+1)=-1 : %3(IT_)=%3(IT_)+1 $! $cal %3=%cu(%3) : %3=%3+2 $! $delete IT_ $endmac ! $macro XPTI ! ! macro to generate time variable ! %1 - survival time ! %2 - cut-points ! %3 - time variable (output) $cal IND_=1 : IND_(CNI_)=1-NI_ : IND_=%cu(IND_) $! $cal %3=%2(IND_) : %3(CNI_)=%1 $! $endmac ! $macro CUTP ! ! macro to find ordered observed death times ! %1 - survival time ! %2 - censor indicator ! %3 - ordered death times (cut-points) (output) $warn $tab for %1 with %2 by VAL_ using F_ $warn $! $cal %z3=%cu(F_/=0) $var %z3 %3 $! $cal IND_=(F_/=0) : IND_=%cu(IND_)*IND_ : %3(IND_)=VAL_ $! $del VAL_ F_ IND_ $! $endmac ! $macro DEVU $warn $cal %1=2*%cu(%4*%3-%2*%log(%3)) $warn $endmac $macro DEVW $warn $cal %1=2*%cu(%5*(%4*%3-%2*%log(%3))) $warn $endmac ! $macro DEVB ! ! macro to find correct deviance $cal FV_=HAZ_(BLOK)*%fv $! $arg DEVU %1 %2 FV_ ET_ : DEVW %1 %2 FV_ ET_ PW_ $! $cal %z1=%W+1 $switch %z1 DEVU DEVW $! $endmac ! $macro ITRB ! $cal HAZ_=0 : HAZ_(BLOK)=HAZ_(BLOK)+ET_*%fv : HAZ_=WJ_/HAZ_ $! $cal IWT_=ET_*HAZ_(BLOK) : WV_=%1/IWT_ $switch %W PWT $! $fit #MODEL $! $cal %z7=%z7+1 $! $use DEVB %z8 %1 $! $cal %z5=%if(%z5<%z8,%z8-%z5,%z5-%z8) : %z5=%z5/%z8 $! $cal %z6=(%z5>%T) & (%z7/=%N) $! $out %POC $trans O $print *I %z7 *6 %dv *6 %z8 $out $trans $! $cal %z5=%z8 $! $endmac ! $macro PWT ! $cal IWT_=IWT_*PW_ $! $endmac ! $macro FITB ! $arg ITRB %1 $! $out $trans $cal %Z5=-1 : %Z6=1 : %Z7=0 $recycle 2 $use ITRB $! $recyc 1 $while %Z6 ITRB $! $out %POC $trans I O W $! $cal %Z8=%df-%Z1 $! $print ; ' cycle ' *I %Z7 ' deviance '*5 %Z5 ' on '*I %Z8 ' d.f.' $! $endmac ! $macro STP2 ! $cal %Z3=%Z3+1 : %Z2=%Z2-1 $ $cal NI_=NI_+(%1 > %2(%Z3-1)) $! $cal D_=%if((%1 > %2(%Z3-1)),%1-%2(%Z3-1),D_) $! $endmac ! $macro STP3 ! $cal %Z2=%Z2-1 : %Z3=%Z3+1 $! $cal WJ_(%Z3)=%cu((%Z3==NI_)*%1) $! $endmac ! $macro CNDJ ! $cal GK_=%cu(ET_*HAZ_) $! $cal ITW_=GK_(NI_-1)+D_*HAZ_(NI_) $! $warn $cal WV_=%1/ITW_ : ITW_=ITW_*PW_ $warn ! $endmac ! $macro CNDI ! $cal %Z2=%Z1 : %Z3=0 $while %Z2 STP4 $! $endmac ! $macro STP4 ! $cal %Z3=%Z3+1 : %Z2=%Z2-1 $! $cal %Z4=ET_(%Z3)*%cu((%Z3 < NI_)*%fv)+%cu((%Z3==NI_)*D_*%fv) $! $cal HAZ_(%Z3)=WJ_(%Z3)/%Z4 $! $endmac ! $macro ITRC ! $use CNDJ %1 $! $fit #MODEL $! $cal %Z7=%Z7+1 $! $use CNDI $! $use DEVU %z8 %1 %fv %pw $cal %z8=%z8-2*%1*%log(HAZ_(NI_)) $! $cal %z5=%if(%z5<%z8,%z8-%z5,%z5-%z8) : %z5=%z5/%z8 $! $cal %z6=(%z5>%T) & (%z/=%N) $! $print 'cycle ' *I %z7 ' deviance ' *6 %z8 $! $cal %z5=%z8 $! $endmac ! $macro FITC ! $out $trans $! $cal %z5=-1 : %z6=1 : %z7=0 $use ITRC %1 $! $recyc 1 $while %z6 ITRC $! $out %POC $trans I O W F H $cycle $! $cal %z8=%df-%z1 $! $print ; ' cycle ' *I %z7 ' deviance '*5 %z5 ' on '*I %z8 ' d.f.' $! $endmac ! $macro PHAZ ! $var %z1 %re $! $ass LCUT=%1,0 $! $extr %pe $! $warn $cal LCUT=%log(LCUT) : LHAZ=%pe(1)+%log(HAZ_) : %re=1 : %re(%z1)=0 $! $warn ! $print ' log hazard v log survival time' $! $plot(rows=20) LHAZ LCUT '+' $! $delete LCUT LHAZ %re $! $endmac ! $macro RESET ! $delete %1 NI_ D_ ET_ WJ_ HAZ_ GK_ ITW_ $! $endmac ! $RETURN ! $FINISH !\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\