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4 Pages

### hand23

Course: STAT 572, Fall 2009
School: Cincinnati
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Word Count: 210

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ANALYSIS SURVIVAL HANDOUT #23 DATA HMOHIV; INFILE 'A:\DATA4.TXT'; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTDATE)/30; DATA AA; INPUT DRUG @@; CARDS; 0 1 ; PROC LIFETEST DATA=HMOHIV OUTS=KM NOTABLE; STRATA DRUG; TIME MONTH*CENSOR(0); DATA KM; SET KM; IF DRUG=0 THEN SURV0=SURVIVAL; IF...

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ANALYSIS SURVIVAL HANDOUT #23 DATA HMOHIV; INFILE 'A:\DATA4.TXT'; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTDATE)/30; DATA AA; INPUT DRUG @@; CARDS; 0 1 ; PROC LIFETEST DATA=HMOHIV OUTS=KM NOTABLE; STRATA DRUG; TIME MONTH*CENSOR(0); DATA KM; SET KM; IF DRUG=0 THEN SURV0=SURVIVAL; IF DRUG=1 THEN SURV1=SURVIVAL; PROC PHREG DATA=HMOHIV; MODEL MONTH*CENSOR(0)=DRUG; BASELINE OUT=BB COVARIATES=AA SURVIVAL=SURVIVAL; DATA CC; SET BB; IF DRUG=0 OR DRUG=1; IF DRUG=0 THEN SUR0=SURVIVAL; IF DRUG=1 THEN SUR1=SURVIVAL; DATA FINAL; SET KM CC; DATA EST; INPUT DRUG; CONTROL=1; MONTH=0; CENSOR=0; CARDS; 0 1 ; DATA SET LAST; HMOHIV EST; PROC LIFEREG DATA=LAST; MODEL MONTH*CENSOR(0)=DRUG/D=WEIBULL; OUTPUT OUT=WEIB QUANTILES=.01 .05 .10 .15 .20 .25 .30 .35 .40 .45 .50 .55 .60 .65 .70 .75 .80 .85 .90 .95 .99 P=PRED CONTROL=CONTROL ; DATA WEIB; SET WEIB; SURV=1-_PROB_; MONTH=PRED; IF DRUG=0 THEN SURVV0=SURV; IF DRUG=1 THEN SURVV1=SURV; DATA FINAL; SET FINAL WEIB; PROC PRINT; RUN; PROC GPLOT...

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Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #24DATA HMOHIV; INFILE 'A:\DATA4.TXT' pad missover; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTDAT
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #28* Data described in Ch. 5 of P. Allison, &quot;Survival Analysis Using the SAS System: A Practical Guide.&quot; ;* Stanford heart transplant data;dat
Cincinnati - STAT - 721
FALL QUARTERSTATISTICAL CONSULTING LAB15-MATH-721-001INSTRUCTOR: JAMES A. DEDDENS Phone: 556-4081ROOM: 423C RievschlTIME: MWF 2-3pmOFFICE: 810E Old ChemWEB PAGE: math.uc.edu/~deddensE
Cincinnati - STAT - 721
CONSULTING HANDOUT #3OPTIONS LINESIZE=80;DATA ONE; INPUT ID LOW AGE LWT RACE SMOKE PTL HT UI FTV BWT; IF PTL&gt;=1 THEN PTL=1; CAGE1=(19&lt;AGE&lt;=23); CAGE2=(23&lt;AGE&lt;=26);
Cincinnati - STAT - 721
%MACRO RCSPLINE(x,knot1,knot2,knot3,knot4,knot5,knot6,knot7,knot8,knot9,knot10, norm=2); %LOCAL j v7 k tk tk1 t k1 k2; %LET v7=&amp;x; %IF %LENGTH(&amp;v7)=8 %THEN %LET v7=%SUBSTR(&amp;v7,1,7); %*Get no. knots, last knot, next to last knot;
Cincinnati - STAT - 149
ELEMENTARY PROBABILITY AND STATISTICS15-025-149SUMMER 2004THIRD TERM August 9 to August 28,2004INSTRUCTOR: JAMES A. DEDDENS PHONE: 556-4081 OFFICE: 810E OLD CHEM WEB PA
Cincinnati - STAT - 149
HOMEWORK PROBLEMS FOR PRACTICE EXERCISE NUMBERSCHAPTER 7.1 3,5,9B,13,33,37CHAPTER 7.2 53,58,70,71,74CHAPTER 8.1 1,3,7,16,17,23,24CHAPTER 8.2 31,35,37,39,40,41,45CHAPTER 9.1 1,2,3,11CHAPTER 9
Cincinnati - STAT - 534
SAS PROGRAMMING15-025-534SUMMER QUARTER 2nd HALF TERM July 28- September 2,2004INSTRUCTOR: JAMES A. DEDDENS PHONE: 556-4081 OFFICE: 810E OLD CHEM OFFICE HOURS: 9:30-10 MTWHF
Cincinnati - STAT - 534
HANDOUT #7 THE OUTPUT DELIVERY SYSTEM The ODS is a new version 8 method for delivering output. It allows one to create SAS data sets out of every piece in the output window.
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #26 This handout does some maps of the USA. data salesmap; length stname \$20.; input @11 stcode \$2. state 3. sales 3. stname \$ &amp;;
Cincinnati - STAT - 363
PROB &amp; STAT III HOMEWORK #2 DUE Monday Friday Apr 18 If your UC M-number ends is 0,1,2,3,4 do #12 on page 454 If your UC M-number ends is 5,6,7,8,9 do #13 on page 455 YOU WI
Cincinnati - STAT - 363
PROB &amp; STAT III HOMEWORK #3 DUE Wednesday May 2 If your UC M-number ends is 0,1,2,3,4 do #12 on page 454 If your UC M-number ends is 5,6,7,8,9 do #13 on page 455 THESE ARE TH
Cincinnati - STAT - 363
PROB &amp; STAT III HOMEWORK #5PART 1 Due Wednesday May 28 Using the data from homework #4 find k-1 orthogonal contrasts Compute SSw and perform the test H0: Contrast =0 Try to find one co
Cincinnati - STAT - 363
X1 X2 X3 X4 X5 Y1.31 1.07 0.44 0.75 0.35 1.951.55 1.49 0.53 0.90 0.47 2.900.99 0.84 0.34 0.57 0.32 0.720.99 0.83 0.34 0.54 0.27 0.811.05 0.90 0.36 0.6
Cincinnati - STAT - 363
SYSTEM B1 A1 A2 A3B2 34.00 32.70 32.00 33.20 28.40 29.30 30.10 32.80 30.20 29.80 27.30 28.90B3 29.80 26.70 28.70 28.10 29.70 27.30B4 29.00 28.90 27.60 27.80 28.80 29.10Anova: Two-Factor With Replication SUMMARYB1A1B2 2 66.7 33.35 0.84 2 65
Cincinnati - STAT - 363
Additive Temp Adhesiveness0 50 2.30 50 2.90 50 3.10 50 3.20 60 3.40 60 3.70 60 3.60 60 3.20 70 3.80 70 3.90 70
Cincinnati - STAT - 571
TIME SERIES15-MATH-571-001FALL QUARTERINSTRUCTOR: JAMES A. DEDDENS PHONE: 556-4081 OFFICE: 811d OLD CHEM WEB PAGE: math.uc.edu/~deddensTIME: M
Cincinnati - STAT - 571
DATA SUNSPOT; INPUT NUMB @; N=_N_;CARDS;101 82 66 35 31 7 20 92 154 125 85 68 38 23 10 24 83 132 131118 90 67 60 47 41 21 16 6 4 7 14 34 45 43 48 42 28 10 8 2 01 5 12 14 35 46 41 30 24 16 7 4 2 8 17 36 50 62 67 71 48 288 13 57 122 138 103 86
Cincinnati - STAT - 571
DATA ONE; Z1=0; Z2=0; Z3=0; A1=0; DO N=1 TO 300; A1=RANNOR(123456789); Z1=1.7*Z2-.7*Z3+A1; Z3=Z2; Z2=Z1; OUTPUT; END;PROC ARIMA; IDENTIFY VAR=Z1 STATIONARITY=(ADF);PROC ARIMA; IDENTIFY VAR=Z1(1) STATIONARITY=(ADF); ESTIMATE P=1 NOINT M
Cincinnati - STAT - 571
DATA SUNSPOT; INPUT NUMB @; N=_N_;CARDS;101 82 66 35 31 7 20 92 154 125 85 68 38 23 10 24 83 132 131118 90 67 60 47 41 21 16 6 4 7 14 34 45 43 48 42 28 10 8 2 01 5 12 14 35 46 41 30 24 16 7 4 2 8 17 36 50 62 67 71 48 288 13 57 122 138 103 86
Cincinnati - STAT - 571
DATA AIRLINE; INPUT Y @; YEAR=INT(_N_-1)/12); MONTH=_N_-12*YEAR; DATE=MDY(MONTH,1,YEAR+60); LY=LOG(Y);CARDS;112 118 132 129 121 135 148 148 136 119 104 118115 126 141 135 125 149 170 170 158 133 114 140145 150 178 1
Cincinnati - STAT - 571
DATA SUNSPOT; INPUT NUMB @; N=_N_;CARDS;101 82 66 35 31 7 20 92 154 125 85 68 38 23 10 24 83 132 131118 90 67 60 47 41 21 16 6 4 7 14 34 45 43 48 42 28 10 8 2 01 5 12 14 35 46 41 30 24 16 7 4 2 8 17 36 50 62 67 71 48 288 13 57 122 138 103 86
Cincinnati - STAT - 571
DATA AIRLINE; INPUT Y @; NN=_N_;CARDS;112 118 132 129 121 135 148 148 136 119 104 118115 126 141 135 125 149 170 170 158 133 114 140145 150 178 163 172 178 199 199 184 162 146 166171 180 193 181 183 218
Cincinnati - STAT - 571
title1 h=2 f=swiss 'Intervention Data for Ozone Concentration';title2 h=2 f=swiss 'Box and Tiao, JASA 1975 P.70';data air; input ozone @; label ozone='Ozone Concentration' x1='Intervention' summer='Summer Months Intervention
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #4 INFILE and INPUT STATEMENTS The INFILE statement is used when reading in an external file. The FILE statement is us
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #6 SAS FUNCTIONS SAS allows many functions to be used in the data step, for example:+,-,/,*
Cincinnati - STAT - 534
HANDOUT #7 THE OUTPUT DELIVERY SYSTEM The ODS is a new version 8 method for delivering output. It allows one to create SAS data sets out of every piece in the output window.
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #9 SOME COMPLEX INPUT STATEMENTS There are several different DO loops possible in the SAS data step.
Cincinnati - STAT - 534
SASPROGRAMMING HANDOUT #11 This handout will illustrate various options of PROC UNIVARIATE, PROC REG. We will use the GNP data set which is in the SASHELP library on e
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #14 This handout will illustrate some of the features of PROC GPLOT and also showhow do to a normal probablity plot.LIBNAME JIM 'A:\STAT534';DATA
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT # 19 This handout will write two SAS MACROs to do Handout #10.%MACRO SIM1(K=,N=,MU=,STD=,OUT=);DATA SIMULAT; DO I=1 TO &amp;K; DO K=1 TO &amp;N;
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #24 This handout uses PROC IML to diagonize a symmetric matrix:PROC IML; A={1 2 3,4 5 6,5 7 9}; * this inputs a
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #31 This program uses the dataset #2 on the web page to draw the map of china. This program uses the dataset #3 on the web page to draw the map
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #34DATA YANG; DO DOSE=1 TO 5; DO N=1 TO 10; Y=DOSE+RANNOR(0); OUTPUT; END; END;PROC SORT; BY DOSE;PROC MEANS NOPRINT; BY DOSE; VAR Y; OUTPUT O
Cincinnati - STAT - 534
SAS Programming15-MATH-534 NAME _Test #1Feb 9,20001) Suppose the following data has been saved on A: as DATA1.TXTFather JIM DEDDENS 56Mother MARCIA DEDDENS 56Daughter
Cincinnati - YR - 614
LINEAR MODELS HANDOUT # 3DATA SEARL263; INPUT STOVE \$ PAN \$ SEC @;CARDS;X A 18 X B 12 X C 24Y C 9Z A 3 Z C 15W A 6 W B 3 W C 18PROC GLM; CLASS STOVE PAN;
Cincinnati - YR - 614
LINEAR MODELS II HANDOUT #5DATA MJ129; INPUT T B Y @;CARDS;1 1 19 1 1 20 1 1 211 2 24 1 2 261 3 22 1 3 25 1 3 252 1 25 2 1 272 2 21 2 2 24
Cincinnati - YR - 614
LINEAR MODELS II HANDOUT #6DATA MJ129; INPUT T B Y @;CARDS;1 1 19 1 1 20 1 1 211 2 24 1 2 261 3 22 1 3 25 1 3 252 1 25 2 1 272 2 21 2 2 24 2
Cincinnati - LM - 614
LINEAR MODELS II HANDOUT #6DATA MJ129; INPUT T B Y @;CARDS;1 1 19 1 1 20 1 1 211 2 24 1 2 261 3 22 1 3 25 1 3 252 1 25 2 1 272 2 21 2 2 24 2
Cincinnati - YR - 614
LINEAR MODELS II HANDOUT #7DATA MJ129; INPUT T B Y @;CARDS;1 1 19 1 1 20 1 1 211 2 24 1 2 261 3 22 1 3 25 1 3 252 1 25 2 1 272 2 21 2 2 24 2
Cincinnati - LM - 614
LINEAR MODELS II HANDOUT #7DATA MJ129; INPUT T B Y @;CARDS;1 1 19 1 1 20 1 1 211 2 24 1 2 261 3 22 1 3 25 1 3 252 1 25 2 1 272 2 21 2 2 24 2
Cincinnati - YR - 614
LINEAR MODELS HANDOUT #9DATA SEARLE2; INPUT GRP Y Z @;CARDS;1 21 9 1 18 8 1 22 7 1 23 5 1 19 9 1 17 102 17 8 2 14 11 2 19 10 2 21 12 2 22 7 2 15 6
Cincinnati - LM - 614
LINEAR MODELS HANDOUT #9DATA SEARLE2; INPUT GRP Y Z @;CARDS;1 21 9 1 18 8 1 22 7 1 23 5 1 19 9 1 17 102 17 8 2 14 11 2 19 10 2 21 12 2 22 7 2 15 6
Cincinnati - YR - 614
LINEAR MODELS II HANDOUT #18data mj308; do tray=1 to 12; moist=10*(1+int(tray-1)/3); do fert=1 to 4; input y @; output; end; end;cards;3.3458 4.3170 4.5572
Cincinnati - YR - 614
LINEAR MODELS II ASSIGNMENT #2 DUE JAN 22CONSIDER THE DATA ON PAGE 414 IN &quot;ANALYSIS OF MESSY DATA&quot;PERFORM AN ANALYSIS OF VARIANCE (NOTE: the
Cincinnati - YR - 614
LINEAR MODELS II ASSIGNMENT #3 DUE JAN 22 Do a 2-way ANOVA on the data set B
Cincinnati - LM - 614
LINEAR MODELS II ASSIGNMENT #6 DUE MAR 2 4 goats were randomly selected and measured using Methods 1 and 2 on 5 randomly sele
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #3 This illustrates the concept of &quot;confounding&quot;DATA KK_EG10; INPUT F E D N @; E2=2-E; D2=2-D;CARDS;1 1 1 194 1 1 0 6061 0 1 24
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #10 Fit an exponential distribution to the entire data set Compare the fit to the Kaplan Meier curveDATA HMOHIV; INPUT ID @13 ENTD
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #12 Fit 2 2-parameter Weibull distributions (drug=0/1) with common scale parameter Plot the survival curvesDATA HMOHIV; INFILE '
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #13 Fit 2 2-parameter Weibull distributions to the data (drug=0/1)DATA HMOHIV; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #14 Use LLS to check for PH and Weibull for AGEDATA HMOHIV; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #15 Fit 4 exponential and Weibull distribution for categorized AGE with common scale parameterDATA HMOHIV; INPUT ID @13 ENTDATE DATE7. @23
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #18 Get the Cox-Snell residuals as explained on page 290DATA HMOHIV; INFILE 'A:\DATA4.TXT' pad missover; INPUT ID @13 ENTDATE DATE7. @23 E
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #21 This handout will plot 2 KM curves, 2 weibull curves and 2 PHREG curvesDATA HMOHIV; INFILE 'A:\DATA4.TXT'; INPUT ID @13 ENTDATE DATE7. @2
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #22 Compare Cox to Weibull for 2 modelsDATA HMOHIV; INFILE 'A:\DATA4.TXT' pad missover; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #23 Get predicted Cox curves for different covariate valuesDATA HMOHIV; INFILE 'A:\data4.txt'; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #24*use drug as a STRATA variable;*use this if the PH assumption is not valid for DRUG;*SAS will estimate different baseline survival curves for DRUG=0
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #27 Do Poisson regression to model rates rates.DATA KKM; INPUT CITY AGE CASES PYRS @; LAGE=LOG(AGE-15)/35); LPYRS=LOG(PYRS);CARDS;0 20 1 1
Cincinnati - STAT - 572
HOMEWORK #1 SURVIVAL ANALYSIS Due April 31) Suppose x1,x2,.,xn is a random sample from the distribution: for x&gt;0:
Cincinnati - STAT - 572
HOMEWORK #4 SURVIVAL ANALYSIS Due May 31) Suppose (t1,e1),(t2,e2),.,(tn,en) is a random sample from the distribution: for t&gt;