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6 Pages

### hand11

Course: YR 615, Fall 2009
School: Cincinnati
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Word Count: 179

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LINEAR MODELS III HANDOUT #11 This handouts does a multivariate normal probability plot, as described in J&amp;W p-198 data weights; input subj program\$ s1 s2 s3 s4 s5 s6 s7; datalines; 1 CONT 85 85 86 85 87 86 87 2 CONT 80 79 79 78 78 79 78 3 CONT 78...

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LINEAR MODELS III HANDOUT #11 This handouts does a multivariate normal probability plot, as described in J&W p-198 data weights; input subj program\$ s1 s2 s3 s4 s5 s6 s7; datalines; 1 CONT 85 85 86 85 87 86 87 2 CONT 80 79 79 78 78 79 78 3 CONT 78 77 77 77 76 76 77 4 CONT 84 84 85 84 83 84 85 5 CONT 80 81 80 80 79 79 80 6 CONT 76 78 77 78 78 77 74 7 CONT 79 79 80 79 80 79 81 8 CONT 76 76 76 75 75 74 74 9 CONT 77 78 78 80 80 81 80 10 CONT 79 79 79 79 77 78 79 11 CONT 81 81 80 80 80 81 82 12 CONT 77 76 77 78 77 77 77 13 CONT 82 83 83 83 84 83 83 14 CONT 84 84 83 82 81 79 78 15 CONT 79 81 81 82 82 82 80 16 CONT 79 79 78 77 77 78 78 17 CONT 83 82 83 85 84 83 82 18 CONT 78 78 79 79 78 77 77 19 CONT 80 80 79 79 80 80 80 20 CONT 78 79 80 81 80 79 80 1 RI 79 79 79 80 80 78 80 2 RI 83 83 85 85 86 87 87 3 RI 81 83 82 82 83 83 82 4 RI 81 81 81 82 82 83 81 5 RI 80 81 82 82 82 84 86 6 RI 76 76 76 76 76 76 75 7 RI 81 84 83 83 85 85 85 8 RI 77 78 79 79 81 82 81 9 RI 84 85 87 89 88 85 86 10 RI 74 75 78 78 79 78 78 11 RI 76 77 77 77 77 76 76 12 RI 84 84 86 85 86 86 86 13 RI 79 80 79 80 80 82 82 14 RI 78 78 77 76 75 75 76 15 RI 78 80 77 77 75 75 75 16 RI 84 85 85 85 85 83 82 1 WI 84 84 85 83 83 83 84 2 WI 74 75 75 76 75 76 76 3 WI 83 84 82 81 83 83 82 4 WI 86 87 87 87 87 87 86 5 WI 82 83 84 85 84 85 86 6 WI 79 80 79 79 80 79 80 7 WI 79 79 79 81 81 83 83 8 WI 87 89 91 90 91 92 92 9 WI 81 81 81 82 82 83 83 10 WI 82 82 82 84 86 85 87 11 WI 79 79 80 81 81 81 81 12 WI 79 80 81 82 83 82 82 13 WI 83 84 84 84 84 83 83 14 WI 81 81 82 84 83 82 85 15 WI 78 78 79 79 78 79 79 16 WI 83 82 82 84 84 83 84 17 WI 80 79 79 81 80 80 80 18 WI 80 82 82 82 81 81 81 19 WI 85 86 87 86 86 86 86 20 WI 77 78 80 81 82 82 82 21 WI 80 81 80 81 81 82 83 ; PROC IML; USE WEIGHTS; READ ALL VAR{S1 S2 S3 S4 S5 S6 S7} INTO XX; NR=NROW(XX); NC=NCOL(XX); ONE=J(NR,1,1); XBAR=ONE`*XX/NR; PRINT XBAR; X=XX-ONE*XBAR; VAR=X`*X/(NR-1); PRINT VAR; DIST=VECDIAG(X*INV(VAR)*X`); CREATE DD F...

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Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #12 This handout does the Hotelling T-statistic.data weights; input subj program\$ s1 s2 s3 s4 s5 s6 s7; datalines; 1 CONT 85
Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #15 Thanks to Misty Hein for help.DATA CHENG; DO SUBJ=1 TO 30; SS=4*RANNOR(0); DO TIME=1 TO 6; ST=2*RANNOR(0); T=TIM
Cincinnati - LM - 615
LINEAR MODELS III HANDOUT #15 Thanks to Misty Hein for help.DATA CHENG; DO SUBJ=1 TO 30; SS=4*RANNOR(0); DO TIME=1 TO 6; ST=2*RANNOR(0); T=TIM
Cincinnati - YR - 615
LINEAR MODEL III HANDOUT #20data iris; input sepallen sepalwid petallen petalwid species @; cards;50 33 14 02 1 64 28 56 22 3 65 28 46 15 2 67 31 56 24 363 28 51 15
Cincinnati - LM - 615
LINEAR MODEL III HANDOUT #20data iris; input sepallen sepalwid petallen petalwid species @; cards;50 33 14 02 1 64 28 56 22 3 65 28 46 15 2 67 31 56 24 363 28 51 15
Cincinnati - STAT - 720
HOMEWORK #4 Consider the SUPPORT data set given as an EXCEL file. See the web-page: http:/hesweb1.med.virginia.edu/biostat/s/data/index.htmlwhere the data set is described and given as a s-plus data set. Using hospita
Cincinnati - STAT - 615
LINEAR MODELS III HANDOUT #3 The whole plot analysis can also be obtained by averaging over the factors.OPTIONS LINESIZE=80;DATA MJ297; INPUT A B BLOCK Y @;CARDS;1 1 1 35.
Cincinnati - STAT - 615
LINEAR MODELS III HANDOUT #4data 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 4.557
Cincinnati - STAT - 615
LINEAR MODELS III HANDOUT #5data 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 - STAT - 615
LINEAR MODELS III HANDOUT #6data 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 4.55
Cincinnati - YR - 614
LINEAR MODELS II HANDOUT #4DATA 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 - LM - 614
LINEAR MODELS II HANDOUT #16 * TWO WAY MIXED; *GLM and MIXED do not always agree;D
Cincinnati - YR - 614
LINEAR MODELS HANDOUT #18 *understanding TYPE III SS; *TYPE III hypotheses are precisely those being tested by pr
Cincinnati - YR - 614
LINEAR MODEL II HANDOUT #19 Here are the examples from M&amp;J in Chapter 19DATA MJ237; INPUT VARIETY \$ Y @;CARDS;A 3.90 A 4.05 A 4.25B 3.60 B 4.20 B 4.05 B 3.85C 4.15 C 4.60 C 4
Cincinnati - LM - 614
LINEAR MODEL II HANDOUT #19 Here are the examples from M&amp;J in Chapter 19DATA MJ237; INPUT VARIETY \$ Y @;CARDS;A 3.90 A 4.05 A 4.25B 3.60 B 4.20 B 4.05 B 3.85C 4.15 C 4.60 C 4
Cincinnati - YR - 614
LINEAR MODEL II HANDOUT 23 Here is an example from SAS for Linear Models (I don't seem to get same SS as LSF). All of the sample code can be found on SAS's webpage
Cincinnati - YR - 614
LINEAR MODEL II HANDOUT #22 Here is another 2-way mixed model from M&amp;J (balanced)DATA MJ285; INPUT MACHINE PERSON Y @;CARDS;1 1 52.0 1 1 52.8 1 1 53.11 2 51.8 1 2 52.8 1 2 53.1
Cincinnati - YR - 614
LINEAR MODELS II HANDOUT #24 The whole plot analysis can also be obtrained by averaging over the factors.OPTIONS LINESIZE=80;DATA MJ297; INPUT A B BLOCK Y @;CARDS;1 1 1 35
Cincinnati - YR - 614
LINEAR MODELS HANDOUT #25data 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
DATA MJ265; INPUT WORKER PLANT SITE Y @;CARDS;1 1 1 100.6 1 1 1 106.8 1 1 1 100.61 1 2 110.0 1 1 2 105.81 1 3 100.0 1 1 3 102.5 1 1 3 97.6 1 1 3 98.7 1 1 3 98.71 1 4 98.2 1 1 4 99.52 1 1 92.3 2 1 1 92.0 2 1 1 97.2 2 1 1 93.9
Cincinnati - YR - 614
LINEAR MODELS II ASSIGNMENT #3 DUE FEB 11 Use Brute Forse to verify Tables 9.9 and 9.10 in Searle
Cincinnati - YR - 614
LINEAR MODELS II ASSIGNMENT #6 DUE February 25 4 goats were randomly selected and measured using Methods 1 and 2 on 5 randomly
Cincinnati - STAT - 534
SAS PROGRAMMING15-025-534WINTER QUARTERINSTRUCTOR: JAMES A. DEDDENS PHONE: 556-4081 OFFICE: 810E OLD CHEM OFFICE HOURS: 8-1 MWF WEB PAGE: math.uc.edu/~deddensTIME: MWF
Cincinnati - STAT - 534
INSTRUCTIONS FOR USING SAS/PC FOR WINDOWS SAS PROGRAMMING HANDOUT #1 SAS/PC for WINDOWS is available on the IBM machines in the Library computer lab and
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #3 STATISTICAL PROCEDURES This handout describes several of the basic procedures in SAS SAS always uses the most rece
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 #8 SAMPLE INPUTS This first example illustrates some of the issues of length for charcater variables.
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #17 ARRAYs are used to process many variables the same way. The ARRAY statement can be used to define the set of variables as elements of
Cincinnati - STAT - 534
SASPROGRAMMING HANDOUT #22 This MACRO program considers a categorical variable (DISCRETE) and creates dummy variables. This can then be used together with other MACROsO
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #23 This handout writes a SAS macro to check for linearity in linear regression, (like HANDOUT #11)by creating dummy CATi variables for the percentil
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #26 In this handout we will use PROC IML to find the maximium likelihood estimatefor the Weibull distribution using the Newton Raphson method. SUPPOSE
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #28 This handout will illustrate some of the features of PROC GPLOT.DATA GNP; SET SASHELP.GNP; IF RANUNI(0)&lt;.5 THEN GROUP='A'; ELSE GROUP='B'; IF G
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #32 This handout show how to put multiple plots on a page. You can also just export the graphs into word and paste them on a page.D
Cincinnati - STAT - 534
SAS PROGRAMMING HOMEWORK #5 Due Monday March 31) Write a SAS MACRO program to divide a continuous variable into K equally spaced c
Cincinnati - STAT - 534
SAS Programming15-MATH-534Test #2 NAME _Mar 13,2002 SHOW ALL YOUR WORK1) Suppose the following data has been saved as: HW21.TXT on A:\JAMES
Cincinnati - STAT - 720
HANDOUT #5 LOGISTIC &amp; LOG-BINOMIAL REGRESSIONDATA ONE; INFILE 'A:\DATA1.TXT'; INPUT ID LOW AGE LWT RACE SMOKE PTL HT UI FTV BWT; IF PTL&gt;=1 THEN PTL=1;PROC LOGI
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #14 ARRAYs are used to process many variables the same way. The ARRAY statement can be used to define the set of variables as elements of
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #16DATA SALES; LENGTH ITEM \$12; INPUT NAME \$ MONTH WEEKDAY COMPID STATE \$ @25 ITEM \$ &amp; UNITS RETAIL TOTRET;CARDS;FOSTER 1 2 153 ID SYSTEM
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #21 This handout writes a SAS macro to check for linearity in linear regression, (like HANDOUT #11)by creating dummy CATi variables for the percentil
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #23 PROC IML is a interactive matrix language that contains lots of matrix functions,SAS functions, and various programming statement
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #25 This handout gives a MACRO written by Prof. Frank Harrell to do &quot;restrictedcubic splines&quot; in SAS. It can be used within a data step to define splines.If you s
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #9 Fit an exponential distribution to the entire dataoptions linesize=80;DATA HMOHIV; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG C
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #11 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 #14 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 #16 Use LLS to check for PH and Weibull for AGEOPTIONS LS=80 FORMDLIM='-';DATA HMOHIV; SET HMOHIV; MONTH=(ENDDATE-ENTDATE)/30; CAGE
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #18 Lets try to simulate the weibull and log-normal right censored distributionsOPTIONS LS=80 FORMDLIM='*';DATA WEIB; DO N=1 TO 400000; CENSOR=1
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #19 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 #21DATA HMOHIV; INFILE 'A:\DATA4.TXT' pad missover; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTDATE)/30;DAT
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #22 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 #23 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 #24 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 #25*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 #28 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 Wednesday April 91) Suppose x1,x2,.,xn is a random sample from the distribution: for x&gt;0:
Cincinnati - STAT - 572
HOMEWORK #6 SURVIVAL ANALYSIS June 6 You need to find an article that uses either logistic, Weibull, or Cox regression
Cincinnati - STAT - 572
HOMEWORK #7 SURVIVAL ANALYSIS June 4 USE THE DATA FROM HOME WORK ASSIGNMENT #5 BUT THIS TIME USE alpha=.10 Perform
Cincinnati - STAT - 534
SAS PROGRAMMING HANDOUT #15 PROC SQL is a relatively new procedure that can handle many data set manipulations. Many of the command are similar to the SQL programming language
Cincinnati - STAT - 534
SAS PROGRAMMING ASSIGNMENT #2 due Monday Jan 28 NOTE: You need to show you programs and your output. You should assume the file contains perhaps 1000'
Cincinnati - STAT - 722
SPRING QUARTERSTATISTICAL CONSULTING LAB15-MATH-722-001INSTRUCTOR: JAMES A. DEDDENS Phone: 556-4081OFFICE: 810E Old ChemWEB PAGE: math.uc.edu/~deddensEMAIL: james.deddens@math.uc.edu j
Cincinnati - STAT - 722
%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 - 572
SURVIVAL ANALYSIS HANDOUT #4DATA ONE; INFILE 'C:\JIMSAS\DATA1.TXT'; 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=