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### assign4

Course: YR 614, Fall 2009
School: Cincinnati
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Word Count: 102

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LINEAR MODELS II ASSIGNMENT #6 DUE February 25 4 goats were randomly selected and measured using Methods 1 and 2 on 5 randomly selected periods resulting in the following data PERIOD 1 2 3 4...

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LINEAR MODELS II ASSIGNMENT #6 DUE February 25 4 goats were randomly selected and measured using Methods 1 and 2 on 5 randomly selected periods resulting in the following data PERIOD 1 2 3 4 5 A 75.1 69.0 74.3 51.2 72.6 1 B 65.4 63.3 59.4 62.9 63.8 C 61.9 57.5 74.4 62.9 54.3 METHOD D 69.4 60.7 57.0 56.6 64.3 75.2 A 63.5 80.7 46.7 71.0 2 B 62.7 61.2 65.3 62.1 63.1 C 60.1 59.6 75.8 55.3 58.3 D 70.1 57.0 54.5 49.5 63.3 Consider the model Y = G P G*P M G*M P*M M-fixed, G,P,GP,GM,PM random 1) Construct the Se...

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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=
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #5DATA 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; C
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #6DATA 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;PROC LOGISTIC DESCENDING; M
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #10DATA HMOHIV; INFILE 'A:\DATA4.TXT'; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTDATE)/30; DA=DRUG*AGE;PRO
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #13DATA HMOHIV; INFILE 'A:\DATA4.TXT'; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTDATE)/30; WHER
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #15DATA HMOHIV; INFILE 'A:\DATA4.TXT'; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTDATE)/30; IF
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #19DATA HMOHIV; INFILE 'A:\DATA4.TXT' pad missover; INPUT ID @13 ENTDATE DATE7. @23 ENDDATE DATE7. TIME AGE DRUG CENSOR; MONTH=(ENDDATE-ENTD
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-ENTD
Cincinnati - STAT - 572
SURVIVAL ANALYSIS HANDOUT #23 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 #24 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 #29 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
SURVIVAL ANALYSIS HANDOUT #30*MATCHED CASE CONTROL DATA FROM HOSMER-LEMESHOW;*FOR EACH CASE, A CONTROL IS RANDOMLY SELECTED FROM THOSE WITH THE SAME AGE;DATA MATCH; INFILE 'A:\DAT
Cincinnati - STAT - 572
%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 - YR - 615
LINEAR MODELS 615 HANDOUT #9 Let us demonstrate how to use the lsmeans statement in PROC MIXED.data mj308; do tray=1 to 12; moist=10*(1+int(tray-1)/3); do fert=
Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #12 This gives an example of a doubly repeated measures analysis of variance.DATA DOUBLY; INPUT SUBJECT Y1 Y2 Y3 Y4 Y5 Y6;CARDS;10029 40
Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #14 This gives the example in SAS System for mixed models on random effects modelssdata wheat; input id variety yield moist; datalines; 1 1
Cincinnati - LM - 615
LINEAR MODELS III HANDOUT #14 This gives the example in SAS System for mixed models on random effects modelssdata wheat; input id variety yield moist; datalines; 1 1
Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #15 This handout does the Hotelling T-statistic. It will test the hypothesis of all means equal to 80 H0: mu1=mu2=mu3=mu4=mu5=mu6=mu7 =
Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #20 This handout will use PROC IML to compute the multivariate statisticsdata weights; input subj program\$ s1 s2 s3 s4 s5 s6 s7; ONE=1;
Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #21 This handout will use the M options in the MANOVA statementdata weights; input subj program\$ s1 s2 s3 s4 s5 s6 s7; datalines; 1
Cincinnati - YR - 615
LINEAR MODEL III HANDOUT #23 This handout will illustrate the multivariate test for equal variance-covariance matrix.data iris; input sepallen sepalwid petallen peta
Cincinnati - YR - 615
LINEAR MODELS III HANDOUT #26 This handout will illustrate factor analysis using the correlation matrix as input.DATA PHYS8(TYPE=CORR /* DF=304 */); IN
Cincinnati - YR - 615
LINEAR MODEL III HANDOUT #29data iris; input sepallen sepalwid petallen petalwid species @; c_species=0; if species&lt;2.5 then c_species=1; cards;50 33 14 02 1 64 2