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hand19

Course: LM 614, Fall 2009
School: Cincinnati
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MODEL LINEAR II HANDOUT #19 Here are the examples from M&J in Chapter 19 DATA MJ237; INPUT VARIETY $ Y @@; CARDS; A 3.90 A 4.05 A 4.25 B 3.60 B 4.20 B 4.05 B 3.85 C 4.15 C 4.60 C 4.15 C 4.40 D 3.35 D 3.80 ; PROC GLM; CLASS VARIETY; MODEL Y=VARIETY; RANDOM VARIETY/TEST; RUN; PROC VARCOMP METHOD=MIVQUE0; *also ML and REML; CLASS...

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MODEL LINEAR II HANDOUT #19 Here are the examples from M&J in Chapter 19 DATA MJ237; INPUT VARIETY $ Y @@; CARDS; A 3.90 A 4.05 A 4.25 B 3.60 B 4.20 B 4.05 B 3.85 C 4.15 C 4.60 C 4.15 C 4.40 D 3.35 D 3.80 ; PROC GLM; CLASS VARIETY; MODEL Y=VARIETY; RANDOM VARIETY/TEST; RUN; PROC VARCOMP METHOD=MIVQUE0; *also ML and REML; CLASS VARIETY; MODEL Y=VARIETY; RUN; PROC MIXED; CLASS VARIETY; MODEL Y= ; RANDOM VARIETY; RUN; DATA MJ238; INPUT ROW COL Y @@; CARDS; 1 1 10 1 1 12 1 1 11 1 2 13 1 2 15 1 3 21 1 3 19 2 16 1 2 1 18 2 2 13 2 2 19 2 2 14 2 3 11 2 3 13 ; *2 way random; PROC GLM; CLASS ROW COL; MODEL Y=ROW COL ROW*COL; RANDOM ROW COL ROW*COL/TEST; RUN; PROC VARCOMP ; CLASS ROW COL; MODEL Y=ROW COL ROW*COL; RUN; PROC VARCOMP METHOD=REML; CLASS ROW COL; MODEL Y=ROW COL ROW*COL; RUN; PROC MIXED; CLASS ROW COL; MODEL Y= ; RANDOM ROW COL ROW*COL ; RUN; ...

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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&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)<.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 & LOG-BINOMIAL REGRESSIONDATA ONE; INFILE 'A:\DATA1.TXT'; INPUT ID LOW AGE LWT RACE SMOKE PTL HT UI FTV BWT; IF PTL>=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 $ & 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 "restrictedcubic splines" 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>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=&x; %IF %LENGTH(&v7)=8 %THEN %LET v7=%SUBSTR(&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>=1 THEN PTL=1; CAGE1=(19<AGE<=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>=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>=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=&x; %IF %LENGTH(&v7)=8 %THEN %LET v7=%SUBSTR(&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