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4 MAKINGSCOMPOSELAT
E
XTABLES
TheEXAMPLEStudy
Protocolxyz–001
February4,2003
Proportion
0.0
0.2
0.4
0.6
0.8
1.0
l
l
l
l
l
l
c
6
2
=5.33,  P=0.502
c
2
2
=2.38,  P=0.304
c
1
2
=0.02,  P=0.885
1  
2  
3  
4  
female  
Histologic Stage
Ludwig Criteria  
sex  
spiders  
l
l
l
l
l
l
Proportions Stratified by drug
l
l
D−penicillamine
placebo
not randomized
Figure6:
Proportionsofpatientsinvariouscategoriesofbaselinevariables,strat-
ifiedbydrug.Pearsonχ
2
testresultsaregiven.
31
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4 MAKINGSCOMPOSELAT
E
XTABLES
TheEXAMPLEStudy
Protocolxyz–001
February4,2003
Serum Bilirubin , 
mg
dl
0
5
10
15
20
D−penicillamine 
placebo 
not randomized 
l
l
l
F
2, 415
=0.03,  P=0.97
Albumin , 
gm
dl
2.5
3.0
3.5
4.0
D−penicillamine 
placebo 
not randomized 
l
l
l
F
2, 415
=2.1,  P=0.12
Prothrombin Time , 
sec.
10
11
12
13
D−penicillamine 
placebo 
not randomized 
l
l
l
F
2, 413
=0.23,  P=0.8
Age
30
40
50
60
70
D−penicillamine 
placebo 
not randomized 
l
l
l
F
2, 415
=6.1,  P=0.0024
Figure7:
Box-percentileplotsforcontinuousbaselinevariablesinprostatecancer
trial.0.90,0.75,0.50,and0.25coverageintervalsareshown.Thesolidcircledepicts
themeanandtheverticallinethemedian. Kruskal-Wallistestsarealsoshown.
32
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4 MAKINGSCOMPOSELAT
E
XTABLES
TheEXAMPLEStudy
Protocolxyz–001
February4,2003
attach(prostate)
stage ← ← factor(stage, , 3:4, , c("Stage e 3","Stage e 4"))
s6 ← ← summary(stage e ∼ ∼ rx x + + age + + wt + + pf f + + hx + sbp p + + dbp p + + ekg +
hg + + sz + sg + ap + bm,
method=’reverse’, overall=TRUE, test=TRUE)
options(digits=2)
w ← latex(s6, , size=’smaller[3]’, outer.size=’smaller’, Nsize=’smaller’,
long=TRUE, prmsd=TRUE, , msdsize=’smaller’,
middle.bold=TRUE, ctable=TRUE)
#Table10
#smaller :fromrelsizeLaTeXstyle
#long=TRUE:putfirst categoryonarowbyitself
#prmsd=TRUE:printmeansandS.D.
setpdf(f6a, h=7)
plot(s6, which=’categorical’, cex=.8)
#Figure8
Key(-.02, 1)
dev.off()
setpdf(f6b, h=7)
plot(s6, which=’continuous’)
#Figure9
dev.off()
#-----------------------------------------------------------------------
#Finalexamplesusecross-classifications onpossiblymorethanone
#independentvariable. Thesummaryfunctionwithmethod=’cross’produces
#adataframecontainingthecross-classifications. Thisdataframeis
#suitableformulti-paneltrellis displays.
bone ← factor(bm, 0:1, c("no mets","bone e mets"))
s7 ← ← summary(ap>1 ∼ sz + bone, method=’cross’)
options(digits=3)
print(s7, twoway=F)
s7
#sameasprint(s7)
w ← latex(s7)
#Makes7.texforFigure11
33
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4 MAKINGSCOMPOSELAT
E
XTABLES
TheEXAMPLEStudy
Protocolxyz–001
February4,2003
library(lattice)
#S-Plus:trellis(automaticallyattached)
setpdf(f7, h=6, , w=6, trellis=T)
#Figure10
Dotplot(sz ∼ ∼ S | bone, data=s7,
#s7isnameofsummarystats
xlab="Fraction ap>1", ylab="Quartile of Tumor Size")
#DotplotisHmiscversionof dotplotinlattice(S-Plustrellis)
dev.off()
summary(age ∼ stage, , method=’cross’)
summary(age ∼ stage, , fun=quantile, method=’cross’)
summary(age ∼ stage, , fun=function(x) ) c(Mean=mean(x), Median=median(x)),
method=’cross’)
summary(cbind(age,ap) ∼ ∼ stage + + bone,
fun=function(y) apply(y, , 2, quantile, , c(.25,.75)),
method=’cross’)
options(digits=2)
summary(log(ap) ∼ sz z + + bone,
fun=function(y) c(Mean=mean(y), quantile(y)),
method=’cross’)
34
Table10:DescriptiveStatisticsbystage
N
Stage3
Stage4
Combined
TestStatistic
N=289
N=213
N=502
rx
502
2χ3
placebo
26%(74)
25%(53)
25%(127)
0.2mgestrogen
25%(73)
24%(51)
25%(124)
1.0mgestrogen
25%(71)
26%(55)
25%(126)
5.0mgestrogen
25%(71)
25%(54)
25%(125)
AgeinYears
501
70.073.076.0(71.8±6.7)
69.073.076.0
(71.0±7.6)
70.073.076.0(71.5±7.1)
2F1,499=0.2,P=0.657
WeightIndex=wt(kg)-ht(cm)+200
500
9199109(100±13)
8997105(97±14)
9098107
(99±13)
2F1,498=5.4,P=0.021
pf
502
2χ3
normalactivity
93%(268)
85%(182)
90%(450)
inbed<50%daytime
6%(18)
9%(19)
7%(37)
inbed>50%daytime
1%(3)
5%(10)
3%(13)
confinedtobed
0%(0)
1%(2)
0%(2)
HistoryofCardiovascularDisease
502
46%(134)
37%(79)
42%(213)
2χ1
SystolicBloodPressure/10
502
13.014.016.0(14.4±2.6)
13.014.016.0
(14.3±2.2)
13.014.016.0(14.4±2.4)
2F1,500=0.01,P=0.907
DiastolicBloodPressure/10
502
7.08.09.0
(8.2±1.6)
7.08.09.0
(8.1±1.3)
7.08.09.0(8.1±1.5)
2F1,500=0.43,P=0.511
ekg
494
2χ6
normal
35%(98)
33%(70)
34%(168)
benign
5%(14)
4%(9)
5%(23)
rhythmicdisturb&electrolytech
8%(22)
14%(29)
10%(51)
heartblockorconductiondef
6%(17)
4%(9)
5%(26)
heartstrain
30%(85)
31%(65)
30%(150)
oldMI
17%(47)
13%(28)
15%(75)
recentMI
0%(1)
0%(0)
0%(1)
SerumHemoglobin
g/100ml
502
12.513.814.9(13.7±1.8)
11.813.414.6
(13.1±2.1)
12.313.714.7(13.4±2.0)
2F1,500=11,P<0.001
SizeofPrimaryTumor
2cm
497
4816(12±11)
71726
(18±13)
51121(15±12)
2F1,495=39,P<0.001
CombinedIndexofStageandHist.Grade
491
8.09.09.0
(9.1±1.3)
11.012.013.0
(12.0±1.5)
9.010.011.0
(10.3±2.0)
2F1,489=605,P<0.001
SerumProstaticAcidPhosphatase
502
0.400.500.70
(0.66±1.75)
1.604.2020.00
(27.80±93.29)
0.500.702.97
(12.18±62.17)
2F1,500=802,P<0.001
BoneMetastases
502
0%(1)
38%(81)
16%(82)
2χ1
¯abcrepresentthelowerquartilea,themedianb,andtheupperquartilecforcontinuousvariables.x±srepresentsX±1SD.Nisthenumberof
1non–missingvalues.Numbersafterpercentsarefrequencies.Testsused:Pearsontest;Wilcoxontest
4 MAKINGSCOMPOSELAT
E
XTABLES
TheEXAMPLEStudy
Protocolxyz–001
February4,2003
Proportion
0.0
0.2
0.4
0.6
0.8
1.0
l
l
l
l
l
l
l
l
l
l
l
l
l
l
l
l
l
c
3
2
=0.22,  P=0.97
c
3
2
=11,  P=0.012
c
1
2
=4.3,  P=0.038
c
6
2
=6.7,  P=0.35
c
1
2
=127,  P<0.001
placebo  
0.2 mg estrogen  
1.0 mg estrogen  
5.0 mg estrogen  
normal activity  
in bed < 50% daytime  
in bed > 50% daytime  
confined to bed  
normal  
benign  
rhythmic disturb & electrolyte ch  
heart block or conduction def  
heart strain  
old MI  
recent MI  
rx  
pf  
History of Cardiovascular Disease  
ekg  
Bone Metastases  
l
l
l
l
l
l
l
l
l
l
l
l
l
l
l
l
l
Proportions Stratified by stage
l
l
Stage 3
Stage 4
Combined
Figure8:
Distributionofcategoricalbaselinevariablesinprostatecancertrial
36
4 MAKINGSCOMPOSELAT
E
XTABLES
TheEXAMPLEStudy
Protocolxyz–001
February4,2003
Age in Years
55
60
65
70
75
80
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 499
=0.2,  P=0.66
Weight Index = wt(kg)−ht(cm)+200
80
90
100
110
120
130
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 498
=5.4,  P=0.021
Systolic Blood Pressure/10
10
12
14
16
18
20
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 500
=0.01,  P=0.9
Diastolic Blood Pressure/10
6
7
8
9
10
11
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 500
=0.43,  P=0.51
Serum Hemoglobin , 
g
100ml
10
12
14
16
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 500
=11,  P<0.001
Size of Primary Tumor , 
cm2
0
10
20
30
40
50
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 495
=39,  P<0.001
Combined Index of Stage and Hist. Grade
6
8
10
12
14
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 489
=605,  P<0.001
Serum Prostatic Acid Phosphatase
0
50
100
150
200
250
[
[
[
Stage 3  
Stage 4  
Combined  
l
l
l
]
]
]
F
1, 500
=802,  P<0.001
Figure 9:
Quartiles ofcontinuous variables inprostate cancer trial. . x–axes s are
scaled to the e lowest 0.025 and d highest 0.975 quantiles over all groups for r each
variable.
37
5 HANDLINGSPECIALVARIABLES
4.3 DataDisplaysfromCross–ClassifyingVariables
Thefinalexamplesusecross–classificationonpossiblymorethanoneinde-
pendentvariable. The e summaryfunctionwith
method=’cross’
produces a
dataframecontainingthecross–classifications. Thisdataframeissuitable
formulti-paneltrellisdisplaysalthoughifmarginalstatisticsarenotneeded,
theHmisc
summarize
functionisbetter.Thefirstexampleinthisserieswas
LAT
E
X’edtocreateTable11(thecodeislistedabove).
Table11:Fractionofap>1bysz,bone
SizeofPrimary Tumor
cm
2
nomets
bonemets
Total
N
ap>1
N
ap>1
N
ap>1
[0,5)
105
0.248
5
0.8
110
0.273
[5,11)
119
0.21
17
0.765
136
0.279
[11,21)
103
0.301
19
0.947
122
0.402
[21,69]
88
0.5
41
0.902
129
0.628
Missing
5
0.4
0
5
0.4
Total
420
0.305
82
0.878
502
0.398
Thereisno
plot
methodfor
method=’cross’
tables,butyoucanuseTrellis
graphicsonthedataframethatiscreatedby
summary
(seecodeabove). For
thispurpose,the
Hmiscsummarize
functionmightbebetterthan
summary.formula
forproducingtheneededaggregateddata.
5 HandlingSpecialVariables
5.1 Multiple e Choice Variables
Clinicalreportsfrequuentlymustsummarize“checklist”ormultiple–choice
variables.Suchvariablesaretypicallylistedonacasereportformusingone
oftwomethods:
1. Specifyuptothreeprimarypresentingsymptoms:
38
5 HANDLINGSPECIALVARIABLES
Fraction ap>1
Quartile of Tumor Size
l
l
l
l
l
l
[ 0, 6)
[ 6,12)
[12,22)
[22,69]
NA
ALL
0.2
0.4
0.6
0.8
no mets
l
l
l
l
l
bone mets
l
l
l
l
l
l
ALL
Figure 10:
Proportion of patients s withacid d phosphatase e exceeding 1.0, cross–
classifiedbytumorsizeandbonemetastasis
39
5 HANDLINGSPECIALVARIABLES
_________ ________ _ ________
Heretherespondentwritesinuptothreesymptomcodesfromalist
ofperhaps15integercodesdefinedbelowthequestion.
2. Checksymptomsthatarepresent:
headache
__
stomach ache e __
hangnail __
back pain n __
neck ache
__
wheezing __
Whensuchdataareprocessed,eitheraseriesofthreecategoricalvariables
or6binaryvariablesiscreated. Inwhatfollowsweassumethatthebinary
variables are e coded as numeric 0/1 or as s character r variables withvalues
(ignoring case) of
’yes’
and
’present’
denoting a positive response. . In
composing a report, we usually y want t to consider r all of f these component
variablesundertheumbrellaof
’Presenting Symptoms’
.Ifusingpresenting
symptomsasstratification(independent)variables,wewillwanttoknowan
outcomestatisticcomputedseparatelyforthosesubjectshavingheadache,
thosehavingstomachache,etc. Thesecategorieswilloverlapforsomesub-
jects.Whensummarizingpresentingsymptomsstratifiedbytreatment,we
willwanttoknowtheproportionofsubjectsineachtreatmentgrouphaving
headache,the proportionhavingstomachache,etc.,withthe proportions
summingto>1.0ifanysubjecthadmorethanonesymptom.
TheHmisc
summary.formula
functioncanhandlemultiplechoice/checklist
variablesaftertheyarecombinedintoamatrix.TheHmisc
mChoice
function
willtakeasinputaseriesofcategoricalvectorvariables(usingthefirstinput
formatabove),andmakeamatrixwiththenumberofcolumnsequaltothe
numberofchoicesthatwereactuallyselectedinthedata
7
. Thisnewmatrix
consistsoflogical
T/F
values. Youcanalsogive
summary.formula
amatrix
youcreate, ifusinginput t formattwoabove. . The e elementsofthismatrix
needtobenumericwithvalues0and1,logical
F/T
,orcharacterwithvalues
(ignoringcase)of
’yes’
or
’present’
.
Hereisanexampleoftheuseof
mChoice
fromitshelpfile.
> options(digits=3)
> set.seed(173)
7
Thereisalsoanoptiontocreateacolumnfor
’none’
forsubjectsforwhomnochoices
wereselected. Theinputvariablesneed d nothavethesamelevels. . Amaster r list ofcate-
goriesisconstructedbyfindingalluniquecategoriesinthelevelsofallvariablescombined,
preservingtheorderoflevelsforthefactorvariables.
40
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