periodontal | R Documentation |
Data from NHANES 2011-2012 containing 441 matched pairs of a daily cigarette smoker and a never smoker, recording the extent of periodontal disease. See Rosenbaum (2017, 2021).
data("periodontal")
A data frame with 882 observations on the following 12 variables.
SEQN
NHANES 2011-2012 sequence number
female
=1 for female, 0 for male
age
Age in years
black
=1 for black, 0 for other
educf
Education, in five categories. An ordered factor with levels <9
for less than 9th grade, 9 to 11
for 9th to 11th grade, HS/GED
for high school or GED degree,
SomeCol
for some college, College
for college degree.
income
Ratio of family income to the poverty level, capped at 5 times the poverty level.
cigsperday
Cigarettes smoked per day for daily smokers, 0 for never smokers
either
Number of periodonal measurements indicative of periodontal disease.
neither
Number of periodonal measurements
pcteither
Percent indicative of periodontal disease, =100*either/neither.
z
Treatment indicator, 1=daily smoker, 0=never smoker
mset
Matched set indicator, 1 to 441.
Excluding wisdom teeth, 6 measurements are taken for each tooth that is present, up to 28 teeth. Following Tomar and Asma (2000), a measurement indicates periodontal disease if either there is a loss of attachment of at least 4mm or a pocket depth of at least 4mm. The first individual has 11 measurements indicative of periodontal disease, out of 106 measurements, so pcteither is 100*11/106 = 10.38 percent.
Data are from the National Health and Nutrition Examination Survey 2011-2012 and were used as an example in Rosenbaum (2017).
Rosenbaum, P. R. (2015) <https://obsstudies.org/two-r-packages-for-sensitivity-analysis-in-observational-studies/> "Two R packages for sensitivity analysis in observational studies". Observational Studies, 1(1), 1-17.
Rosenbaum, P. R. (2017) <doi:10.1214/17-STS621> "The general structure of evidence factors in observational studies". Statistical Science 32, 514-530.
Rosenbaum, Paul R. (2021) <doi:10.1201/9781003039648> Replication and Evidence Factors in Observational Studies. Chapman and Hall/CRC.
Tomar, S. L. and Asma, S. (2000) <doi:10.1902/jop.2000.71.5.743> "Smoking attributable periodontitis in the US: Findings from NHANES III". J Periodont 71, 743-751.
"US National Health and Nutrition Examination Survey 2011-2012". www.cdc.gov/nchs/nhanes/index.htm
# Figure 1 in Rosenbaum (2017) data(periodontal) attach(periodontal) oldpar<-par() m<-matrix(1:2,1,2) layout(m,widths=c(1,2)) boxplot(pcteither[z==1]-pcteither[z==0],ylab="Smoker-Control Difference", main="(i)",xlab="Matched Pairs",ylim=c(-100,100)) abline(h=0,lty=2) DOS2::crosscutplot(cigsperday[z==1], pcteither[z==1]-pcteither[z==0], ylab="Smoker-Control Difference", xlab="Cigarettes per Day",main="(ii)", ylim=c(-100,100)) abline(h=0,lty=2) # Sensitivity analysis in Section 2.3 of Rosenbaum (2017) y<-pcteither[z==1]-pcteither[z==0] x<-cigsperday[z==1] DOS2::senWilcox(y,gamma=2.76) # The following is the same as sensitivitymw::senmw(y,gamma=2.77,method="p") sensitivitymult::senm(pcteither,z,mset,gamma=2.77,inner=.5,trim=2) # The following is the same as sensitivitymw::senmw(y,gamma=3.5,method="p") sensitivitymult::senm(pcteither,z,mset,gamma=3.5,inner=.5,trim=2) # Second evidence factor DOS2::crosscut(x,y) DOS2::crosscut(x,y,gamma=1.6) # Note, however, that other statistics report greater insensitivity to # bias by virtue of having larger design sensitivity: sensitivitymult::senm(pcteither,z,mset,gamma=3.5,inner=1,trim=4) sensitivitymult::senm(pcteither,z,mset,gamma=4.2,inner=1,trim=4) DOS2::senU(y,m1=4,m2=5,m=5,gamma=2.77) DOS2::senU(y,m1=6,m2=8,m=8,gamma=2.77) DOS2::senU(y,m1=6,m2=8,m=8,gamma=3.5) detach(periodontal) par(oldpar)
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