卫生统计学习题软件分析教程例题R16

第十六章设置目录
setwd("D:\\data\\chapter16")
例16-1
lnrkxs<-118927158/1332810869
lnrkxs
##[1]0.08923033
snetrkxs<-221322621/1332810869
snetrkxs
##[1]0.166057
zfdxs<-340249779/992561090
zfdxs
##[1]0.3427998
sefdxs<-221322621/992561090
sefdxs
##[1]0.2229814
lnfdxs<-118927158/992561090
lnfdxs
##[1]0.1198185
lsb<-118927158/221322621
lsb
##[1]0.5373475
xbb<-682329104/650481765
xbb
##[1]1.04896
例16-2
csl<-14218657/1332810869
csl
##[1]0.01066817
zsyl<-14218657/379779700
zsyl
##[1]0.03743922
例16-3
zzsyl<-5*262.43/1000
zzsyl
##[1]1.31215
jzsyl<-5*253.05/1000
jzsyl
##[1]1.26525
例16-4
data16.4<-read.csv("16-4.csv")
colnames(data16.4)[1]<-c("nf")
djbfzsd<-c(1,rep(NA,11))
for(i in2:12){
djbfzsd[i]<-data16.4$mqrzyyss[i]/data16.4$mqrzyyss[1]
}
data16.4$djbfzsd100<-djbfzsd*100
data16.4$djbzzsd100<-(djbfzsd-1)*100
hbfzsd<-c(1,rep(NA,11))
for(i in2:12){
hbfzsd[i]<-data16.4$mqrzyyss[i]/data16.4$mqrzyyss[i-1]
}
data16.4$hbfzsd100<-hbfzsd*100
data16.4$hbzzsd100<-(hbfzsd-1)*100
data16.4
##nf mqrzyyss djbfzsd100djbzzsd100hbfzsd100hbzzsd100 ##12003 1.22100.00000.000000100.00000.000000
##22004 1.25102.4590 2.459016102.4590 2.459016
##32005 1.24101.6393 1.63934499.2000-0.800000
##42006 1.28104.9180 4.918033103.2258 3.225806
##52007 1.30106.5574 6.557377101.5625 1.562500
##62008 1.35110.655710.655738103.8462 3.846154
##72009 1.43117.213117.213115105.9259 5.925926
##82010 1.47120.491820.491803102.7972 2.797203
##92011 1.50122.950822.950820102.0408 2.040816
##102012 1.58129.508229.508197105.3333 5.333333
##112013 1.67136.885236.885246105.6962 5.696203
##122014 1.74142.623042.622951104.1916 4.191617
pjfzsd<-(data16.4$mqrzyyss[12]/data16.4$mqrzyyss[1])^(1/(length(data16.4$mqrzyyss)-1)) pjfzsd
##[1]1.032802
pjzzsd<-pjfzsd-1
pjzzsd
##[1]0.03280236
例16-5
年龄标准化高血压患病率
c.18<-27.74*18.18/100
v.18<-27.74*13.38/100
c.30<-22.04*20.66/100
v.30<-22.04*29.18/100
c.40<-23.60*29.11/100
v.40<-23.60*41.41/100
c.50<-16.40*48.19/100
v.50<-16.40*58.15/100
c.60<-10.22*56.76/100
v.60<-10.22*66.26/100
c.total.age<-sum(c.18,c.30,c.40,c.50,c.60)
v.total.age<-sum(v.18,v.30,v.40,v.50,v.60)
c.total.age
##[1]30.17059
v.total.age
##[1]36.22402
性别标准化高血压患病率
c.man<-50.81*39.59/100
v.man<-50.81*45.06/100
c.wom<-49.19*31.99/100
v.wom<-49.19*40.41/100
c.total.sex<-sum(c.man,c.wom)
v.total.sex<-sum(v.man,v.wom)
c.total.sex
##[1]35.85156
v.total.sex
##[1]42.77267
计算城市男性和女性年龄标准化率
c.man.18<-0.2774*0.2115
c.wom.18<-0.2774*0.1625
c.man.30<-0.2204*0.2881
c.wom.30<-0.2204*0.1290
c.man.40<-0.2360*0.3607
c.wom.40<-0.2360*0.2474
c.man.50<-0.1640*0.4865
c.wom.50<-0.1640*0.4790
c.man.60<-0.1022*0.6383
c.wom.60<-0.1022*0.5156
c.total.age.man<-sum(c.man.18,c.man.30,c.man.40,c.man.50,c.man.60) c.total.age.wom<-sum(c.wom.18,c.wom.30,c.wom.40,c.wom.50,c.wom.60) c.total.age.man
##[1]0.3523128
c.total.age.wom
##[1]0.2631458
计算农村男性和女性年龄标准化率
v.man.18<-0.2774*0.1360
v.wom.18<-0.2774*0.1319
v.man.30<-0.2204*0.4173
v.wom.30<-0.2204*0.1883
v.man.40<-0.2360*0.4674
v.wom.40<-0.2360*0.3734
v.man.50<-0.1640*0.5402
v.wom.50<-0.1640*0.6133
v.man.60<-0.1022*0.6434
v.wom.60<-0.1022*0.6838
v.total.age.man<-sum(v.man.18,v.man.30,v.man.40,v.man.50,v.man.60) v.total.age.wom<-sum(v.wom.18,v.wom.30,v.wom.40,v.wom.50,v.wom.60) v.total.age.man
##[1]0.394354
v.total.age.wom
##[1]0.3366783
计算男性和女性年龄和性别标准化率
c.man<-0.5081*c.total.age.man
v.man<-0.5081*v.total.age.man
c.wom<-0.4919*c.total.age.wom
v.wom<-0.4919*v.total.age.wom
c.total<-sum(c.man,c.wom)
v.total<-sum(v.man,v.wom)
c.total
##[1]0.3084516
v.total
##[1]0.3659833。