率
率（rate）表示在一定空间或时间范围内某现象的发生数与可能发生的总数之比，说明某现象出现的频率。
标准化率（standardized rate）
相对比
相对比（relative ratio）是A和B两个有关联指标值之比。
Using R for Biomedical Statistics
-
相对危险度 （Relative Risk，RR），是指暴露组人群的发病率与非暴露组人群的发病率之比。RR 用于反映暴露因素与结局事件的关联程度， 其 取值范围为 0 到无穷大。数值为 1 时，表明暴露因素与结局事件无关联；小于 1 时，表 明暴露因素导致结局事件的发生率降低；大于 1 时，表明暴露因素导致结局事件的发生率增加。相对风险适用于前瞻性队列研究。
Code
x <- matrix(c(156,9421,1531,14797),nrow=2,byrow=TRUE,
dimnames = list(c("Exposed","Unexposed"),c("Disease","Control")))
x
#> Disease Control
#> Exposed 156 9421
#> Unexposed 1531 14797
# RR
156/(156+9421)*(1531+14797)/1531
#> [1] 0.1737212
source("function/calcRelativeRisk.R")
calcRelativeRisk(x,alpha=0.05)
#> [1] "category = Exposed , relative risk = 0.173721236521721"
#> [1] "category = Exposed , 95 % confidence interval = [ 0.147624440337197 , 0.204431379720742 ]"
# OR
156/9421/(1531/14797)
#> [1] 0.1600391
source("function/calcOddsRatio.R")
calcOddsRatio(x,alpha = 0.05)
#> [1] "category = Exposed , odds ratio = 0.160039091621751"
#> [1] "category = Exposed , 95 % confidence interval = [ 0.135460641900536 , 0.189077140693912 ]"
-
优势比（Odds Ratio，OR），是指暴露组中病例与非病例人数的比值除以非暴露组中病例与非病例人数的比值。 OR 的取值范围也为 0 到无穷大。如果 OR 值大于 1 ，说明该暴露因素更 容易导致结果事件发生，或者说该因素是一个危险因素；小于 1 ，则说明该暴露因素更不 容易导致结果事件发生，或者说该因素是一个保护因素。比值比适用于队列研究和病例对照研究。
Code
y <- matrix(c(30,24,76,241,82,509),nrow=3,byrow=TRUE,
dimnames = list(c("Exposure1","Exposure2","Unexposed"),
c("Disease","Control")))
y
#> Disease Control
#> Exposure1 30 24
#> Exposure2 76 241
#> Unexposed 82 509
calcOddsRatio(y, referencerow=3)
#> [1] "category = Exposure1 , odds ratio = 7.75914634146342"
#> [1] "category = Exposure1 , 95 % confidence interval = [ 4.32163714854064 , 13.9309131884372 ]"
#> [1] "category = Exposure2 , odds ratio = 1.95749418075094"
#> [1] "category = Exposure2 , 95 % confidence interval = [ 1.38263094540732 , 2.77137111707344 ]"
calcRelativeRisk(y, referencerow=3)
#> [1] "category = Exposure1 , relative risk = 4.00406504065041"
#> [1] "category = Exposure1 , 95 % confidence interval = [ 2.93130744422409 , 5.46941498113737 ]"
#> [1] "category = Exposure2 , relative risk = 1.72793721628068"
#> [1] "category = Exposure2 , 95 % confidence interval = [ 1.30507489771431 , 2.2878127750653 ]"
列联表
Code
eg <- matrix(c(156,9421,1531,14797),nrow=2,byrow=TRUE)
colnames(eg) <- c("Disease","Control")
rownames(eg) <- c("Exposed","Unexposed")
print(eg)
#> Disease Control
#> Exposed 156 9421
#> Unexposed 1531 14797
prop.table(eg) #各单元格比例
#> Disease Control
#> Exposed 0.006022003 0.3636750
#> Unexposed 0.059100560 0.5712025
prop.table(eg,margin = 1) #行比例
#> Disease Control
#> Exposed 0.01628903 0.9837110
#> Unexposed 0.09376531 0.9062347
边际列联表
Code
# 边际
margin.table(x=eg,margin = 2) #列和
#> Disease Control
#> 1687 24218
addmargins(eg) #添加行和、列和
#> Disease Control Sum
#> Exposed 156 9421 9577
#> Unexposed 1531 14797 16328
#> Sum 1687 24218 25905
addmargins(eg,1) #添加列和
#> Disease Control
#> Exposed 156 9421
#> Unexposed 1531 14797
#> Sum 1687 24218
addmargins(eg,2) #添加行和
#> Disease Control Sum
#> Exposed 156 9421 9577
#> Unexposed 1531 14797 16328
addmargins(prop.table(eg,1))
#> Disease Control Sum
#> Exposed 0.01628903 0.9837110 1
#> Unexposed 0.09376531 0.9062347 1
#> Sum 0.11005434 1.8899457 2
ftable(eg) # "平铺式"列联表
#> Disease Control
#>
#> Exposed 156 9421
#> Unexposed 1531 14797
