bacteria(MASS)
bacteria()所属R语言包：MASS
Presence of Bacteria after Drug Treatments
药物治疗后，细菌的存在
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Tests of the presence of the bacteria H. influenzae in children with otitis media in the Northern Territory of Australia.
在澳大利亚北领地中耳炎的儿童存在的细菌流感嗜血试验。
用法----------Usage----------
bacteria
格式----------Format----------
This data frame has 220 rows and the following columns:
此数据框有220行，以下的列：
y presence or absence: a factor with levels
Ÿ存在或不存在：与水平的一个因素
ap active/placebo: a factor with levels a and p.
AP主动/安慰剂：各级a和p的一个因素。
hilo hi/low compliance: a factor with levels hi amd
希洛高/低的规定：各级hiAMD的一个因素
week numeric: week of test.
一周数字：本周的测试。
ID subject ID: a factor.
编号题目编号：一个因素。
trt a factor with levels placebo, drug and
泰爱泰党的一个因素水平placebo，drug“
Details
详情----------Details----------
Dr A. Leach tested the effects of a drug on 50 children with a history of otitis media in the Northern Territory of Australia. The children were randomized to the drug or the a placebo, and also to receive active encouragement to comply with taking the drug.
答：利奇博士对50例儿童中耳炎在澳大利亚北领地的历史测试药物的影响。这些儿童被随机分配到药物或安慰剂，也得到积极鼓励符合服用的药物。
The presence of H. influenzae was checked at weeks 0, 2, 4, 6 and 11: 30 of the checks were missing and are not included in this data frame.
流感嗜血杆菌的存在是0，2，4，6和11周时检查：检查的30人失踪，不包括在这个数据框。
源----------Source----------
Menzies School of Health Research 1999–2000 Annual Report pp. 18–21 (http://www.menzies.edu.au/publications/anreps/MSHR00.pdf).
孟席斯学校卫生研究1999-2000年度报告第18-21页（http://www.menzies.edu.au/publications/anreps/MSHR00.pdf）。
参考文献----------References----------
Modern Applied Statistics with S. Fourth edition. Springer.
举例----------Examples----------
contrasts(bacteria$trt) <- structure(contr.sdif(3),
dimnames = list(NULL, c("drug", "encourage")))
## fixed effects analyses[＃固定的效果分析]
summary(glm(y ~ trt * week, binomial, data = bacteria))
summary(glm(y ~ trt + week, binomial, data = bacteria))
summary(glm(y ~ trt + I(week > 2), binomial, data = bacteria))
# conditional random-effects analysis[有条件的随机效应分析]
library(survival)
bacteria$Time <- rep(1, nrow(bacteria))
coxph(Surv(Time, unclass(y)) ~ week + strata(ID),
data = bacteria, method = "exact")
coxph(Surv(Time, unclass(y)) ~ factor(week) + strata(ID),
data = bacteria, method = "exact")
coxph(Surv(Time, unclass(y)) ~ I(week > 2) + strata(ID),
data = bacteria, method = "exact")
# PQL glmm analysis[PQL GLMM分析]
library(nlme)
summary(glmmPQL(y ~ trt + I(week > 2), random = ~ 1 | ID,
family = binomial, data = bacteria))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
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发表于 2012-2-16 20:09:02
