epilepsy(robustbase)
epilepsy()所属R语言包：robustbase
Epilepsy Attacks Data Set
癫痫攻击数据集
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Data from a clinical trial of 59 patients with epilepsy (Breslow, 1996) in order to illustrate diagnostic techniques in Poisson regression.
从59例患者与的癫痫（布瑞斯罗夫，1996年），以说明泊松回归的诊断技术的临床试验数据。
用法----------Usage----------
data(epilepsy)
格式----------Format----------
A data frame with 59 observations on the following 11 variables.
59以下11个变量的观察数据框。
ID Patient identification number
ID病人的识别号码
Y1 Number of epilepsy attacks patients have during the
Y1的癫痫发作患者数在
Y2 Number of epilepsy attacks patients have during the
Y2的癫痫发作患者数在
Y3 Number of epilepsy attacks patients have during the
Y3的癫痫发作患者数在
Y4 Number of epilepsy attacks patients have during the
Y4的癫痫发作患者数在
Base Number of epileptic attacks
Base的癫痫攻击的数量
Age Age of the patients
Age患者的年龄
Trt a factor with levels placebo progabide indicating whether the anti-epilepsy
Trt的因素与水平placeboprogabide表明是否抗癫痫
Ysum Total number of epilepsy attacks patients have
Ysum总数的癫痫发作患者有
Age10 Age of the patients devided by 10
Age10患者的年龄，分裂则10
Base4 Variable Base devided by 4
Base4变量“Base分裂则4
Details
详细信息----------Details----------
Thall and Vail reported data from a clinical trial of 59 patients with epilepsy, 31 of whom were randomized to receive the anti-epilepsy drug Progabide and 28 of whom received a placebo. Baseline data consisted of the patient's age and the number of epileptic seizures recorded during 8 week period prior to randomization. The response consisted of counts of seizures occuring during the four consecutive follow-up periods of two weeks each.
Thall和韦尔59例癫痫患者的临床试验报告的数据，其中31人被随机收到的抗癫痫药物Progabide，28名接受安慰剂。基线数据，包括病人的年龄和之前的随机数在8周的时间记录癫痫发作。响应发作发生在连续四次，每次两个星期的随访时间的计数。
源----------Source----------
Thall, P.F. and Vail S.C. (1990) Some covariance models for longitudinal count data with overdispersion. Biometrics 46, 657–671.
Thall，P.F.和韦尔SC（1990年）的一些协方差模型纵向计数数据偏大的。生物识别技术46，657-671。
参考文献----------References----------
Analysis of Longitudinal Data; Clarendon Press.
Generalized linear models: Checking assumptions and strengthening conclusions. Statistica Applicata 8, 23–41.
实例----------Examples----------
data(epilepsy)
str(epilepsy)
pairs(epilepsy[,c("Ysum","Base4","Trt","Age10")])
Efit1 <- glm(Ysum ~ Age10 + Base4*Trt, family=poisson, data=epilepsy)
summary(Efit1)
## Robust Fit : %%>>>>> FIXME <<<<[＃稳健适用于：％>>>>> FIXME <<<<]
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 2012-9-27 22:08:47
