clogistCalc(saws)
clogistCalc()所属R语言包：saws
Conditional Logistic Regression fit
条件Logistic回归拟合
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Perform conditional logistic regression with output formatted for input into saws which will give confidence intervals and p-values.
执行条件Logistic回归格式化的输入与输出saws，这将给置信区间和p值。
用法----------Usage----------
clogistCalc(n, m, x, set, initb = NA, h = 1e-04, maxitr = 15, epsilon = 1e-08, conf.level = 0.95)
clogistLoglike(n, m, x, beta)
clogistInfo(n, m, x, beta, h)
参数----------Arguments----------
参数：n
vector of number at risk
向量的数量在风险
参数：m
vector of number of events
向量的事件数
参数：x
matrix of covariates
矩阵的协变量
参数：set
vector of denoting clusters
矢量表示聚类
参数：initb
vector of initial parameter estimates, initb=NA uses unconditional logistic regression for initial estimate
矢量的初始参数估计，初步估计，INITB = NA采用非条件Logistic回归
参数：h
small value for numeric integration
小值数值积分
参数：maxitr
maximum number of iterations
最大迭代次数
参数：epsilon
convergence criteria (see details)
收敛标准（见详情）
参数：conf.level
confidence level for confidence intervals
置信区间的置信水平
参数：beta
vector of current parameter estimate
矢量电流参数估计
Details
详细信息----------Details----------
The main program is clogistCalc. It calls clogistLoglike and clogistInfo which are not to be called explicitly. The function clogistLoglike finds the loglikelihood using recursive methods, and clogistInfo calculates score vector and information matrix using numerical methods. Both methods are described in Gail, Lubin and Rubinstein (1981), and the h value is the same as is defined in that paper.
主程序clogistCalc。它要求clogistLoglike和clogistInfo不被显式调用。函数clogistLoglike发现loglikelihood使用递归的方法，和clogistInfo用数值方法计算出得分向量和信息矩阵。盖尔，卢宾和鲁宾斯坦（1981）中描述的，这两种方法的h值是相同的，如在该文件中的定义。
The algorithm stops when the largest absolute relative change in either the loglikelihood or in any parameter is less than epsilon. For parameters close to zero (i.e., less than 0.01 in absolute value) the relative change is defined as change/0.01.
无论是在loglikelihood或任何参数的绝对值最大的相对变化时，该算法停止小于小量。对于接近零（即，小于0.01的绝对值）的参数的相对变化被定义为change/0.01。
值----------Value----------
A list for input into the saws function, containing the following elements (K=number of clusters, p=number of parameters):
一个列表输入saws功能，包含以下元素（K =簇数，P =参数的个数）：
参数：coefficients
p by 1 vector of parameter estimates
p的1向量参数估计
参数：u
K by p matrix of scores or estimating equations
p矩阵K的成绩或估计方程
参数：omega
K by p by p array of -1*information
K的p的P阵列-1 *信息
（作者）----------Author(s)----------
Michael Fay, modeled after a Fortran program by Doug Midthune
参考文献----------References----------
<h3>See Also</h3>
实例----------Examples----------
data(micefat)
cout<-clogistCalc(micefat$N,micefat$NTUM,micefat[,c("fatCal","totalCal")],micefat$cluster)
## usual model based variance[＃通常基于模型的方差]
saws(cout,method="dm")
## sandwich based variance with small sample correction[＃的三明治基于方差小样本校正]
s3<-saws(cout,method="d3")
s3
print.default(s3)
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。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-29 22:22:26
