standardScreeningCensoredTime(WGCNA)
standardScreeningCensoredTime()所属R语言包：WGCNA
Standard Screening with regard to a Censored Time Variable
考虑到截断的时间变量的标准与筛选
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function standardScreeningCensoredTime computes association measures between the columns of the input data datE and a censored time variable (e.g. survival time). The censored time is specified using two input variables "time" and "event". The event variable is binary where 1 indicates that the event took place (e.g. the person died) and 0 indicates censored (i.e. lost to follow up). The function fits univariate Cox regression models (one for each column of datE) and outputs a Wald test p-value, a logrank p-value, corresponding local false discovery rates (known as q-values, Storey et al 2004), hazard ratios. Further it reports the concordance index (also know as area under the ROC curve) and optionally results from dichotomizing the columns of datE.
的的功能standardScreeningCensoredTime计算列输入数据的日期和审查时间变量（如生存时间）之间的关联措施。使用两个输入变量“时间”和“事件”的审查时间。事件变量是二进制，其中1表示该事件发生（例如人死亡），0表示审查（即失访）。该功能适合单变量Cox回归模型（1为每个列的日期），并输出一个Wald检验p值，对数秩p值，相应的本地虚假的发现率（被称为Q值，楼层等人，2004年），危险性比。此外，报告的一致性指数（也称为ROC曲线下面积）和任选结果二分法的列日。
用法----------Usage----------
standardScreeningCensoredTime(
time,
event,
datExpr,
percentiles = seq(from = 0.1, to = 0.9, by = 0.2),
dichotomizationResults = FALSE,
qValues = TRUE,
fastCalculation = TRUE)
参数----------Arguments----------
参数：time
numeric variable showing time to event or time to last follow up.
数值变量的事件或时间，末次随访时间。
参数：event
Input variable time specifies the time to event or time to last follow up. Input variable event indicates whether the event happend (=1) or whether there was censoring (=0).
输入变量time指定事件或末次随访的时间。输入变量event表示该事件是否happend（= 1），或是否有审查（= 0）。
参数：datExpr
a data frame or matrix whose columns will be related to the censored time.
一个数据框或矩阵的列将相关的审查时间。
参数：percentiles
numeric vector which is only used when dichotomizationResults=T. Each value should lie between 0 and 1. For each value specified in the vector percentiles, a binary vector will be defined by dichotomizing the column value according to the corresponding quantile. Next a corresponding p-value will be calculated.
数字向量，只用在dichotomizationResults = T每个值应位于0和1之间。对于每一个值指定的矢量百分的，将被定义为一个二进制向量二分列的值根据相应的分位数。下一个相应的p-值将被计算。
参数：dichotomizationResults
logical. If this option is set to TRUE then the values of the columns of datE will be dichotomized and corresponding Cox regression p-values will be calculated.
逻辑。如果这个选项被设置为TRUE，则日期的列的值将是二分和相应的Cox回归模型的p值将被计算。
参数：qValues
logical. If this option is set to TRUE (default) then q-values will be calculated for the Cox regression p-values.
逻辑。如果这个选项被设置为TRUE（默认值），然后Q值将被计算为Cox回归p值。
参数：fastCalculation
logical. If set to TRUE, the function outputs correlation test p-values (and q-values) for correlating the columns of datE with the expected hazard (if no covariate is fit). Specifically, the expected hazard is defined as the deviance residual of an intercept only Cox regression model. The results are very similar to those resulting from a univariate Cox model where the censored time is regressed on the columns of dat. Specifically, this computational speed up is facilitated by the insight that the p-values resulting from a univariate Cox regression coxph(Surv(time,event)~datE[,i]) are very similar to those from corPvalueFisher(cor(devianceResidual,datE[,i]), nSamples).
逻辑。如果设置为TRUE，函数输出的相关性检验的p值（Q值），与预期的危险（如果没有协变量是合适的）相关联的列日。具体而言，预期的危害定义的作为越轨残余截距唯一Cox回归模型。从单变量Cox比例风险模型的定时截尾回归的那列所造成的结果是非常相似的。具体而言，这种计算速度是促进了敏锐的洞察力，从一个单变量，Cox回归coxph（“幸存者（时间，事件）~日期导致的p值[，]）是非常相似的那些从corPvalueFisher（对应（devianceResidual，日期[，]），nSamples）。
Details
详细信息----------Details----------
If input option fastCalculation=TRUE, then the function outputs correlation test p-values (and q-values) for correlating the columns of datE with the expected hazard (if no covariate is fit). Specifically, the expected hazard is defined as the deviance residual of an intercept only Cox regression model. The results are very similar to those resulting from a univariate Cox model where the censored time is regressed on the columns of dat. Specifically, this computational speed up is facilitated by the insight that the p-values resulting from a univariate Cox regression coxph(Surv(time,event)~datE[,i]) are very similar to those from corPvalueFisher(cor(devianceResidual,datE[,i]), nSamples)
如果输入选项fastCalculation = TRUE，那么该函数输出的相关性检验的P值（Q值）与预期的危险（如果没有适合协）相关联的列日。具体而言，预期的危害定义的作为越轨残余截距唯一Cox回归模型。从单变量Cox比例风险模型的定时截尾回归的那列所造成的结果是非常相似的。具体而言，这种计算速度是促进了敏锐的洞察力，从一个单变量，Cox回归coxph（“幸存者（时间，事件）~日期导致的p值[，]）是非常相似的那些从corPvalueFisher（对应（devianceResidual，日期[I]），nSamples）
值----------Value----------
If fastCalculation is FALSE, the function outputs a data frame whose rows correspond to the columns of datE and whose columns report
如果fastCalculation是FALSE，功能输出一个数据框的行对应的列日和列报告
参数：ID
column names of the input data datExpr.
列名的输入数据datExpr。
参数：pvalueWald
Wald test p-value from fitting a univariate Cox regression model where the censored time is regressed on each column of datExpr.
Wald检验p值拟合一个单变量Cox回归模型，其中审查时间上的每一列datExpr回归。
参数：qValueWald
local false discovery rate (q-value) corresponding to the Wald test p-value.
虚假的发现率（q值）对应的Wald检验p值。
参数：pvalueLogrank
Logrank p-value resulting from the Cox regression model. Also known as score test p-value. For large sample sizes this sould be similar to the Wald test p-value.
对数秩从Cox回归模型的p值。也被称为得分测试p值。对于大样本容量的高度重视和类似Wald检验p值。
参数：qValueLogrank
local false discovery rate (q-value) corresponding to the Logrank test p-value.
当地Logrank检验p值对应的错误发现率（q值）。
参数：HazardRatio
hazard ratio resulting from the Cox model. If the value is larger than 1, then high values of the column are associated with shorter time, e.g. increased hazard of death. A hazard ratio equal to 1 means no relationship between the column and time. HR<1 means that high values are associated with longer time, i.e. lower hazard.
Cox模型产生的危险比。如果该值大于1，那么高的值的列相关联的更短的时间，例如增加死亡风险。危险比等于1意味着列和时间没有关系。 HR <1意味着与较长的时间相关联的高值，即较低的危险。
参数：CI.LowerLimitHR
Lower bound of the 95 percent confidence interval of the hazard ratio.
的危险比在95％的置信区间的下界。
参数：CI.UpperLimitHR
Upper bound of the 95 percent confidence interval of the hazard ratio.
的危险比在95％的置信区间的上限。
参数：C.index
concordance index, also known as C-index or area under the ROC curve. Calculated with the rcorr.cens option outx=TRUE (ties are ignored).
一致性指数，也被称为C-索引或ROC曲线下的面积。与rcorr.cens选项OUTX = TRUE（关系忽略不计）计算。
参数：MinimumDichotPvalue
This is the smallest p-value from the dichotomization results. To see which dichotomized variable (and percentile) corresponds to the minimum, study the following columns.
这是从二分法结果最小的p-值。要查看哪些虚拟变量（百分位）对应于最小，学习下面的列。
参数：pValueDichot0.1
This columns report the p-value when the column is dichotomized according to the specified percentile (here 0.1). The percentiles are specified in the input option percentiles.
根据指定的百分位（这里是0.1）二列时，这列报告的p-值。百分位中指定的输入选项百分。
参数：pvalueDeviance
The p-value resulting from using a correlation test to relate the expected hazard (deviance residual) with each (undichotomized) column of datE. Specifically, the Fisher transformation is used to calculate the p-value for the Pearson correlation. The resulting p-value should be very similar to that of a univariate Cox regression model.
p值使用相关测试与预期的危险（残余偏差），列日（每undichotomized）。具体而言，Fisher变换用于计算的Pearson相关性的p-值。将所得的p-值应该是非常相似的一个单变量Cox回归模型。
参数：qvalueDeviance
Local false discovery rate (q-value) corresponding to pvalueDeviance.
虚假的发现率（q值）到pvalueDeviance相应的。
参数：corDeviance
Pearson correlation between the expected hazard (deviance residual) with each (undichotomized) column of datExpr.
皮尔森相关系数预期的危险（偏差残余）（每undichotomized）列datExpr的。
（作者）----------Author(s)----------
Steve Horvath
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。
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发表于 2012-10-1 22:23:24
