Power(SSPA)
Power()所属R语言包：SSPA
Estimates the average power of the pilot data
试验数据估计平均功耗
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function Power estimates the average power of the pilot data at a given false discovery rate. The average power can be estimated for sample sizes other then the pilot data.
功能Power估计在给定的错误发现率试验数据的平均功率。样本大小等，然后试验数据可估计的平均功率。
用法----------Usage----------
plot = FALSE, type = "l", ylim = c(0, 1), xlim = c(0, 1), xlab = "p-value",
ylab = "average power", main, sub, ...)
参数----------Arguments----------
参数：x
object of class SampleSize-class
对象类SampleSize-class
参数：threshold
threshold for truncation of the density of effect-sizes. A small symmetrical region around zero can be defined that will be excluded from the density of effect sizes.
阈值的影响大小的密度截断。对称零附近一个小区域可以定义密度的影响大小，将被排除在外。
参数：fdr
numeric given the desired false discovery rate threshold, possibly a vector like: c(0.1, 0.05)
数字所需的假发现率的阈值，可能是一个向量，如：c(0.1, 0.05)
参数：samplesizes
numeric vector, giving the samplesizes for which the power will be estimated
数字向量，给予的权力将估计samplesizes
参数：plot
logical if TRUE plots the power curve and intersection for the given fdr(default plot=FALSE).
如果TRUE图逻辑的功率曲线，并给FDR路口（默认plot=FALSE）。
参数：type
what type of plot should be drawn
应当制定什么样的图类型
参数：ylim
range of y values
y值的范围
参数：xlim
range of x values
x值的范围
参数：xlab
a title for the x axis
X轴的标题
参数：ylab
a title for the y axis
为Y轴的标题
参数：main
an overall title for the plot
图的总冠军
参数：sub
a sub title for the plot
一个图子称号
参数：...
additional arguments to plot or par
额外的参数plot或par
Details
详情----------Details----------
Having estimated the proportion of non-differentially expressed genes and the density of effect-sizes an estimate of the average power is calculated at a given false discovery rate and sample size. Power and sample size analysis can be performed by estimating the average power for sample sizes other then the pilot data. Ferreira and Zwinderman (2006) show that the average power (the proportion of rejected hypothesis out of all alternative hypothesis) of the adaptive Benjamini-Hochberg procedure is estimated by the point where the CDF of p-values under the alternative hypothesis intersects the straight line with a slope determined by the given FDR and the estimated proportion of non-differentially expressed genes. Using plot=TRUE the CDF of p-values under the alternative hypothesis is shown with the intersecting lines for different FDRs and sample sizes. Don't use more than 2 FDRs and more than 3 different sample sizes because the plot will then be unclear.
估计非差异表达基因的比例和效果大小的估计是在给定的错误发现率和样本大小计算平均功率密度。估计样本大小等，然后试验数据的平均功耗可以由电源和样本大小分析。费雷拉和Zwinderman的（2006年）的的自适应Benjamini Hochberg过程的平均功率（所有替代假说，拒绝假说的比例）由替代假说下的P-值民防直线相交点估计由FDR和非差异表达基因的估计比例确定的斜坡。使用plot=TRUEp值替代假设下的民防部队不同FDRs和样本大小的相交线所示。不要使用超过2 FDRs超过3个不同的样本大小，因为图届时不清楚的。
值----------Value----------
estimated average power, probabily a named matrix with on the rows different sample sizes and on the columns the different false discovery rates.
估计的平均功耗，probabily名为矩阵与行不同的样本大小和不同的错误发现率列。
作者（S）----------Author(s)----------
Maarten van Iterson
参考文献----------References----------
Approximate Power and Sample Size Calculations with Microarray Data: An Illustration.
举例----------Examples----------
library(multtest)
data(golub)
teststat <- mt.teststat(golub, golub.cl)
table(golub.cl)
pd <- pilotData(name="golub", testStatistics=teststat, sampleSizeA=11, sampleSizeB=27)
hist(pd)
plot(pd)
ss <- sampleSize(pd)
plotEffectSize(ss)
Power(ss)
##creating a plot estimate power vs. sample size[＃创建一个图估计功率与样本大小]
pwr <- Power(ss, plot = FALSE, samplesizes = c(5, 10, 15, 20), fdr=0.01)
plot(c(5, 10, 15, 20), pwr, ylim = c(0, 1), type = "b", ylab = "Power", xlab = "Sample size per group")
legend("bottomright", colnames(pwr), col=c(1:ncol(pwr)), pch=1, lty=1)
##creating a plot estimate power vs. sample size for different false discovery rates[＃创建一个图估计功率对样本大小不同的假发现率]
pwr <- Power(ss, plot = FALSE, samplesizes = c(5, 10, 15, 20), fdr=c(0.01, 0.05))
matplot(c(5, 10, 15, 20), pwr, ylim = c(0, 1), type = "b", pch=1, ylab = "Power", xlab = "Sample size per group")
legend("bottomright", colnames(pwr), col=c(1:ncol(pwr)), pch=1, lty=1)
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 2012-2-26 15:07:06
