AUC(sensR)
AUC()所属R语言包:sensR
AUC computation
AUC计算
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This is the default AUC function for scalar d-primes, which will compute Area Under the ROC curve (ROC is an acronym for receiver operating characteristic).
这标D-素数计算的ROC曲线下面积(ROC是受试者工作特征的缩写),这将是默认的AUC功能。
用法----------Usage----------
## Default S3 method:[默认方法]
AUC(d, se.d, scale = 1, CI.alpha = 0.05, ...)
## S3 method for class 'anota'
AUC(d, CI.alpha = 0.05, ...)
参数----------Arguments----------
参数:d
a unit lenght vector with the value of d-prime for which AUC is to be computed or a anota object from the fitting of a A-not A test with AnotA
一个单位长度向量,D-黄金的价值AUC是计算或anota对象从装修的A-的测试AnotA
参数:scale
a unit length vector giving the ratio of scale (ie. standard deviation) of the latent distribution for the no-class items relative to that of the yes-class items
单位长度矢量提供的潜在分布的无级项目规模之比(即标准差)相对的是一流的项目
参数:se.d
standard error of d (d-prime). If provided, the function will compute confidence limits of value of AUC—cf. in section value.
d(D-黄金标准误差)。如果提供的话,该函数将计算AUC-CF值的置信限。部分价值。
参数:CI.alpha
the type I level of the confidence interval of AUC
I型水平的置信区间AUC
参数:...
additional arguments passed integrate
额外的参数传递integrate
Details
详细信息----------Details----------
The function calls integrate to obtain the area under the ROC curve implied by d and scale.
该函数调用integrate获得的ROC曲线下面积暗示的d和scale。
Confidence limits are based on a normal approximation of d and not of AUC. The limits are computed, if an estimate of the standard error of d is provided. Note that the limits do not take the uncertainty in estimating the scale nor that of estimating the standard error of d into account.
置信区间是根据正常的近似d而不是AUC。的限度,如果被计算的估计值的标准误差d设置。请注意,不采取的限制中的不确定性估计规模,也不是估计的标准误差d考虑。
A print method is implemented for objects of class AUC.
一个打印方法,实施对象的类AUC。
值----------Value----------
A list with components. If se.d is supplied to the default method or if a discrim object is supplied, the object contains the latter three additional elements.
列表组件。如果se.d被供给到默认的方法,或如果判别分析供给对象,该对象包含后面的三个额外的元素。
<table summary="R valueblock"> <tr valign="top"><td>value</td> <td> the estimated value of AUC</td></tr> <tr valign="top"><td>res.int</td> <td> the result from the call to integrate</td></tr> <tr valign="top"><td>lower</td> <td> the lower confidence limit</td></tr> <tr valign="top"><td>upper</td> <td> the upper confidence limit</td></tr> <tr valign="top"><td>CI.alpha</td> <td> echoes the provided CI.alpha</td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD> value</ TD> <TD>的估计值AUC </ TD> </ TR> <TR VALIGN =“顶“<TD> res.int </ TD> <TD>结果从调用integrate </ TD> </ TR> <tr valign="top"> <TD> X> </ TD> <TD>置信下限</ TD> </ TR> <tr valign="top"> <TD>lower </ TD> <TD>置信上限< / TD> </ TR> <tr valign="top"> <TD>upper </ TD> <TD>相呼应所提供的CI.alpha </ TD> </ TR> </表>
(作者)----------Author(s)----------
Rune Haubo B Christensen
实例----------Examples----------
(odor <- matrix(c(112, 112, 72, 53, 22, 4, 7, 38, 50, 117, 101, 62), 2,
byrow = TRUE))
(d.primes <- SDT(odor)[,3])
for(i in 1:5) print(AUC(d.primes[i]))
## Provide standard error of d-prime and compute CI:[#提供标准的D-素数,计算CI的错误:]
fm1 <- AnotA(8, 25, 1, 25)
AUC(fm1$coef, fm1$se)
AUC(fm1)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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