influence.rma.uni(metafor)
influence.rma.uni()所属R语言包：metafor
Case Diagnostics for rma.uni Objects
案例诊断rma.uni对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function calculates various case diagnostics that indicate the influence of deleting one case at a time on the model fit and the fitted/residual values for objects of class "rma.uni".
该函数计算各种情况下的诊断，删除一个模型拟合情况下，在上一次的影响和装/剩余价值的对象类"rma.uni"。
用法----------Usage----------
## S3 method for class 'rma.uni'
influence(model, digits=model$digits, ...)
参数----------Arguments----------
参数：model
an object of class "rma.uni".
对象类"rma.uni"。
参数：digits
an integer specifying the number of decimal places to which the printed results should be rounded (the default is to take the value from the object).
一个整数，指定打印的结果应四舍五入的小数位数（默认为对象的值）。
参数：...
other arguments.
其他参数。
Details
详细信息----------Details----------
The following leave-one-out diagnostics are calculated for each study:
计算每个研究下面留一诊断：
externally standardized residual,
外部的标准化残差，
DFFITS value,
DFFITS值，
Cook's distance,
库克的距离，
covariance ratio,
协方差的比例，
the leave-one-out amount of (residual) heterogeneity,
留一出量（剩余）的异质性，
the leave-one-out test statistic for the test of (residual) heterogeneity, and
留一出检验统计量（剩余）异质性的考验，
DFBETAS value(s).
DFBETAS值（S）。
The diagonal elements of the hat matrix and the weights (in %) given to the observed effects or outcomes during the model fitting are also provided (except for their scaling, the hat values and weights are the same for models without moderators, but will differ when moderators are included).
的对角线元素的帽子的矩阵和权重（％）给模型拟合期间所观察到的效应或结果还提供了（除了其缩放，帽子值和权重是相同的模型，而无需调节剂，但将不同当主持人都包括在内）。
For details on externally standardized residuals, see rstudent.rma.uni.
外部标准化残差的详细信息，请参阅rstudent.rma.uni。
The DFFITS value essentially indicates how many standard deviations the predicted average effect for the ith study changes after excluding the ith study from the model fitting.
DFFITS值基本上表明多少个标准差的预测平均ith研究后不包括ith研究从模型的拟合效果。
Cook's distance can be interpreted as the Mahalanobis distance between the entire set of predicted values once with the ith study included and once with the ith study excluded from the model fitting.
Cook距离整个组预测值之间的Mahalanobis距离可以被解释为一次与ith研究包括，一旦与ith研究排除从模型拟合。
The covariance ratio is defined as the determinant of the variance-covariance matrix of the parameter estimates based on the dataset with the ith study removed divided by the determinant of the variance-covariance matrix of the parameter estimates based on the complete dataset. A value below 1 therefore indicates that removal of the ith study yields more precise estimates of the model coefficients.
的协方差比的定义完整的数据集的基础上估计得出的数据集ith删除的参数方差 - 协方差矩阵的行列式除以估计的参数方差 - 协方差矩阵的行列式。值小于1表明，去除ith的研究产生更精确的估计模型系数。
The leave-one-out amount of (residual) heterogeneity is the estimated value of tau^2 based on the dataset with the ith study removed. Note that this is always equal to 0 for fixed-effects models.
留一出量（剩余）异质性是tau^2的ith研究删除的数据集的基础上的估计值。请注意，这是始终等于0固定效应模型。
Similarly, the leave-one-out test statistic for the test of (residual) heterogeneity is the value of the test statistic of the test for (residual) heterogeneity calculated based on the dataset with the ith study removed.
同样，留一出检验统计量的异质性测试（剩余）（剩余）的ith研究删除的数据集的基础上计算的异质性检验统计量的测试值。
Finally, the DFBETAS value(s) essentially indicate(s) how many standard deviations the estimated coefficient(s) change(s) after excluding the ith study from the model fitting.
最后，DFBETAS的值（s）基本上（S）多少个标准差的估计系数（S）不包括ith研究从模型的拟合后的变化（S）。
值----------Value----------
An object of class "infl.rma.uni". The object is a list containing the following components: <table summary="R valueblock"> <tr valign="top"><td>inf</td> <td> A data frame with columns equal to the externally standardized residuals, DFFITS values, Cook's distances, covariance ratios, leave-one-out tau^2 estimates, leave-one-out (residual) heterogeneity test statistics, hat values, and weights.</td></tr> <tr valign="top"><td>dfb</td> <td> A data frame with columns equal to the DFBETAS values.</td></tr> <tr valign="top"><td>...</td> <td> some additional elements/values.</td></tr>
对象的类"infl.rma.uni"。对象是一个列表，其中包含以下组件：<table summary="R valueblock"> <tr valign="top"> <TD> inf</ TD> <td>一个数据框列等于外部的标准化残差DFFITS值，库克的距离，协方差比率，留一tau^2估计，留一出异质性检验（剩余）的统计，帽值，和权重。</ TD> </ TR > <tr valign="top"> <TD> dfb</ TD> <td>一个数据框等于DFBETAS值列。</ TD> </ TR> <TR VALIGN =“顶” > <TD> ... </ TD> <TD>一些额外的元素/值。</ TD> </ TR>
</table> The results are printed with print.infl.rma.uni and plotted with plot.infl.rma.uni.
</ TABLE>打印结果与print.infl.rma.uni和策划与plot.infl.rma.uni。
注意----------Note----------
Right now, the leave-one-out diagnostics are calculated by refitting the model k times. Depending on how large k is, it may take a few moments to finish the calculations. There are shortcuts for calculating at least some of these values without refitting the model each time, but these are currently not implemented (and may not exist for all of the leave-one-out diagnostics calculated by the present function).
眼下，留一诊断改装模型k倍计算。根据大k是，它可能需要一些时间来完成计算。有用于计算这些值中的至少一些不重新安装的模型中，每个时间的快捷方式，但这些当前未实现（可能不存在可用于所有的留一诊断由本函数计算）。
It may not be possible to fit the model after deletion of the ith study from the dataset. This will result in NA values for that study.
它可能无法删除的ith研究的数据集，以适应后的模型。这将导致在NA值用于该研究。
Certain relationships between the leave-one-out diagnostics and the (internally or externally) standardized residuals (Belsley, Kuh, & Welsch, 1980; Cook & Weisberg, 1982) no longer hold for the meta-analytic models. Maybe there are other relationships. These remain to be determined.
一定关系留一诊断和（内部或外部）标准化残差（贝尔斯利山，韦尔施，1980年库克和韦斯伯格，1982年）不再担任的荟萃分析模型。也许还有其他的关系。这些仍有待确定。
（作者）----------Author(s)----------
Wolfgang Viechtbauer <a href="mailto:wvb@metafor-project.org">wvb@metafor-project.org</a> <br>
project homepage: <a href="http://www.metafor-project.org/">http://www.metafor-project.org/</a> <br>
author homepage: <a href="http://www.wvbauer.com/">http://www.wvbauer.com/</a>
参考文献----------References----------
Belsley, D. A., Kuh, E., & Welsch, R. E. (1980). Regression diagnostics. New York: Wiley.
Cook, R. D. & Weisberg, S. (1982). Residuals and influence in regression. London: Chapman and Hall.
Hedges, L. V. & Olkin, I. (1985). Statistical methods for meta-analysis. San Diego, CA: Academic Press.
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. http://www.jstatsoft.org/v36/i03/.
Viechtbauer, W. & Cheung, M. W.-L. (2010). Outlier and influence diagnostics for meta-analysis. Research Synthesis Methods, 1, 112–125.
参见----------See Also----------
print.infl.rma.uni, plot.infl.rma.uni, rstudent.rma.uni, hatvalues.rma.uni
print.infl.rma.uni，plot.infl.rma.uni，rstudent.rma.uni，hatvalues.rma.uni
实例----------Examples----------
### load BCG vaccine data[＃＃负荷卡介苗（BCG）]
data(dat.bcg)
### meta-analysis of the log relative risks using a mixed-effects model[＃＃使用混合效应模型荟萃分析的log相对风险]
### with two moderators (absolute latitude and publication year)[＃＃两个主持人（绝对纬度和出版年份）]
res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, mods=cbind(ablat, year),
data=dat.bcg, measure="RR", method="REML")
influence(res)
plot(influence(res))
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 2012-9-23 09:30:08
