eff.aovlist(stats)
eff.aovlist()所属R语言包：stats
Compute Efficiencies of Multistratum Analysis of Variance
多段方差分析计算效率
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computes the efficiencies of fixed-effect terms in an analysis of variance model with multiple strata.
计算固定效应方差分析模型与多个阶层的效率。
用法----------Usage----------
eff.aovlist(aovlist)
参数----------Arguments----------
参数：aovlist
The result of a call to aov with an Error term.
呼叫aov与Error长期的结果。
Details
详情----------Details----------
Fixed-effect terms in an analysis of variance model with multiple strata may be estimable in more than one stratum, in which case there is less than complete information in each. The efficiency for a term is the fraction of the maximum possible precision (inverse variance) obtainable by estimating in just that stratum. Under the assumption of balance, this is the same for all contrasts involving that term.
在固定效应方差分析模型与多个阶层而言可能是难能可贵的，在超过一个阶层，在这种情况下，有不到在每一个完整的信息。长期的效率是最大可能的精确的分数（逆差额），估计在地层只是索取。平衡的假设下，这是对所有涉及这个词的对比一样。
This function is used to pick strata in which to estimate terms in model.tables.aovlist and se.contrast.aovlist.
此功能用于选择阶层在其中估计model.tables.aovlist和se.contrast.aovlist。
In many cases terms will only occur in one stratum, when all the efficiencies will be one: this is detected and no further calculations are done.
在许多情况下只会出现在一个阶层，当所有的效率将是一个：这是检测并没有做进一步的计算。
The calculation used requires orthogonal contrasts for each term, and will throw an error if non-orthogonal contrasts (e.g. treatment contrasts or an unbalanced design) are detected.
用于计算要求每学期的正交对比，将抛出一个错误，如果检测到非正交对比（如治疗对比或不平衡的设计）。
值----------Value----------
A matrix giving for each non-pure-error stratum (row) the efficiencies for each fixed-effect term in the model.
矩阵让每个非纯错误层（行）为固定效应模型中的每个任期的效率。
参考文献----------References----------
Computation for the Analysis of Designed Experiments. Wiley.
参见----------See Also----------
aov, model.tables.aovlist, se.contrast.aovlist
aov，model.tables.aovlist，se.contrast.aovlist
举例----------Examples----------
## An example from Yates (1932),[＃一个例子耶茨（1932年），]
## a 2^3 design in 2 blocks replicated 4 times[＃2 ^ 3设计，2块复制的4倍]
Block <- gl(8, 4)
A <- factor(c(0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,
0,1,0,1,0,1,0,1,0,1,0,1))
B <- factor(c(0,0,1,1,0,0,1,1,0,1,0,1,1,0,1,0,0,0,1,1,
0,0,1,1,0,0,1,1,0,0,1,1))
C <- factor(c(0,1,1,0,1,0,0,1,0,0,1,1,0,0,1,1,0,1,0,1,
1,0,1,0,0,0,1,1,1,1,0,0))
Yield <- c(101, 373, 398, 291, 312, 106, 265, 450, 106, 306, 324, 449,
272, 89, 407, 338, 87, 324, 279, 471, 323, 128, 423, 334,
131, 103, 445, 437, 324, 361, 302, 272)
aovdat <- data.frame(Block, A, B, C, Yield)
old <- getOption("contrasts")
options(contrasts=c("contr.helmert", "contr.poly"))
(fit <- aov(Yield ~ A*B*C + Error(Block), data = aovdat))
eff.aovlist(fit)
options(contrasts = old)
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 2012-2-16 18:16:22
