anova.mlm(stats)
anova.mlm()所属R语言包：stats
Comparisons between Multivariate Linear Models
多元线性模型之间的比较
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute a (generalized) analysis of variance table for one or more multivariate linear models.
计算为一个或多个多元线性模型方差表（广义）分析。
用法----------Usage----------
## S3 method for class 'mlm'
anova(object, ...,
test = c("Pillai", "Wilks", "Hotelling-Lawley", "Roy", "Spherical"),
Sigma = diag(nrow = p), T = Thin.row(proj(M) - proj(X)),
M = diag(nrow = p), X = ~0,
idata = data.frame(index = seq_len(p)), tol = 1e-7)
参数----------Arguments----------
参数：object
an object of class "mlm".
对象类"mlm"。
参数：...
further objects of class "mlm".
进一步对象的类"mlm"。
参数：test
choice of test statistic (see below).
检验统计量的选择（见下文）。
参数：Sigma
(only relevant if test == "Spherical"). Covariance matrix assumed proportional to Sigma.
（仅有关test == "Spherical"）。协方差矩阵的假设Sigma成正比。
参数：T
transformation matrix. By default computed from M and X.
变换矩阵。默认情况下，从M和X计算。
参数：M
formula or matrix describing the outer projection (see below).
公式或矩阵描述外投影（见下文）。
参数：X
formula or matrix describing the inner projection (see below).
公式或矩阵描述（见下文）内的投影。
参数：idata
data frame describing intra-block design.
数据框描述块内的设计。
参数：tol
tolerance to be used in deciding if the residuals are rank-deficient: see qr.
容忍在决定使用残差秩缺陷：qr。
Details
详情----------Details----------
The anova.mlm method uses either a multivariate test statistic for the summary table, or a test based on sphericity assumptions (i.e. that the covariance is proportional to a given matrix).
anova.mlm方法使用汇总表为一个多元的检验统计量，或球形假设（即方差是一个给定的矩阵成正比）为基础的测试。
For the multivariate test, Wilks' statistic is most popular in the literature, but the default Pillai–Bartlett statistic is recommended by Hand and Taylor (1987). See summary.manova for further details.
多元测试，威尔克斯统计文献中最流行的，但默认皮莱巴特利特统计是由手和泰勒（1987年）的建议。看到summary.manova作进一步的细节。
For the "Spherical" test, proportionality is usually with the identity matrix but a different matrix can be specified using Sigma). Corrections for asphericity known as the Greenhouse–Geisser, respectively Huynh–Feldt, epsilons are given and adjusted F tests are performed.
为"Spherical"测试，比例通常是与身份矩阵，但可以使用一个不同的矩阵Sigma）。更正对温室Geisser，分别为黄长发Feldt称为非球面，epsilons和F测试进行调整。
It is common to transform the observations prior to testing. This typically involves transformation to intra-block differences, but more complicated within-block designs can be encountered, making more elaborate transformations necessary. A transformation matrix T can be given directly or specified as the difference between two projections onto the spaces spanned by M and X, which in turn can be given as matrices or as model formulas with respect to idata (the tests will be invariant to parametrization of the quotient space M/X).
改造之前测试的意见是很常见的。这通常涉及转换块内部的分歧，但更复杂的区块内的设计，使得有必要更详细的转换可能会遇到。转换矩阵T可以直接或指定的到M和X，这反过来又可以为矩阵或模型公式跨越空间的预测之间的差异尊重idata（测试将是不变的参数化的商空间M/X）。
As with anova.lm, all test statistics use the SSD matrix from the largest model considered as the (generalized) denominator.
anova.lm，所有的测试统计使用SSD的矩阵（广义）分母认为最大的模型。
Contrary to other anova methods, the intercept is not excluded from the display in the single-model case. When contrast transformations are involved, it often makes good sense to test for a zero intercept.
违反其他anova方法，拦截不排除从单一模式的情况下显示。当涉及对比转换，它往往是有道理的测试为零拦截。
值----------Value----------
An object of class "anova" inheriting from class "data.frame"
一个类的对象"anova"类"data.frame"继承
注意----------Note----------
The Huynh–Feldt epsilon differs from that calculated by SAS (as of v. 8.2) except when the DF is equal to the number of observations minus one. This is believed to be a bug in SAS, not in R.
黄长发Feldt小量不同于SAS（诉8.2）计算时除外DF是观测数减一等于。这被认为是在SAS中的一个错误，而不是在R
参考文献----------References----------
Multivariate Analysis of Variance and Repeated Measures. Chapman and Hall.
参见----------See Also----------
summary.manova
summary.manova
举例----------Examples----------
require(graphics)
utils::example(SSD) # Brings in the mlmfit and reacttime objects[带来的mlmfit和reacttime对象]
mlmfit0 <- update(mlmfit, ~0)
### Traditional tests of intrasubj. contrasts[＃传统的intrasubj测试。对比]
## Using MANOVA techniques on contrasts:[＃使用变异数分析对比技术：]
anova(mlmfit, mlmfit0, X=~1)
## Assuming sphericity[＃假设球形]
anova(mlmfit, mlmfit0, X=~1, test="Spherical")
### tests using intra-subject 3x2 design[＃测试使用内受3x2的设计]
idata <- data.frame(deg=gl(3,1,6,labels=c(0,4,8)),
noise=gl(2,3,6,labels=c("A","P")))
anova(mlmfit, mlmfit0, X = ~ deg + noise,
idata = idata, test = "Spherical")
anova(mlmfit, mlmfit0, M = ~ deg + noise, X = ~ noise,
idata = idata, test="Spherical" )
anova(mlmfit, mlmfit0, M = ~ deg + noise, X = ~ deg,
idata = idata, test="Spherical" )
f <- factor(rep(1:2,5)) # bogus, just for illustration[假的，只是为了说明]
mlmfit2 <- update(mlmfit, ~f)
anova(mlmfit2, mlmfit, mlmfit0, X = ~1, test = "Spherical")
anova(mlmfit2, X = ~1, test = "Spherical")
# one-model form, eqiv. to previous [一个模型的形式，eqiv。以前]
### There seems to be a strong interaction in these data[＃似乎有在这些数据的强相互作用]
plot(colMeans(reacttime))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
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发表于 2012-2-16 20:26:32
