anova(simsem)
anova()所属R语言包：simsem
Provide a comparison of nested models and nonnested models across replications
提供整个复制的嵌套模型和nonnested模型的比较
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function will provide averages of model fit statistics and indices for nested models. It will also provide average differences of fit indices and power for likelihood ratio tests of nested models.
此功能将提供嵌套模型模型拟合的统计数据和指标的平均值。它也将提供平均似然比检验的嵌套模型的拟合指数和功率的差异。
参数----------Arguments----------
参数：object
SimResult object being described. Currently at least two objects must be included as arguments
SimResult对象的描述。目前必须包含至少两个对象作为参数
参数：...
any additional arguments, such as additional objects or for the function with result object
任何额外的参数，如其他对象的功能，结果对象
值----------Value----------
A data frame that provides the statistics described above from all parameters. For using with SimModelOut, each column means
提供的统计数据一个数据框，上述所有参数。每列为了用SimModelOut，指
summary: The fit indices of each output
summary:每个输出的拟合指数
diff: The differences in fit indices among outputs
diff:输出拟合指数之间的差异
For using with linkS4class{SimResult}, the result is a list with two or three elements:
为了用linkS4class{SimResult}，结果是与两个或三个元素的列表：
summary: Average of fit indices across all replications
summary:在所有复制的拟合指数的平均
diff: Average of the differences in fit indices across all replications
diff:的平均拟合指数的差异，在所有复制
varyParam: The statistical power of chi-square difference test given values of varying parameters (such as sample size or percent missing)
varyParam:的统计功率的卡方差异测试不同的参数给定值（如样本量或缺少％）
（作者）----------Author(s)----------
Alexander M. Schoemann (University of Kansas; <a href="mailto:schoemann@ku.edu">schoemann@ku.edu</a>),
Sunthud Pornprasertmanit (University of Kansas; <a href="mailto:psunthud@ku.edu">psunthud@ku.edu</a>)
参见----------See Also----------
SimResult for the object input
SimResult的对象输入
实例----------Examples----------
loading1 <- matrix(0, 6, 1)
loading1[1:6, 1] <- NA
loading2 <- loading1
loading2[6,1] <- 0
LX1 <- simMatrix(loading1, 0.7)
LX2 <- simMatrix(loading2, 0.7)
RPH <- symMatrix(diag(1))
RTD <- symMatrix(diag(6))
CFA.Model1 <- simSetCFA(LY = LX1, RPS = RPH, RTE = RTD)
CFA.Model2 <- simSetCFA(LY = LX2, RPS = RPH, RTE = RTD)
SimData <- simData(CFA.Model1, 500)
SimModel1 <- simModel(CFA.Model1)
SimModel2 <- simModel(CFA.Model2)
# We make the examples running only 5 replications to save time.[我们的例子只有5次重复，以节省时间。]
# In reality, more replications are needed.[在现实中，需要更多的复制。]
# Need to make sure that both simResult calls have the same seed![需要，以确保，这两个simResult调用的相同的种子！]
Output1 <- simResult(5, SimData, SimModel1, seed=123567)
Output2 <- simResult(5, SimData, SimModel2, seed=123567)
anova(Output1, Output2)
Output1b <- simResult(NULL, SimData, SimModel1, seed=123567, n=seq(50, 500, 50))
Output2b <- simResult(NULL, SimData, SimModel2, seed=123567, n=seq(50, 500, 50))
anova(Output1b, Output2b)
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 2012-9-30 09:15:11
