plotCutoffNested(simsem)
plotCutoffNested()所属R语言包：simsem
Plot sampling distributions of the differences in fit indices between nested models with fit indices cutoffs
图抽样分布的嵌套模型的拟合指数之间的拟合指数临界值的差异
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function will plot sampling distributions of the differences in fit indices between nested models if the nested model is true. The users may add cutoffs by specifying the alpha level.
此功能将绘制的嵌套模型的嵌套模型拟合指数之间的差异，如果是真正的抽样分布。用户可以添加的截断通过指定alpha水平的。
用法----------Usage----------
plotCutoffNested(nested, parent, alpha = 0.05, cutoff = NULL,
usedFit = NULL, useContour = T)
参数----------Arguments----------
参数：nested
SimResult that saves the analysis results of nested model from multiple replications
SimResult，节省了嵌套模型的分析结果，从多个复制
参数：parent
SimResult that saves the analysis results of parent model from multiple replications
SimResult，节省了父模型的分析结果，从多个复制
参数：alpha
A priori alpha level
先验α水平
参数：cutoff
A priori cutoffs for fit indices, saved in a vector
先验的截止时间为拟合指数，保存在一个向量
参数：usedFit
Vector of names of fit indices that researchers wish to plot the sampling distribution.
矢量，研究人员希望绘制的抽样分布的拟合指数的名称。
参数：useContour
If there are two of sample size, percent completely at random, and percent missing at random are varying, the plotCutoff function will provide 3D graph. Contour graph is a default. However, if this is specified as FALSE, perspective plot is used.
如果有两个样本量，％完全随机的，百分之随机缺失不同的，plotCutoff：功能将提供3D图形。等高线图是默认的。但是，如果这是指定作为FALSE，使用立体图。
值----------Value----------
NONE. Only plot the fit indices distributions.
NONE。仅绘制的拟合指数分布。
（作者）----------Author(s)----------
Sunthud Pornprasertmanit (University of Kansas; <a href="mailto:psunthud@ku.edu">psunthud@ku.edu</a>)
参见----------See Also----------
SimResult for simResult that used in this function.
SimResultsimResult中使用此功能。
getCutoffNested to find the difference in fit indices cutoffs
getCutoffNested找到拟合指数临界值的差异
实例----------Examples----------
## Not run: [＃不运行：]
n1 <- simNorm(0, 0.1)
u79 <- simUnif(0.7, 0.9)
loading.null <- matrix(0, 6, 1)
loading.null[1:6, 1] <- NA
LX.NULL <- simMatrix(loading.null, 0.7)
RPH.NULL <- symMatrix(diag(1))
RTD <- symMatrix(diag(6))
CFA.Model.NULL <- simSetCFA(LY = LX.NULL, RPS = RPH.NULL, RTE = RTD)
error.cor.mis <- matrix(NA, 6, 6)
diag(error.cor.mis) <- 1
RTD.Mis <- symMatrix(error.cor.mis, "n1")
CFA.Model.NULL.Mis <- simMisspecCFA(RTE = RTD.Mis)
loading.alt <- matrix(0, 6, 2)
loading.alt[1:3, 1] <- NA
loading.alt[4:6, 2] <- NA
LX.ALT <- simMatrix(loading.alt, 0.7)
latent.cor.alt <- matrix(NA, 2, 2)
diag(latent.cor.alt) <- 1
RPH.ALT <- symMatrix(latent.cor.alt, "u79")
CFA.Model.ALT <- simSetCFA(LY = LX.ALT, RPS = RPH.ALT, RTE = RTD)
SimData.NULL <- simData(CFA.Model.NULL, 500)
SimModel.NULL <- simModel(CFA.Model.NULL)
SimModel.ALT <- simModel(CFA.Model.ALT)
# The actual number of replications should be greater than 10.[的实际数目的复制应该是大于10。]
Output.NULL.NULL <- simResult(10, SimData.NULL, SimModel.NULL)
Output.NULL.ALT <- simResult(10, SimData.NULL, SimModel.ALT)
plotCutoffNested(Output.NULL.NULL, Output.NULL.ALT, alpha=0.05)
## End(Not run)[＃（不执行）]
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 09:23:21
