plotPowerFit(simsem)
plotPowerFit()所属R语言包：simsem
Plot sampling distributions of fit indices that visualize power of rejecting datasets underlying misspecified models
图抽样分布拒绝的数据集可视化功率的契合度，潜在的误设模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function will plot sampling distributions of fit indices that visualize power in rejecting the misspecified models
此功能将绘制在拒绝误设模型的拟合指数的抽样分布，可视化功率
用法----------Usage----------
plotPowerFit(altObject, nullObject = NULL, cutoff = NULL, usedFit = NULL,
alpha = 0.05, contN = TRUE, contMCAR = TRUE, contMAR = TRUE,
useContour = TRUE, logistic = TRUE)
参数----------Arguments----------
参数：altObject
The result object (SimResult) saves the simulation result of fitting the hypothesized model when the hypothesized model is FALSE.
结果的对象（SimResult）节省了装修的假设模型假设的模型是FALSE的仿真结果。
参数：nullObject
The result object (SimResult) saves the simulation result of fitting the hypothesized model when the hypothesized model is TRUE. This argument may be not specified if the cutoff is specified.
结果的对象（SimResult）节省了装修的假设模型假设的模型是TRUE的仿真结果。这种说法可能不指定，如果cutoff指定。
参数：cutoff
A vector of priori cutoffs for fit indices.
一个向量的先验的截止时间为契合度。
参数：usedFit
Vector of names of fit indices that researchers wish to plot.
矢量，研究人员希望绘制的拟合指数的名称。
参数：alpha
A priori alpha level
先验α水平
参数：contN
Include the varying sample size in the power plot if available
包括不同样本大小的功率变化的曲线，如果有
参数：contMCAR
Include the varying MCAR (missing completely at random percentage) in the power plot if available
包括不同的MCAR（完全丢失在随机的百分比）在功率变化的曲线，如果有的话
参数：contMAR
Include the varying MAR (missing at random percentage) in the power plot if available
包括在功率变化的曲线，如果有不同的MAR（失踪在随机的百分比）
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。
参数：logistic
If logistic is TRUE and the varying parameter exists (e.g., sample size or percent missing), the plot based on logistic regression predicting the significance by the varying parameters is preferred. If FALSE, the overlaying scatterplot with a line of cutoff is plotted.
如果logisticTRUE和不同的参数（例如，样本大小或缺少％），图的基础上logistic回归分析预测的变参数的意义是首选。如果FALSE，散点图绘制线的截止覆盖。
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。
getCutoff to find values of cutoffs based on null hypothesis sampling distributions only
getCutoff值的临界值零假设抽样分布的基础上，
getPowerFit to find power of rejecting the hypothesized model when the hypothesized model is FALSE.
getPowerFit找到拒绝的假设模型假设的模型是FALSE的电源。
实例----------Examples----------
## Not run: [＃不运行：]
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)
SimData.NULL <- simData(CFA.Model.NULL, 500)
SimModel <- simModel(CFA.Model.NULL)
# 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。]
Output.NULL <- simResult(5, SimData.NULL, SimModel)
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, 0.5)
CFA.Model.ALT <- simSetCFA(LY = LX.ALT, RPS = RPH.ALT, RTE = RTD)
SimData.ALT <- simData(CFA.Model.ALT, 500)
Output.ALT <- simResult(5, SimData.ALT, SimModel)
plotPowerFit(Output.ALT, nullObject=Output.NULL, alpha=0.05, usedFit=c("RMSEA", "CFI", "TLI", "SRMR"))
Rule.of.thumb <- c(RMSEA=0.05, CFI=0.95, TLI=0.95, SRMR=0.06)
plotPowerFit(Output.ALT, cutoff=Rule.of.thumb, alpha=0.05, usedFit=c("RMSEA", "CFI", "TLI", "SRMR"))
Output.NULL2 <- simResult(NULL, SimData.NULL, SimModel, n=seq(50, 250, 25))
Output.ALT2 <- simResult(NULL, SimData.ALT, SimModel, n=seq(50, 250, 25))
plotPowerFit(Output.ALT2, nullObject=Output.NULL2, alpha=0.05, usedFit=c("RMSEA", "CFI", "TLI", "SRMR"))
plotPowerFit(Output.ALT2, cutoff=Rule.of.thumb, alpha=0.05, usedFit=c("RMSEA", "CFI", "TLI", "SRMR"))
## 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 09:24:10
