getPowerFitNonNested(simsem)
getPowerFitNonNested()所属R语言包：simsem
Find power in rejecting non-nested models based on the differences in fit indices
拒绝非嵌套模型拟合指数的差异的基础上，查找权力
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Find the proportion of the difference in fit indices from one model that does not in the range of sampling distribution from another model (reject that the dataset comes from the second model) or indicates worse fit than a specified cutoff.
找到的比例拟合指数的差异，从一个模型，没有从另一个模型（拒绝该数据集从第二个模型）的抽样分布范围，或表明适合于指定的截止差。
用法----------Usage----------
getPowerFitNonNested(dat2Mod1, dat2Mod2, cutoff, ...)
参数----------Arguments----------
参数：dat2Mod1
SimResult that saves the simulation of analyzing Model 1 by datasets created from Model 2
SimResult，节省了模拟分析模型1模型2所创建的数据集
参数：dat2Mod2
SimResult that saves the simulation of analyzing Model 2 by datasets created from Model 2
SimResult，节省了模拟分析模型2模型2所创建的数据集
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：...
Additional arguments
附加参数
值----------Value----------
List of power given different fit indices.
赋予的权力不同的拟合指数列表。
方法----------Methods----------
This method will find the the differences in fit indices from dat2Mod1 and dat2Mod2 that provides worse fit than the cutoff. The additional arguments are revDirec, usedFit, nVal, pmMCARval, pmMARval, condCutoff, and df, which are needed when using varying sample sizes or percent missing across replications in SimResult. The revDirec is whether to reverse a direction. The default is to count the proportion of the difference of fit indices that lower than the specified cutoffs, such as how many the difference in RMSEA in the alternative model that is lower than cutoffs. The direction can be reversed by setting as TRUE. The usedFit is the vector of names of fit indices that researchers wish to get power from. The default is to get the powers of all fit indices. The nVal is the sample size value that researchers wish to find the fit indices cutoffs from. The pmMCARval is the percent missing completely at random value that researchers wish to find the fit indices cutoffs from. The pmMARval is the percent missing at random value that researchers wish to find the fit indices cutoffs from. The condCutoff is a logical. If TRUE, the cutoff is applicable only a given set of nVal, pmMCARval, and pmMARval. If FALSE, the cutoff is applicable in any values of sample size and percent missing. The df is the degree of freedom used in spline method in predicting the fit indices by the predictors. If df is 0, the spline method will not be applied.
这个方法就可以找到契合度的差异dat2Mod1和dat2Mod2，提供适合比cutoff差。额外的参数revDirec，usedFit，nVal，pmMCARval，pmMARval，condCutoff和df，这是必要的时使用不同的样本量或在重复，缺少SimResult％。 revDirec是扭转方向。默认值是拟合指数的差异数的比例低于指定的临界值，如多少RMSEA中的另一种模式，即低于临界值的差异。的方向是可以逆转的通过设置TRUE。 usedFit是矢量，研究人员希望得到权力的拟合指数的名称。默认是所有的拟合指数的权力。 nVal为样本，研究人员希望找到拟合指数临界值的大小值。 pmMCARval是完全随机值，研究人员希望找到拟合指数临界值的百分比失踪。 pmMARval是失踪的随机值，研究人员希望找到拟合指数临界值的百分比。 condCutoff是一个逻辑。如果TRUE，截止仅适用于一组给定的nVal，pmMCARval，pmMARval。如果FALSE，截止适用于任何值的样本的大小和百分比失踪。 df程度的自由中使用的样条方法在预测的拟合指数的预测。如果df是0，样条方法将不适用。
The details are similar to the method for dat2Mod1="SimResult", dat2Mod2="SimResult", and cutoff="vector". The cutoff argument must not be specified. Rather, the dat1Mod1 and dat1Mod2, which are additional arguments of this method, are required. The dat1Mod1 is the SimResult that saves the simulation of analyzing Model 1 by datasets created from Model 1. The dat1Mod2 is the SimResult that saves the simulation of analyzing Model 2 by datasets created from Model 1. The another additional argument is onetailed that is to derive the cutoff by using one-tailed test if specified as TRUE.
类似的方法dat2Mod1="SimResult"，dat2Mod2="SimResult"和cutoff="vector"的详细信息。 cutoff参数必须不被指定。相反，dat1Mod1和dat1Mod2，这是额外的参数这种方法，需要。 dat1Mod1是SimResult，节省了模拟分析模型1模型1所创建的数据集。 dat1Mod2是SimResult，节省了模拟分析模型2模型1所创建的数据集。另一个额外的参数是onetailed这是截止使用单尾测试，如果指定为TRUE。
（作者）----------Author(s)----------
Sunthud Pornprasertmanit (University of Kansas; <a href="mailto:psunthud@ku.edu">psunthud@ku.edu</a>)
参见----------See Also----------
getCutoffNonNested to find the cutoffs for non-nested model comparison
getCutoffNonNested找到的截断的非嵌套模型的比较
SimResult to see how to create simResult
SimResult来看看如何创建simResult
实例----------Examples----------
## Not run: [＃不运行：]
n1 <- simNorm(0, 0.1)
u79 <- simUnif(0.7, 0.9)
loading.A <- matrix(0, 8, 2)
loading.A[1:3, 1] <- NA
loading.A[4:8, 2] <- NA
LX.A <- simMatrix(loading.A, 0.7)
latent.cor <- matrix(NA, 2, 2)
diag(latent.cor) <- 1
RPH <- symMatrix(latent.cor, "u79")
RTD <- symMatrix(diag(8))
CFA.Model.A <- simSetCFA(LY = LX.A, RPS = RPH, RTE = RTD)
error.cor.mis <- matrix(NA, 8, 8)
diag(error.cor.mis) <- 1
RTD.Mis <- symMatrix(error.cor.mis, "n1")
CFA.Model.A.Mis <- simMisspecCFA(RTE = RTD.Mis)
loading.B <- matrix(0, 8, 2)
loading.B[1:4, 1] <- NA
loading.B[5:8, 2] <- NA
LX.B <- simMatrix(loading.B, 0.7)
CFA.Model.B <- simSetCFA(LY = LX.B, RPS = RPH, RTE = RTD)
SimData.A <- simData(CFA.Model.A, 500)
SimData.B <- simData(CFA.Model.B, 500)
SimModel.A <- simModel(CFA.Model.A)
SimModel.B <- simModel(CFA.Model.B)
# 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.A.A <- simResult(10, SimData.A, SimModel.A)
Output.A.B <- simResult(10, SimData.A, SimModel.B)
Output.B.A <- simResult(10, SimData.B, SimModel.A)
Output.B.B <- simResult(10, SimData.B, SimModel.B)
getPowerFitNonNested(Output.B.A, Output.B.B, dat1Mod1=Output.A.A, dat1Mod2=Output.A.B)
getPowerFitNonNested(Output.B.A, Output.B.B, cutoff=c(AIC=0, BIC=0))
## End(Not run)[＃（不执行）]
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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。
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发表于 2012-9-30 09:21:00
