pValue(simsem)
pValue()所属R语言包：simsem
Find p-values (1 - percentile)
查找p-值（1 - 百分位）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function will provide p value from comparing number and vector or the analytic result to the observed data (in SimModelOut) and the simulation result (in SimResult).
此功能将提供p值比较数量和矢量或分析的结果，观测到的数据（在SimModelOut）的模拟结果（在SimResult）。
用法----------Usage----------
pValue(target, dist, ...)
参数----------Arguments----------
参数：target
A value, multiple values, or a model output object used to find p values. This argument could be a cutoff of a fit index.
A值，多个值，或找到p值模型输出对象。这个参数可以是一个合适的指数截止。
参数：dist
The comparison distribution, which can be a vector of numbers, a data frame, or a result object.
比较分布，它可以是一个矢量的号码，一个数据框，或一个结果对象。
参数：...
Other values that will be explained specifically for each class
其他值，将具体说明用于每个类别
Details
详细信息----------Details----------
In comparing fit indices, the p value is the proportion of the number of replications that provide poorer fit (e.g., less CFI value or greater RMSEA value) than the analysis result from the observed data. If the target is a critical value (e.g., fit index cutoff) and the dist is the sampling distribution underlying the alternative hypothesis, this function can provide a statistical power.
在比较拟合指数，p值是比从所观察到的数据的分析结果提供较差的适合复制的数目（例如，更少的CFI的值或更大的RMSEA值）的比例。如果target是一个临界值（例如，适合指数截止）和dist是抽样分布的另一种假设的基础，此功能可提供的统计功率。
值----------Value----------
Mostly, this function provides a vector of p values based on the comparison. If the target is a model output object and dist is a result object, the p values of fit indices are provided, as well as two additional values: andRule and orRule. The andRule is based on the principle that the model is retained only when all fit indices provide good fit. The proportion is calculated from the number of replications that have all fit indices indicating a better model than the observed data. The proportion from the andRule is the most stringent rule in retaining a hypothesized model. The orRule is based on the principle that the model is retained only when at least one fit index provides good fit. The proportion is calculated from the number of replications that have at least one fit index indicating a better model than the observed data. The proportion from the orRule is the most lenient rule in retaining a hypothesized model.
大多数情况下，这个功能提供基于该比较的P值的矢量。如果目标是模型输出对象和区是结果对象，拟合指数的P值，以及另外两个值：andRule和orRule。 andRule的基础上，该模型时，只保留了所有的拟合指数提供适合的原则。有一个更好的模型比观测到的数据拟合指数的复制数的比例计算。的比例从andRule保留一个假设的模型是最严格的规则。 orRule的基础上，该模型保留，只有当至少有一个合适的索引提供适合的原则。至少有一个合适的指标一个更好的模型比观测到的数据复制数的比例计算。的比例从orRule保留一个假设的模型是最宽松的规则。
方法----------Methods----------
This method will find the p value (quantile rank) of the target value on the dist vector. The additional arguments are revDirec, x , xval, condCutoff, and df. The revDirec is a logical argument whether to reverse the direction of comparison. If TRUE, the proportion of the dist that is lower than target value is reported. If FALSE, the proportion of the dist that is higher than the target value is reported. The x is the data.frame of the predictor values. The number of rows of the x argument should be equal to the number of rows in the dist. The xval is the values of predictor that researchers would like to find the fit indices cutoffs from. The condCutoff is a logical argument. If TRUE, the cutoff is applicable only a given value of xval. If FALSE, the cutoff is applicable in any values of predictor. 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.
此方法将找到的target值dist矢量的p值（分位数级）。额外的参数是revDirec，x，xval，condCutoff和df。 revDirec是一个符合逻辑的论据是否扭转方向的比较。如果TRUE，dist的比例即低于target值据悉。如果FALSE，dist的比例，是高于target值的报告。 x是data.frame的预测值。行x参数的数量应等于在dist的行数。 xval是，研究人员希望找到的拟合指数临界值的预测值。 condCutoff是一个符合逻辑的论据。如果TRUE，截止是只适用的给定值xval。如果FALSE，截止适用于任何值predictor。 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。
This method will find the p value of each columns in the dist based on the value specified in the target. The additional arguments are revDirec, x , xval, df, and asLogical. The revDirec is a logical vector whether to reverse the direction of comparison. If TRUE, the proportion of the dist that is lower than target value is reported. If FALSE, the proportion of the dist that is higher than the target value is reported. The x is the data.frame of the predictor values. The number of rows of the x argument should be equal to the number of rows in the dist. The xval is the values of predictor that researchers would like to find the fit indices cutoffs from. 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. The asLogical is to provide the result as the matrix of significance result (TRUE) or just the proportion of significance result (FALSE).
此方法将每列的p值在dist根据指定的值在target。额外的参数是revDirec，x，xval，df和asLogical。 revDirec是一个逻辑向量是否扭转方向的比较。如果TRUE，dist的比例即低于target值据悉。如果FALSE，dist的比例，是高于target值的报告。 x是data.frame的预测值。行x参数的数量应等于在dist的行数。 xval是，研究人员希望找到的拟合指数临界值的预测值。 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。 asLogical是提供结果作为的意义结果矩阵（TRUE）或只是比例的意义的结果（FALSE）。
This method will find the p value of the analysis result compared to the simulated sampling distribution in a result object (SimResult). The additional arguments are usedFit, nVal, pmMCARval, pmMARval, and df. The usedFit is the vector of names of fit indices that researchers wish to find the p value from. 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 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.
此方法会发现p值相比，一个结果对象的模拟抽样分布（SimResult）的分析结果。额外的参数是usedFit，nVal，pmMCARval，pmMARval和df。 usedFit是向量，研究人员希望找到p值的拟合指数的名称。 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。 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。
（作者）----------Author(s)----------
Sunthud Pornprasertmanit (University of Kansas; <a href="mailto:psunthud@ku.edu">psunthud@ku.edu</a>)
参见----------See Also----------
SimModelOut to see how to get the analysis result of observed data
SimModelOut来看看如何得到观测数据的分析结果
SimResult to run a simulation study
SimResult运行的模拟研究
runFit to run a simulation study based on the parameter estimates from the analysis result of observed data
runFit运行参数的模拟研究的基础上估计，从观测数据的分析结果
实例----------Examples----------
## Not run: [＃不运行：]
# Compare number with a vector[比较与一个向量的数目]
pValue(0.5, rnorm(1000, 0, 1))
# Compare numbers with a data frame[比较用的数据框的数目]
pValue(c(0.5, 0.2), data.frame(rnorm(1000, 0, 1), runif(1000, 0, 1)))
# Compare an analysis result with a result of simulation study[与模拟研究的结果比较的分析结果]
library(lavaan)
loading <- matrix(0, 9, 3)
loading[1:3, 1] <- NA
loading[4:6, 2] <- NA
loading[7:9, 3] <- NA
model <- simParamCFA(LY=loading)
SimModel <- simModel(model, indLab=paste("x", 1:9, sep=""))
u2 <- simUnif(-0.2, 0.2)
loading.trivial <- matrix(NA, 9, 3)
loading.trivial[is.na(loading)] <- 0
LY.trivial <- simMatrix(loading.trivial, "u2")
mis <- simMisspecCFA(LY = LY.trivial)
out <- run(SimModel, HolzingerSwineford1939)
Output2 <- runFit(out, HolzingerSwineford1939, 20, mis)
pValue(out, Output2)
## 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。
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发表于 2012-9-30 09:25:19
