SimMissing-class(simsem)
SimMissing-class()所属R语言包：simsem
Class "SimMissing"
类“SimMissing”
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Missing information imposing on the complete dataset
缺少的信息气势上完整的数据集
类对象----------Objects from the Class----------
Objects can be created by simMissing function. It can also be called from the form new("SimMissing", ...).
对象可以创建的simMissing功能。它也可以被称为，从形式new("SimMissing", ...)。
插槽----------Slots----------
cov: Column indices of any normally distributed covariates used in the data set.
cov：任何正态分布的协变量的数据集的列索引。
pmMCAR: Decimal percent of missingness to introduce completely at random on all variables.
pmMCAR：十进制％的missingness介绍完全随机对所有的变量。
pmMAR: Decimal percent of missingness to introduce using the listed covariates as predictors.
pmMAR：十进制％的missingness介绍上市的协变量的预测。
nforms: The number of forms for planned missing data designs, not including the shared form.
nforms：计划丢失的数据设计，不包括共享的形式的形式。
itemGroups: List of lists of item groupings for planned missing data forms. Without this, items will be divided into groups sequentially (e.g. 1-3,4-6,7-9,10-12)
itemGroups列表：列出项目组计划丢失的数据形式。没有这一点，项目将被分为组顺序（例如1-3,4-6,7-9,10-12）
twoMethod: Vector of (percent missing, column index). Will put a given percent missing on that column in the matrix to simulate a two method
twoMethod：矢量（％丢失，列索引）。将提出一个给定的百分比，在基质中，以模拟在该列上缺少两个方法
timePoints: Number of timepoints items were measured over. For longitudinal data, planned missing designs will be implemented within each timepoint.
timePoints：时间点项目的数量进行测量。纵向数据，将实施计划缺少的设计在每一个时间点。
numImps: The number of imputations to be used when multiply imputing missing data. Setting numImps to 0 will use FIML to handle missing data.
numImps：的数量时要使用的乘法填充缺失数据的插补。处理缺失数据，将使用FIML将numImps设置为0。
impMethod: Package that will be used for imputation. Currently only Amelia is supported.
impMethod：将用于归集的包。目前，只有阿米莉亚的支持。
ignoreCols: The columns not imposed any missing values for any missing data patterns
ignoreCols：列不施加任何缺失值的任何丢失的数据模式
threshold: The threshold of covariates that divide between the area to impose missing and the area not to impose missing. The default threshold is the mean of the covariate.
threshold：阈值的协变量之间的鸿沟的区域征收人失踪，宅碱基的面积不得征收缺少的。预设的阈值协变量的平均值。
prAttr: Probability (or vector of probabilities) of an entire case being removed due to attrition at a given time point. See imposeMissing for further details.
prAttr：被去除由于磨损在给定时间点的整个壳体的概率（或矢量的概率）。见imposeMissing进一步的细节。
covAsAux: If TRUE, the covariate listed in the object will be used as auxiliary variables when putting in the model object. If FALSE, the covariate will be included in the analysis.
covAsAux：如果TRUE，协变量中列出的对象将被用来作为辅助变量时，模型中的对象。如果FALSE，协将被包括在分析中。
logical: A matrix of logical values (TRUE/FALSE). If a value in the dataset is corresponding to the TRUE in the logical matrix, the value will be missing.
logical：矩阵的逻辑值（TRUE/FALSE）。如果在数据集中的值是对应的TRUE的逻辑矩阵，该值将丢失。
opts: A list of additional options to be passed to the imputation method specified in impMethod.
opts：一个额外的选项列表将被传递给指定的impMethod的插补方法。
方法----------Methods----------
summary To summarize the object
summary总结对象
run To impose missing information into data
run“”征收缺少的信息数据
（作者）----------Author(s)----------
Patrick Miller(University of Kansas; <a href="mailto:patr1ckm@ku.edu">patr1ckm@ku.edu</a>)
Alexander M. Schoemann (University of Kansas; <a href="mailto:schoemann@ku.edu">schoemann@ku.edu</a>)
Kyle Lang (University of Kansas; <a href="mailto:kylelang@ku.edu">kylelang@ku.edu</a>)
Sunthud Pornprasertmanit (University of Kansas; <a href="mailto:psunthud@ku.edu">psunthud@ku.edu</a>)
参见----------See Also----------
imposeMissing for directly imposing missingness into a dataset.
imposeMissing为直接气势missingness到一个数据集。
实例----------Examples----------
# No Example[否示例]
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 09:29:24
