pheno.list(CGEN)
pheno.list()所属R语言包：CGEN
List to describe the covariate and outcome data
列出来形容协及结果数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The list to describe the covariate and outcome data for snp.scan.logistic
列表来形容snp.scan.logistic协变量和结果的数据
格式----------Format----------
The format is: List of 11
格式是：列表11
file Covariate data file. This file must have variable names, two of which being an id variable and a response variable (see id.var and response.var).
文件的协方差数据。此文件必须有变量名，其中两个是一个id变量和反应变量（见id.var和response.var）。
id.var Name of the id variable.
id变量id.var名。
response.var Name of the binary response variable. This variable must be coded as 0 and 1.
response.var二进制响应变量的名称。这个变量必须被编码为0和1。
strata.var Stratification variable name or a formula for variables in file. See the strata.var argument in snp.logistic for more details. The default is NULL so that all observations
strata.var分层变量名或变量file公式。在strata.var更多详情，请参阅snp.logistic参数。默认值为NULL，使所有意见
main.vars Character vector of variables names or a formula for variables in file that will be included in the model as main effects.
main.vars特征向量的变量名或变量的公式file这将包括在模型中为主要的影响。
int.vars Character vector of variable names or a formula for variables in file that will be included in the model as interactions with each SNP in the genotype data.
变量名或变量的公式int.vars特征向量file这将包括在模型中每个SNP基因型数据中的相互作用。
file.type 1, 3, 4. 1 is for an R object file created with the save() function. 3 is for a table that will be read in with read.table(). 4 is for a SAS data set.
file.type 1，3，4。 1是一个R对象save()函数创建的文件。 3是一个将阅读与read.table()表。四是为SAS数据集。
delimiter The delimiter in file.
分隔符分隔符file。
factor.vars Vector of variable names to convert into factors.
factor.vars向量的变量名转换成因素。
in.miss Vector of character strings to define the missing values. This option corresponds to the option na.strings in read.table().
in.miss向量的字符串定义缺失值。该选项对应的选项na.stringsread.table()。
sas.list See sas.list.
sas.list见sas.list。
Details
详情----------Details----------
In this list, file, id.var, and response.var must be specified. The variable id.var is the link between the covariate data and the genotype data. For each subject id, there must be the same subject id in the genotype data for that subject to be included in tha analysis. <br> Missing data: If any of the variables defined in main.vars, int.vars, strata.var, or response.var contain missing values, then those subjects will be removed from the covariate and outcome data. After the subjects with missing values are removed, the subject ids are matched with the genotype data.
在这份名单中，file，id.var，response.var必须指定。变量id.var协的数据和基因型数据之间的联系。每个主题的ID，必须是同一主题的ID在该课题被列入THA分析基因型数据。参考缺少的数据：如果任何变量定义在main.vars，int.vars，strata.var或response.var包含缺失值，那么这些科目从协删除结果数据。遗漏值的对象将被删除后，受IDS匹配的基因型数据。
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 2012-2-25 14:28:05
