summary.snpLong(SimHap)
summary.snpLong()所属R语言包：SimHap
Summarizing single SNP analysis models for longitudinal data
单个SNP分析纵向数据模型综述
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Summary method for objects of class snpLong
摘要方法的类的对象的snpLong
用法----------Usage----------
## S3 method for class 'snpLong'
summary(object, ...)
## S3 method for class 'summary.snpLong'
print(x, digits = max(3, getOption("digits") - 3),
signif.stars = getOption("show.signif.stars"), ...)
参数----------Arguments----------
参数：object
an object of class snpLong, a result of a call to snp.long.
类的一个对象snpLong，其结果，调用snp.long。
参数：x
an object of class summary.snpLong, the result of a call to <PRE>summary.snpLong.</PRE>
类的一个对象summary.snpLong，结果的调用<PRE> summary.snpLong。</ PRE>
参数：digits
the number of significant digits to use when printing.
打印时所使用的数量显著数字。
参数：signif.stars
logical. If TRUE, “significance stars" are printed for each coefficient.
逻辑。如果TRUE，“意义明星”打印每个系数。
参数：...
further arguments passed to or from other methods.
进一步的参数传递给其他方法。
值----------Value----------
summary.snpLong returns an object of class summary.snpLong. Some components taken from summary.lme. A list with components
summary.snpLong返回一个对象类summary.snpLong。一些组件从summary.lme。组件列表
参数：call
the formula call.
的公式通话。
参数：terms
terms attribute of the formula called in snp.long.
条款属性的公式称为snp.long。
参数：fixDF
as per lmeObject. A list with components X and terms specifying the denominator degrees of freedom for, respectively, t-tests for the individual fixed effects and F-tests for the fixed-effects terms in the models.
如每lmeObject。的组件列表X和terms指定分母的自由度，分别为固定效应模型中的个体固定效应和F-检验，t检验。
参数：sigma
as per lmeObject. The estimated within-group error standard deviation.
如每lmeObject。组内估计误差标准差。
参数：groups
as per lmeObject. A data frame with the grouping factors as columns. The grouping level increases from left to right.
如每lmeObject。一个数据框作为列的分组因素。分组级别增加由左到右。
参数：dims
as per lmeObject. A list with basic dimensions used in the lme fit, including the components N - the number of observations in the data, Q - the number of grouping levels, qvec - the number of random effects at each level from innermost to outermost (last two values are equal to zero and correspond to the fixed effects and the response), ngrps - the number of groups at each level from innermost to outermost (last two values are one and correspond to the fixed effects and the response), and ncol - the number of columns in the model matrix for each level of grouping from innermost to outermost (last two values are equal to the number of fixed effects and one).
如每lmeObject。在伦敦金属交易所适合使用的基本尺寸，包括组件的列表N“ - 的若干意见中的数据，Q - 分组级别的数量，qvec - 随机数在从最内层到最外层的每一级的影响（最后两个值等于零，对应的固定效果和响应），ngrps - 在每个级别的组的数目，从最内层到最外层（最后两个值是一个并对应于固定的效果和响应）和ncol - 模型矩阵中的列的数目为每个分组级别从最内层到最外层（最后两个值是相等的固定效应的数目和一个） 。
参数：method
as per lmeObject. The estimation method: either “ML" for maximum likelihood, or “REML" for restricted maximum likelihood.
如每lmeObject。估算方法：要么“ML”最大的可能性，或REML“约束最大似然。
参数：coefficients
summarized results from fitted model, including coefficients, standard errors and p-values.
汇总结果拟合模型，包括系数，标准差和p值。
参数：formula
fixed effects formula used in snp.long.
固定效应在snp.long公式中使用。
参数：residuals
as per lmeObject. If more than five observations are used in the lme fit, a vector with the minimum, first quartile, median, third quartile, and maximum of the innermost grouping level residuals distribution; else the innermost grouping level residuals.
如每lmeObject。如果超过五个观测值用来在lme拟合，与至少一个矢量，第一四分位数，中位数，第三四分位，和最大的最内层的分组级别残差分布;否则的最内的分组级别残差。
参数：AIC
Akaike Information Criterion for the model fitted in snp.long.
赤池信息准则的模型安装在snp.long。
参数：corStruct
the correlation structure specified in snp.long.
在snp.long指定的相关结构。
参数：modelStruct
as per lmeObject. An object inheriting from class lmeStruct, representing a list of mixed-effects model components, such as reStruct, corStruct, and varFunc objects.
如每lmeObject。一个继承类的对象lmeStruct，混合效应模型组件的列表，如reStruct，corStruct和varFunc对象。
（作者）----------Author(s)----------
Pamela A. McCaskie
参考文献----------References----------
参见----------See Also----------
haplo.long, lme
haplo.long，lme
实例----------Examples----------
data(SNPlong.dat)
# transforms SNPlong.dat to an object containing 3 columns[转换到一个对象，它包含3列的SNPlong.dat]
# per SNP - additive, dominant and recessive, where genotypes[每个SNP - 添加剂，显性和隐性的，其中基因型]
# defined in 'baseline' serve as the baseline genotypes[中定义的“基线”作为基线基因型]
longGeno.dat <- SNP2Geno(SNPlong.dat, baseline=c("AA", "GG", "V2V2"))
data(longPheno.dat)
mymodel <- snp.long(fixed=fev1f~SNP_1_add, random=~1|ID,
geno=longGeno.dat, pheno=longPheno.dat, form=~year|ID)
summary(mymodel)
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 02:49:32
