我目前正在对人口数据进行一些数据分析,因此报告参数系数表中的标准误差实际上并没有统计意义。我做了一些搜索,无法找到任何方法来自定义xtable输出以删除它。谁能指出我正确的方向?
非常感谢,我没有轻易发布;如果这是明显的事情,我为浪费时间而道歉!
答案 0 :(得分:5)
所以在我(其他)整个冗长的答案之后...这也有效:
xtable(summary(model1)$coefficients[,c(1,3,4)])
或者更一般地说:
sm <- summary(SomeModel)
SE.indx <- which(colnames(sm$coefficients) == "Std. Error") # find which column is Std. Error (usually 2nd)
sm$coefficients <- sm$coefficients[, -SE.indx] # Remove it
xtable(sm$coefficients) # call xtable on just the coefficients table
% latex table generated in R 2.15.1 by xtable 1.7-0 package
% Sun Dec 9 00:01:46 2012
\begin{table}[ht]
\begin{center}
\begin{tabular}{rrrr}
\hline
& Estimate & t value & Pr($>$$|$t$|$) \\
\hline
(Intercept) & 29.80 & 30.70 & 0.00 \\
crim & -0.31 & -6.91 & 0.00 \\
age & -0.09 & -6.50 & 0.00 \\
\hline
\end{tabular}
\end{center}
\end{table}
答案 1 :(得分:2)
使用help(lm)中的第一个示例:
xtable(as.matrix(coef(lm.D9)))
% latex table generated in R 2.15.2 by xtable 1.7-0 package
% Sat Dec 8 19:53:09 2012
\begin{table}[ht]
\begin{center}
\begin{tabular}{rr}
\hline
& x \\
\hline
(Intercept) & 5.03 \\
groupTrt & -0.37 \\
\hline
\end{tabular}
\end{center}
\end{table}
如果这是对人口的描述而不仅仅是样本,我同意不使用标准错误。但是,通过这种推理,您不希望留下p值或t统计量。这就是我只包括系数的原因。仅从摘要系数矩阵中删除标准错误列:
xtable( coef(summary(lm.D9))[,-2] )
% latex table generated in R 2.15.2 by xtable 1.7-0 package
% Sat Dec 8 21:02:17 2012
\begin{table}[ht]
\begin{center}
\begin{tabular}{rrrr}
\hline
& Estimate & t value & Pr($>$$|$t$|$) \\
\hline
(Intercept) & 5.03 & 22.85 & 0.00 \\
groupTrt & -0.37 & -1.19 & 0.25 \\
\hline
\end{tabular}
\end{center}
\end{table}
答案 2 :(得分:0)
查看str(summary(Model1))
,我们发现$coefficients
具有我们要删除的Std. Error
值。
lesserSummary <- function(x) {
## returns same as summary(x), but with "Std. Error" remove from coefficients.
## and class of object is "modifiedSummary"
# grab the summary
sm <- summary(x)
# find which column is std error
SE.indx <- which(colnames(sm$coefficients) == "Std. Error")
# remove it
sm$coefficients <- sm$coefficients[, -SE.indx]
# give it some class
class(sm) <- "modifiedSummary"
# return it
sm
}
xtable.modifiedSummary <-
function (x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, ...) {
# x is a modifiedSummary object
# This function is a modification of xtable:::xtable.summary.lm
# Key Difference is simply the number of columns that x$coef is expected to have
# (Here 3. Originally 4)
x <- data.frame(x$coef, check.names = FALSE)
class(x) <- c("xtable", "data.frame")
caption(x) <- caption
label(x) <- label
align(x) <- switch(1 + is.null(align), align, c("r", "r", "r", "r"))
digits(x) <- switch(1 + is.null(digits), digits, c(0, 4, 2, 4))
display(x) <- switch(1 + is.null(display), display, c("s", "f", "f", "f"))
return(x)
}
xtable_mod <- function(x) {
# Wrapper function to xtable.modified summary, calling first lesserSummary on x
xtable(lesserSummary(x))
}
xtable_mod(model1)
% latex table generated in R 2.15.1 by xtable 1.7-0 package
% Sat Dec 8 23:44:54 2012
\begin{table}[ht]
\begin{center}
\begin{tabular}{rrrr}
\hline
& Estimate & t value & Pr($>$$|$t$|$) \\
\hline
(Intercept) & 29.8007 & 30.70 & 0.0000 \\
crim & -0.3118 & -6.91 & 0.0000 \\
age & -0.0896 & -6.50 & 0.0000 \\
\hline
\end{tabular}
\end{center}
\end{table}
您可以修改对xtable的调用,但首先需要跟进它: 首先看一下xtable的来源:
xtable
# function (x, caption = NULL, label = NULL, align = NULL, digits = NULL,
# display = NULL, ...)
# {
# UseMethod("xtable")
# }
# <environment: namespace:xtable>
我们看到它只是打电话给UseMethod()
。那么让我们看看哪些方法可用:
methods(xtable)
# [1] xtable.anova* xtable.aov* xtable.aovlist*
# [4] xtable.coxph* xtable.data.frame* xtable.glm*
# [7] xtable.lm* xtable.matrix* xtable.prcomp*
# [10] xtable.summary.aov* xtable.summary.aovlist* xtable.summary.glm*
# [13] xtable.summary.lm* xtable.summary.prcomp* xtable.table*
# [16] xtable.ts* xtable.zoo*
有几个。请注意,带有星号*
的那些不可见。
调用的方法由我们调用的对象的类xtable
决定。
假设我们的输出是Model1
我们看一下它的类:'
class(Model1)
# [1] "lm"
因此,我们要查看的来源是xtable.lm
。
xtable.lm
# Error: object 'xtable.lm' not found
错误?没错,它是不可见的。所以我们使用包含三重冒号的包名称。 注意:请务必阅读帮助文件中的通知?“:::”
xtable:::xtable.lm
# function (x, caption = NULL, label = NULL, align = NULL, digits = NULL,
# display = NULL, ...)
# {
# return(xtable.summary.lm(summary(x), caption = caption, label = label,
# align = align, digits = digits, display = display))
# }
# <environment: namespace:xtable>
我们注意到xtable.lm
调用xtable.summary.lm
并将第一个参数作为summary(x)
传递,其中x是我们的模型。
因此,我们将我们带到两个地方进行调查:summary
和xtable.summary.lm