从 mtable/outreg 类型表中省略一些系数 [英] omit some coefficients from mtable/outreg-type table

问题描述

我一直在运行一堆不同的回归模型，现在想将它们的估计值放入 LaTeX 表中.为了使不同的规范具有可比性，我想使用 rockchalk 包中的 outreg 或 memisc<中的 mtable 的那种表/code>produce，即不同的模型显示在列中，来自这些模型的参数估计显示在适当的行中.这就是我所拥有的:

I've been running a bunch of different regression models and would now like to get their estimates into a LaTeX table. To make the different specifications comparable I would like to use the kind of table that outreg from the rockchalk package or mtable from memisc produce, i.e. one in which the different models are shown in columns and parameter estimates from those models are shown in the appropriate rows. This is what I've got:

df <- data.frame(x=rnorm(20),
                 z=rnorm(20),
                 group=gl(5,4,20,labels=paste('group',rep(1:5))))
df$y = 5 + 2*df$x + 5*df$z + rep(c(3.2,5,6.2,8.2,5),each=4) + rnorm(20)

model1 <- lm(y ~ x + z + factor(group),data=df)
model2 <- lm(y ~ x + factor(group),data=df)
model3 <- lm(y ~ x + z,data=df)

library(memisc)

reg.table <- mtable("Model 1"=model1,"Model 2"=model2,"Model 3"=model3,
                summary.stats=c("sigma","R-squared","F","p","N"))

toLatex(reg.table)

这很好用，但我有一个大约有 200 个级别的因子和相应的大量系数.我想做的是要么从表中省略与该因子相关的系数，要么(为了加分！)以简单的是"或否"显示该因子在模型中使用.所以，我理想的输出是这样的:

This works well enough, but I've got a factor with roughly 200 levels and a correspondingly large number of coefficients. What I'd like to do is to either omit the coefficients associated with this factor from the table or (for bonus points!) to show that the factor was used in the model with a simple 'yes' or 'no'. So, my ideal output would be this:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%    %
%
% Calls:
% Model 1:  lm(formula = y ~ x + z + factor(group), data = df) 
% Model 2:  lm(formula = y ~ x + factor(group), data = df) 
% Model 3:  lm(formula = y ~ x + z, data = df) 
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%    %
egin{tabular}{lcD{.}{.}{7}cD{.}{.}{7}cD{.}{.}{7}}
	oprule
&&multicolumn{1}{c}{Model 1} && multicolumn{1}{c}{Model 2} && multicolumn{1}{c}{Model 3}\
midrule
(Intercept)                    &  &  8.315^{***} &&    4.235     && 10.338^{***}\
                               &  &  (0.537)     &&   (3.276)    &&  (0.468)    \
x                              &  &  1.976^{***} &&    2.398     &&  1.858^{***}\
                               &  &  (0.238)     &&   (1.530)    &&  (0.443)    \
z                              &  &  5.389^{***} &&              &&  5.359^{***}\
                               &  &  (0.226)     &&              &&  (0.463)    \
group                          &  &   yes        &&    yes       &&     no      \
midrule
sigma                          &  &     0.929    &&     5.981    &&     2.092   \
R-squared                      &  &     0.984    &&     0.265    &&     0.891   \
F                              &  &   129.485    &&     1.009    &&    69.306   \
p                              &  &     0.000    &&     0.448    &&     0.000   \
N                              &  &    20        &&    20        &&    20       \
ottomrule
end{tabular}

这可能吗?

推荐答案

只选择前三个系数非常简单:

Just selecting the first three coefficients is pretty simple:

reg.table$coefficients <- reg.table$coefficients[,,1:3,,drop=FALSE]
toLatex(reg.table)

<小时>

奖励"问题(即添加手工构建的第 4 行描述组")需要更多工作:

---

The "bonus" question (i.e. adding a hand-built 4th row describing "group") requires a bit more work:

## Select the first three coeffients + one to be modified
reg.table$coefficients <- reg.table$coefficients[,,1:4,,drop=FALSE]

## Make a copy of all the coefficients, and in the copy, modify the 4th
j <- reg.table$coefficients
j[,,4,] <- c("yes", "", "yes", "", "no", "")
dimnames(j)[[3]][4] <- "group"

## Put the modified coefficients back into `reg.table`
reg.table$coefficients <- j

瞧瞧

toLatex(reg.table)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Calls:
% Model 1:  lm(formula = y ~ x + z + factor(group), data = df) 
% Model 2:  lm(formula = y ~ x + factor(group), data = df) 
% Model 3:  lm(formula = y ~ x + z, data = df) 
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
egin{tabular}{lcD{.}{.}{7}cD{.}{.}{7}cD{.}{.}{7}}
	oprule
&&multicolumn{1}{c}{Model 1} && multicolumn{1}{c}{Model 2} && multicolumn{1}{c}{Model 3}\
midrule
(Intercept) &  &   8.830^{***} &&   9.846^{**}  && 10.342^{***} \
            &  &   (0.626)     &&    (3.272)    &&   (0.442)    \
x           &  &   2.047^{***} &&     1.765     &&  1.937^{***} \
            &  &   (0.244)     &&    (1.276)    &&   (0.319)    \
z           &  &   5.138^{***} &&               &&  4.847^{***} \
            &  &   (0.267)     &&               &&   (0.372)    \
group       &  &  yes          &&   yes         &&   no         \
            &  &               &&               &&              \
midrule
sigma       &  &     1.204     &&     6.310     &&      1.812   \
R-squared   &  &     0.975     &&     0.270     &&      0.927   \
F           &  &    85.576     &&     1.033     &&    107.717   \
p           &  &     0.000     &&     0.436     &&      0.000   \
N           &  &    20         &&    20         &&     20       \
ottomrule
end{tabular}

<小时>

这是我更喜欢的版本.它解决了 OP 在下面的第 1 条评论，并使用 abind() (如数组的 rbind() )将组信息添加到数组中，我发现它更干净:

Here's a version I like even better. It addresses the OP's 1st comment below, and uses abind() (like rbind() for arrays) to add the group info to the array, which I find to be cleaner:

library(abind)

j <- reg.table$coefficients

groupFac <- array(c("yes", "", "yes", "", "no", ""), dim=c(2,1,3))
nonGroupFacs <- which(!grepl("group", dimnames(j)[[3]]))
j <- j[,,nonGroupFacs,,drop=FALSE]
j <- abind(j, groupFac, along=3)
dimnames(j)[[3]][length(nonGroupFacs)+1] <- "group"

reg.table$coefficients <- j

toLatex(reg.table)

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