描述性表-如何创建同时包含数字变量和分类变量的表

Question

I can't find a really intuitive way of doing the most basic thing; creating a summary table with my base variables. The best method I've found is currently using tapply:

seed(200)
my_stats <- function(x){
    if (is.factor(x)){
        a <- table(x, useNA="no")
        b <- round(a*100/sum(a),2)

        # If binary
        if (length(a) == 2){
            ret <- paste(a[1], " (", b[1], " %)", sep="")
        }
        return(ret)
    }else{
        ret <- mean(x, na.rm=T)
        if (ret < 1){
            ret <- round(ret, 2)
        }else{
            ret <- round(ret)
        }
        return(ret)
    }
}

library(rms)
groups <- factor(sample(c("Group A","Group B"), size=51, replace=T))
a <- 3:53 
b <- rnorm(51)
c <- factor(sample(c("male","female"), size=51, replace=T))

res <- rbind(a=tapply(a, groups, my_stats),
      b=tapply(b, groups, my_stats),
      c=tapply(c, groups, my_stats))
latex(latexTranslate(res))

The res contains:

> res
  Group A     Group B       
a "28"        "28"          
b "-0.08"     "-0.21"       
c "14 (56 %)" "14 (53.85 %)"

Now this works but it seems very complex and not the most elegant solution. I've tried to search for how to create descriptive tables but the all focus on the table(), prop.table(), summary() for just single variable or variables of the same kind.

My question: Is there a package/function that allows an easy way of creating a good-looking latex table? If so, please give a hint of how to get the above result.

Thanks!

Answer 1

If you would like to create a summary table with both catergorical and continuous variables you should look into the package 'tableone'.

Here is an example of what it can do https://rpubs.com/kaz_yos/tableone-vignette . And here is the pdf documentation: https://cran.r-project.org/web/packages/tableone/tableone.pdf

I hope this helps.

• Mike

Answer 2

What you're asking is a tad open ended, since there's the distinct possibility that you will disagree with me on what constitutes a "good-looking LaTeX table".

For instance, I would probably prefer to organize this by row, rather than by column:

require(plyr)
require(xtable)
dat <- data.frame(a,b,c,groups)
xtable(ddply(dat,.(groups),summarise,a = my_stats(a),
                                     b = my_stats(b),
                                     c = my_stats(c)))


\begin{table}[ht]
\begin{center}
\begin{tabular}{rlrrl}
  \hline
 & groups & a & b & c \\ 
  \hline
1 & Group A & 28.00 & 0.14 & 13 (52 \%) \\ 
  2 & Group B & 28.00 & -0.00 & 13 (50 \%) \\ 
   \hline
\end{tabular}
\end{center}
\end{table}

And of course, much of that is customizable if you look at ?xtable and also ?print.xtable .

Answer 3

If you rewrite your function so that it always returns a string (it sometimes returns a string, sometimes a number, sometimes NULL), you can call ddply on the data.frame, without having to specify all the columns.

f <- function(u) {
  res <- "?" 
  if(is.factor(u) || is.character(u)) {
    u <- table(u, useNA = "no")
    if (length(u) == 0 || sum(u) == 0) { res <- "NA" }
    else { res <- sprintf( "%0.0f%%", 100 * u[1] / sum(u) ) }
  } else {
    u <- mean(u, na.rm=TRUE)
    if(is.na(u)) { res <- "NA" }
    else { res <- sprintf( ifelse( abs(u) < 1, "%0.2f", "%0.0f" ), u ) }
  }
  return( res )
}
# Same function, for data.frames
g <- function(d) do.call( data.frame, lapply(d, f) )

library(plyr)
ddply(data.frame(a,b,c), .(groups), g)

Since you want LaTeX tables, you may also want to try the following, which does not group the data, but adds sparkline histograms for the numeric variables.

library(Hmisc)
latex(describe(d), file="")

Answer 4

查看tables包，这可能会使此过程更简单。