Keith Wong wrote:
> Dear all,
>
> The incredibly useful Hmisc package provides a method to generate
> summary tables that can be typeset in latex. The Alzola and Harrell book
>  "An introduction to S and the Hmisc and Design libraries" provides an
> example that generates mean and quartiles for continuous variables, and
> numbers and percentages for count variables: summary() with method =
> 'reverse'.
>
> I wonder if there is a way to change it so the mean and standard
> deviation are reported instead for continuous variables.
>
> I illustrate my question below using an example from the book.
>
> Thank you.
>
> Keith

Newer versions of Hmisc have an option to add mean and SD for
method='reverse'. Quartiles are always there.

Frank

>
>
> > ####
> > library(Hmisc)
> >
> > set.seed(173)
> > sex = factor(sample(c("m", "f"), 500, rep = T))
> > age = rnorm(500, 50, 5)
> > treatment = factor(sample(c("Drug", "Placebo"), 500, rep = T))
> > summary(sex ~ treatment, fun = table)
> sex   N=500
>
> +---------+-------+---+---+---+
> |      |     |N |f |m |
> +---------+-------+---+---+---+
> |treatment|Drug  |263|140|123|
> |      |Placebo|237|133|104|
> +---------+-------+---+---+---+
> |Overall |     |500|273|227|
> +---------+-------+---+---+---+
> >
> >
> >
> > (x = summary(treatment ~ age + sex, method = "reverse"))
> > # generates quartiles for continuous variables
>
>
> Descriptive Statistics by treatment
>
> +-------+--------------+--------------+
> |     |Drug       |Placebo     |
> |     |(N=263)     |(N=237)     |
> +-------+--------------+--------------+
> |age   |46.5/49.9/53.2|46.7/50.0/53.4|
> +-------+--------------+--------------+
> |sex : m|  47% (123) |  44% (104) |
> +-------+--------------+--------------+
> >
> >
> > # latex(x) generates a very nicely formatted table
> > # but I'd like "mean (standard deviation)" instead of quartiles.
>
>
>
> > # this function from
> http://tolstoy.newcastle.edu.au/R/e2/help/06/11/4713.html
> > g <- function(y) {
> +  s <- apply(y, 2,
> +         function(z) {
> +           z <- z[!is.na(z)]
> +           n <- length(z)
> +           if(n==0) c(NA,NA,NA,0) else
> +           if(n==1) c(z, NA,NA,1) else {
> +            m <- mean(z)
> +            s <- sd(z)
> +            c(N=n, Mean=m, SD=s)
> +           }
> +         })
> +  w <- as.vector(s)
> +  names(w) <- as.vector(outer(rownames(s), colnames(s), paste, sep=''))
> +  w
> + }
>
> >
> > summary(treatment ~ age + sex, method = "reverse", fun = g)
> > # does not work, 'fun' or 'FUN" argument is ignored.
>
>
> Descriptive Statistics by treatment
>
> +-------+--------------+--------------+
> |     |Drug       |Placebo     |
> |     |(N=263)     |(N=237)     |
> +-------+--------------+--------------+
> |age   |46.5/49.9/53.2|46.7/50.0/53.4|
> +-------+--------------+--------------+
> |sex : m|  47% (123) |  44% (104) |
> +-------+--------------+--------------+
> >
> >
> > (x1 = summarize(cbind(age), llist(treatment), FUN = g,
> stat.name=c("n", "mean", "sd")))
>   treatment  n mean  sd
> 1    Drug 263 49.9 4.94
> 2  Placebo 237 50.1 4.97
> >
> > # this works but table is rotated, and it count data has to be
> > # treated separately.
>
>
>


--
Frank E Harrell Jr  Professor and Chair       School of Medicine
              Department of Biostatistics  Vanderbilt University

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