Description Usage Arguments Details Value Note Author(s) References See Also Examples
This function creates an I-by-J frequency table and summarizes the results in a clean table for a statistical report.
1 2 3 4 5 6 7 8 9 10 | tabfreq(x, y, latex = FALSE, xlevels = NULL, yname = NULL, ylevels = NULL,
quantiles = NULL, quantile.vals = FALSE, cell = "n", parenth = NULL,
text.label = NULL, parenth.sep = "-", test = "chi", decimals = NULL,
p.include = TRUE, p.decimals = c(2, 3), p.cuts = 0.01,
p.lowerbound = 0.001, p.leading0 = TRUE, p.avoid1 = FALSE,
overall.column = TRUE, n.column = FALSE, n.headings = TRUE,
compress = FALSE, compress.val = NULL, bold.colnames = TRUE,
bold.varnames = FALSE, bold.varlevels = FALSE,
variable.colname = "Variable", print.html = FALSE,
html.filename = "table1.html")
|
x |
Vector of values indicating group membership for columns of IxJ table. |
y |
Vector of values indicating group membership for rows of IxJ table. |
latex |
If |
xlevels |
Optional character vector to label the levels of |
yname |
Optional label for the |
ylevels |
Optional character vector to label the levels of |
quantiles |
If specified, function compares distribution of the |
quantile.vals |
If |
cell |
Controls what value is placed in each cell of the table. Possible choices are
|
parenth |
Controls what values (if any) are placed in parentheses after the values in each
cell. By default, if |
text.label |
Optional text to put after the |
parenth.sep |
Optional character specifying the separator between lower and upper bound of
confidence interval (when requested). Usually either |
test |
Controls test for association between |
decimals |
Number of decimal places for values in table (no decimals are used for counts). If unspecified, function uses 1 decimal for percentages and 3 decimals for proportions. |
p.include |
If |
p.decimals |
Number of decimal places for p-values. If a vector is provided rather than a
single value, number of decimal places will depend on what range the p-value l
ies in. See |
p.cuts |
Cut-point(s) to control number of decimal places used for p-values. For example,
by default |
p.lowerbound |
Controls cut-point at which p-values are no longer printed as their value, but
rather <lowerbound. For example, by default |
p.leading0 |
If |
p.avoid1 |
If |
overall.column |
If |
n.column |
If |
n.headings |
If |
compress |
If |
compress.val |
When |
bold.colnames |
If |
bold.varnames |
If |
bold.varlevels |
If |
variable.colname |
Character string with desired heading for first column of table, which shows the
|
print.html |
If |
html.filename |
Character string indicating the name of the .html file that gets printed if
|
NA
A character matrix with the requested frequency table. If latex = TRUE
,
the character matrix will be formatted for inserting into a
Markdown/Sweave/knitr report using xtable
[1].
If you wish to paste your tables into Word, you can use either of these approaches:
1. Use the write.cb
function in the Kmisc
package
[2]. If your table is stored in a character matrix named table1
, use
write.cb(table1)
to copy the table to your clipboard. Paste the result
into Word, then highlight the text and go to Insert - Table - Convert Text
to Table... OK
.
2. Set print.html = TRUE
. This will result in a .html file writing to
your current working directory. When you open this file, you will see a nice
looking table that you can copy and paste into Word. You can control the name of
this file with html.filename
.
If you wish to use LaTeX, R Markdown, knitr, Sweave, etc., set
latex = TRUE
and then use xtable
[1]. You may have to set
sanitize.text.function = identity
when calling
print.xtable
.
If you have suggestions for additional options or features, or if you would like some help using any function in tab, please e-mail me at vandomed@gmail.com. Thanks!
Dane R. Van Domelen
1. Dahl DB (2013). xtable: Export tables to LaTeX or HTML. R package version 1.7-1, https://cran.r-project.org/package=xtable.
2. Kevin Ushey (2013). Kmisc: Kevin Miscellaneous. R package version 0.5.0. https://CRAN.R-project.org/package=Kmisc.
Acknowledgment: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0940903.
tabmeans
tabmedians
tabmulti
tabglm
tabcox
tabgee
tabfreq.svy
tabmeans.svy
tabmedians.svy
tabmulti.svy
tabglm.svy
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | # Load in sample dataset d and drop rows with missing values
data(d)
d <- d[complete.cases(d), ]
# Compare sex distribution by group, with group as column variable
freqtable1 <- tabfreq(x = d$Group, y = d$Sex)
# Same comparison, but compress table to show Female row only, show percent (SE)
# rather than n (percent), and suppress (n = ) from column headings
freqtable2 <- tabfreq(x = d$Group, y = d$Sex, compress = TRUE,
compress.val = "Female", cell = "col.percent",
parenth = "se", n.headings = FALSE)
# Compare sex distribution by race, suppressing (n = ) from column headings and
# showing percent (95% CI) rather than n (percent)
freqtable3 <- tabfreq(x = d$Race, y = d$Sex, n.headings = FALSE,
cell = "col.percent")
# Use rbind to create single table comparing sex and race in control vs.
# treatment group
freqtable4 <- rbind(tabfreq(x = d$Group, y = d$Sex),
tabfreq(x = d$Group, y = d$Race))
# A (usually) faster way to make the above table is to call the the tabmulti
# function
freqtable5 <- tabmulti(dataset = d, xvarname = "Group",
yvarnames = c("Sex", "Race"))
# freqtable4 and freqtable5 are equivalent
all(freqtable4 == freqtable5)
|
Pearson's chi-square test was used to test whether the distribution of Sex differed across groups.
Pearson's chi-square test was used to test whether the distribution of Sex differed across groups.
Pearson's chi-square test was used to test whether the distribution of Sex differed across groups.
Pearson's chi-square test was used to test whether the distribution of Sex differed across groups.
Pearson's chi-square test was used to test whether the distribution of Race differed across groups.
Pearson's chi-square test was used to test whether the distribution of Sex differed across groups.
Pearson's chi-square test was used to test whether the distribution of Race differed across groups.
[1] TRUE
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