Cross-tabulation for a pair of categorical variables with either row, column, or total proportions, as well as marginal sums. Works with numeric, character, as well as factor variables.
ctable(
x,
y,
prop = st_options("ctable.prop"),
useNA = "ifany",
totals = st_options("ctable.totals"),
style = st_options("style"),
round.digits = st_options("ctable.round.digits"),
justify = "right",
plain.ascii = st_options("plain.ascii"),
headings = st_options("headings"),
display.labels = st_options("display.labels"),
split.tables = Inf,
na.val = st_options("na.val"),
rev = "none",
dnn = c(substitute(x), substitute(y)),
chisq = FALSE,
OR = FALSE,
RR = FALSE,
weights = NA,
rescale.weights = FALSE,
...
)First categorical variable - values will appear as row names.
Second categorical variable - values will appear as column names.
Character. Indicates which proportions to show: “r”
(rows, default), “c” (columns), “t” (total), or “n”
(none). Default value can be changed using st_options,
option ctable.prop.
Character. One of “ifany” (default), “no”, or
“always”. This argument is passed on ‘as is’ to
table, or adapted for xtabs when
weights are used.
Logical. Show row and column totals. Defaults to
TRUE but can be set globally with st_options, option
ctable.totals.
Character. Style to be used by pander. One
of “simple” (default), “grid”, “rmarkdown”, or
“jira”. Can be set globally with st_options.
Numeric. Number of significant digits to keep. Defaults
to 1. To change this default value, use st_options,
option ctable.round.digits.
Character. Horizontal alignment; one of “l” (left), “c” (center), or “r” (right, default).
Logical. Used by pander; when
TRUE, no markup characters are generated (useful when printing
to console). Defaults to TRUE unless style = 'rmarkdown',
in which case it is set to FALSE automatically. To change the
default value globally, use st_options.
Logical. Show heading section. TRUE by default; can be
set globally with st_options.
Logical. Display data frame label in the heading
section. TRUE by default, can be changed globally with
st_options.
Numeric. pander argument that
specifies how many characters wide a table can be. Inf by default.
Character. For factors and character vectors, consider this
value as NA. Ignored if there are actual NA values or if it matches
no value / factor level in the data. NULL by default.
Character. Dimension(s) to reverse for calculation of risk/odds ratios. One of “rows” / “r”, “columns” / “c”, “both” / “b”, or “none” / “n” (default). See details.
Character vector. Variable names to be used in output table. In most cases, setting this parameter is not required as the names are automatically generated.
Logical. Display chi-square statistic along with p-value.
Logical or numeric. Set to TRUE to show odds ratio with 95
confidence interval, or specify confidence level explicitly (e.g.,
.90). CI's are calculated using Wald's method of normal approximation.
Logical or numeric. Set to TRUE to show risk ratio (also
called relative risk with 95
confidence level explicitly (e.g. .90). CI's are
calculated using Wald's method of normal approximation.
Numeric. Vector of weights; must have the same length as
x.
Logical. When TRUE, a global constant is
applied so that the sum of counts equals nrow(x). FALSE by
default.
A list containing two matrices, cross_table and
proportions. The print method takes care of assembling
figures from those matrices into a single table. The returned object has
classes “summarytools” and “list”, unless
stby is used, in which case we have an
object of class “stby”.
For risk ratios and odds ratios, the expected structure of the contingency table is as follows (using “No” as reference):
Outcome
Exposure Yes No
Yes a b
No c d
The rev parameter allows for different structures; use either one of “rows”, “columns”, or “both” to indicate which dimension(s) to reverse in order to match that structure. This does not affect display.
Markdown does not fully support multi-header tables; until such support is available, the recommended way to display cross-tables in .Rmd documents is to use `method=render`. See package vignettes for examples.
data("tobacco")
ctable(tobacco$gender, tobacco$smoker)
#> Cross-Tabulation, Row Proportions
#> gender * smoker
#> Data Frame: tobacco
#>
#> -------- -------- ------------- ------------- ---------------
#> smoker Yes No Total
#> gender
#> F 147 (30.1%) 342 (69.9%) 489 (100.0%)
#> M 143 (29.2%) 346 (70.8%) 489 (100.0%)
#> <NA> 8 (36.4%) 14 (63.6%) 22 (100.0%)
#> Total 298 (29.8%) 702 (70.2%) 1000 (100.0%)
#> -------- -------- ------------- ------------- ---------------
# Use with() to simplify syntax
with(tobacco, ctable(gender, smoker))
#> Cross-Tabulation, Row Proportions
#> gender * smoker
#> Data Frame: tobacco
#>
#> -------- -------- ------------- ------------- ---------------
#> smoker Yes No Total
#> gender
#> F 147 (30.1%) 342 (69.9%) 489 (100.0%)
#> M 143 (29.2%) 346 (70.8%) 489 (100.0%)
#> <NA> 8 (36.4%) 14 (63.6%) 22 (100.0%)
#> Total 298 (29.8%) 702 (70.2%) 1000 (100.0%)
#> -------- -------- ------------- ------------- ---------------
# Show column proportions, without totals
with(tobacco, ctable(smoker, diseased, prop = "c", totals = FALSE))
#> Cross-Tabulation, Column Proportions
#> smoker * diseased
#> Data Frame: tobacco
#>
#> -------- ---------- ------------- -------------
#> diseased Yes No
#> smoker
#> Yes 125 (55.8%) 173 (22.3%)
#> No 99 (44.2%) 603 (77.7%)
#> -------- ---------- ------------- -------------
# Simple 2 x 2 table with odds ratio and risk ratio
with(tobacco, ctable(smoker, diseased, totals = FALSE, headings = FALSE,
prop = "r", OR = TRUE, RR = TRUE))
#>
#> -------- ---------- ------------- -------------
#> diseased Yes No
#> smoker
#> Yes 125 (41.9%) 173 (58.1%)
#> No 99 (14.1%) 603 (85.9%)
#> -------- ---------- ------------- -------------
#>
#> ----------------------------------
#> Odds Ratio Lo - 95% Hi - 95%
#> ------------ ---------- ----------
#> 4.40 3.22 6.02
#> ----------------------------------
#>
#> ----------------------------------
#> Risk Ratio Lo - 95% Hi - 95%
#> ------------ ---------- ----------
#> 2.97 2.37 3.73
#> ----------------------------------
# Grouped cross-tabulations
with(tobacco, stby(data = list(x = smoker, y = diseased),
INDICES = gender, FUN = ctable))
#> NA detected in grouping variable(s); consider using useNA = TRUE
#> Cross-Tabulation, Row Proportions
#> smoker * diseased
#> Data Frame: tobacco
#> Group: gender = F
#>
#> -------- ---------- ------------- ------------- --------------
#> diseased Yes No Total
#> smoker
#> Yes 62 (42.2%) 85 (57.8%) 147 (100.0%)
#> No 49 (14.3%) 293 (85.7%) 342 (100.0%)
#> Total 111 (22.7%) 378 (77.3%) 489 (100.0%)
#> -------- ---------- ------------- ------------- --------------
#>
#> Group: gender = M
#>
#> -------- ---------- ------------- ------------- --------------
#> diseased Yes No Total
#> smoker
#> Yes 63 (44.1%) 80 (55.9%) 143 (100.0%)
#> No 47 (13.6%) 299 (86.4%) 346 (100.0%)
#> Total 110 (22.5%) 379 (77.5%) 489 (100.0%)
#> -------- ---------- ------------- ------------- --------------
if (FALSE) { # \dontrun{
ct <- ctable(tobacco$gender, tobacco$smoker)
# Show html results in browser
print(ct, method = "browser")
# Save results to html file
print(ct, file = "ct_gender_smoker.html")
# Save results to text file
print(ct, file = "ct_gender_smoker.txt")
} # }