The analyze function estimate_odds_ratio() creates a layout element to compare bivariate responses between
two groups by estimating an odds ratio and its confidence interval.
The primary analysis variable specified by vars is the group variable. Additional variables can be included in the
analysis via the variables argument, which accepts arm, an arm variable, and strata, a stratification variable.
If more than two arm levels are present, they can be combined into two groups using the groups_list argument.
Usage
estimate_odds_ratio(
lyt,
vars,
variables = list(arm = NULL, strata = NULL),
conf_level = 0.95,
groups_list = NULL,
method = "exact",
na_str = default_na_str(),
nested = TRUE,
...,
table_names = vars,
show_labels = "hidden",
var_labels = vars,
.stats = "or_ci",
.stat_names = NULL,
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)
s_odds_ratio(
df,
.var,
.ref_group,
.in_ref_col,
.df_row,
variables = list(arm = NULL, strata = NULL),
conf_level = 0.95,
groups_list = NULL,
method = "exact",
...
)
a_odds_ratio(
df,
...,
.stats = NULL,
.stat_names = NULL,
.formats = NULL,
.labels = NULL,
.indent_mods = NULL
)Arguments
- lyt
(
PreDataTableLayouts)
layout that analyses will be added to.- vars
(
character)
variable names for the primary analysis variable to be iterated over.- variables
(named
listofstring)
list of additional analysis variables.- conf_level
(
proportion)
confidence level of the interval.- groups_list
(named
listofcharacter)
specifies the new group levels via the names and the levels that belong to it in the character vectors that are elements of the list.- method
(
string)
whether to use the correct ("exact") calculation in the conditional likelihood or one of the approximations. Seesurvival::clogit()for details.- na_str
(
string)
string used to replace allNAor empty values in the output.- nested
(
flag)
whether this layout instruction should be applied within the existing layout structure _if possible (TRUE, the default) or as a new top-level element (FALSE). Ignored if it would nest a split. underneath analyses, which is not allowed.- ...
additional arguments to
rtables::split_cols_by()in order. For instance, to control formats (format), add a joint column for all groups (incl_all).- table_names
(
character)
this can be customized in the case that the samevarsare analyzed multiple times, to avoid warnings fromrtables.- show_labels
(
string)
label visibility: one of "default", "visible" and "hidden".- var_labels
(
character)
variable labels.- .stats
-
(
character)
statistics to select for the table.Options are:
'or_ci', 'n_tot' - .stat_names
(
character)
names of the statistics that are passed directly to name single statistics (.stats). This option is visible when producingrtables::as_result_df()withmake_ard = TRUE.- .formats
(named
characterorlist)
formats for the statistics. See Details inanalyze_varsfor more information on the"auto"setting.- .labels
(named
character)
labels for the statistics (without indent).- .indent_mods
(named
integer)
indent modifiers for the labels. Defaults to 0, which corresponds to the unmodified default behavior. Can be negative.- df
(
data.frame)
data set containing all analysis variables.- .var
(
string)
single variable name that is passed byrtableswhen requested by a statistics function.- .ref_group
(
data.frameorvector)
the data corresponding to the reference group.- .in_ref_col
(
flag)TRUEwhen working with the reference level,FALSEotherwise.- .df_row
(
data.frame)
data frame across all of the columns for the given row split.
Value
estimate_odds_ratio()returns a layout object suitable for passing to further layouting functions, or tortables::build_table(). Adding this function to anrtablelayout will add formatted rows containing the statistics froms_odds_ratio()to the table layout.
s_odds_ratio()returns a named list with the statisticsor_ci(containingest,lcl, anducl) andn_tot.
a_odds_ratio()returns the corresponding list with formattedrtables::CellValue().
Functions
estimate_odds_ratio(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper forrtables::analyze().s_odds_ratio(): Statistics function which estimates the odds ratio between a treatment and a control. Avariableslist witharmandstratavariable names must be passed if a stratified analysis is required.a_odds_ratio(): Formatted analysis function which is used asafuninestimate_odds_ratio().
Note
This function uses logistic regression for unstratified analyses, and conditional logistic regression for stratified analyses. The Wald confidence interval is calculated with the specified confidence level.
For stratified analyses, there is currently no implementation for conditional likelihood confidence intervals, therefore the likelihood confidence interval is not available as an option.
When
varscontains only responders or non-responders no odds ratio estimation is possible so the returned values will beNA.
See also
Relevant helper function h_odds_ratio().
Examples
set.seed(12)
dta <- data.frame(
rsp = sample(c(TRUE, FALSE), 100, TRUE),
grp = factor(rep(c("A", "B"), each = 50), levels = c("A", "B")),
strata = factor(sample(c("C", "D"), 100, TRUE))
)
l <- basic_table() %>%
split_cols_by(var = "grp", ref_group = "B") %>%
estimate_odds_ratio(vars = "rsp")
build_table(l, df = dta)
#> A B
#> ————————————————————————————————————————————
#> Odds Ratio (95% CI) 0.85 (0.38 - 1.88)
# Unstratified analysis.
s_odds_ratio(
df = subset(dta, grp == "A"),
.var = "rsp",
.ref_group = subset(dta, grp == "B"),
.in_ref_col = FALSE,
.df_row = dta
)
#> $or_ci
#> est lcl ucl
#> 0.8484848 0.3831831 1.8788053
#> attr(,"label")
#> [1] "Odds Ratio (95% CI)"
#>
#> $n_tot
#> n_tot
#> 100
#> attr(,"label")
#> [1] "Total n"
#>
# Stratified analysis.
s_odds_ratio(
df = subset(dta, grp == "A"),
.var = "rsp",
.ref_group = subset(dta, grp == "B"),
.in_ref_col = FALSE,
.df_row = dta,
variables = list(arm = "grp", strata = "strata")
)
#> $or_ci
#> est lcl ucl
#> 0.7689750 0.3424155 1.7269154
#> attr(,"label")
#> [1] "Odds Ratio (95% CI)"
#>
#> $n_tot
#> n_tot
#> 100
#> attr(,"label")
#> [1] "Total n"
#>
a_odds_ratio(
df = subset(dta, grp == "A"),
.var = "rsp",
.ref_group = subset(dta, grp == "B"),
.in_ref_col = FALSE,
.df_row = dta
)
#> RowsVerticalSection (in_rows) object print method:
#> ----------------------------
#> row_name formatted_cell indent_mod row_label
#> 1 Odds Ratio (95% CI) 0.85 (0.38 - 1.88) 0 Odds Ratio (95% CI)
#> 2 Total n 100 0 Total n
