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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,6 @@ | ||
| Package: cardx | ||
| Title: Extra Analysis Results Data Utilities | ||
| Version: 0.1.0.9021 | ||
| Version: 0.1.0.9026 | ||
| Authors@R: c( | ||
| person("Daniel", "Sjoberg", , "[email protected]", role = c("aut", "cre")), | ||
| person("Abinaya", "Yogasekaram", , "[email protected]", role = "aut"), | ||
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|
@@ -30,6 +30,7 @@ Suggests: | |
| broom.helpers (>= 1.15.0), | ||
| car (>= 3.0-11), | ||
| effectsize (>= 0.6.0), | ||
| emmeans (>= 1.7.3), | ||
| geepack (>= 1.3.2), | ||
| ggsurvfit (>= 1.0.0), | ||
| lme4 (>= 1.1-31), | ||
|
|
||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,134 @@ | ||
| #' ARD for LS Mean Difference | ||
| #' | ||
| #' @description | ||
| #' This function calculates least-squares mean differences using the 'emmeans' | ||
| #' package using the following | ||
| #' | ||
| #' ```r | ||
| #' emmeans::emmeans(object = <regression model>, specs = ~ <primary covariate>) |> | ||
| #' emmeans::contrast(method = "pairwise") |> | ||
| #' summary(infer = TRUE, level = <confidence level>) | ||
| #' ``` | ||
| #' | ||
| #' The arguments `data`, `formula`, `method`, `method.args`, `package` are used | ||
| #' to construct the regression model via `cardx::construct_model()`. | ||
| #' | ||
| #' @param data (`data.frame`/`survey.design`)\cr | ||
| #' a data frame or survey design object | ||
| #' @inheritParams construct_model | ||
| #' @param response_type (`string`) | ||
| #' string indicating whether the model outcome is `'continuous'` | ||
| #' or `'dichotomous'`. When `'dichotomous'`, the call to `emmeans::emmeans()` is | ||
| #' supplemented with argument `regrid="response"`. | ||
| #' @param conf.level (scalar `numeric`)\cr | ||
| #' confidence level for confidence interval. Default is `0.95`. | ||
| #' @param primary_covariate (`string`)\cr | ||
| #' string indicating the primary covariate (typically the dichotomous treatment variable). | ||
| #' Default is the first covariate listed in the formula. | ||
| #' | ||
| #' @return ARD data frame | ||
| #' @export | ||
| #' | ||
| #' @examplesIf do.call(asNamespace("cardx")$is_pkg_installed, list(pkg = "emmeans", reference_pkg = "cardx")) | ||
| #' ard_emmeans_mean_difference( | ||
| #' data = mtcars, | ||
| #' formula = mpg ~ am + cyl, | ||
| #' method = "lm" | ||
| #' ) | ||
| #' | ||
| #' ard_emmeans_mean_difference( | ||
| #' data = mtcars, | ||
| #' formula = vs ~ am + mpg, | ||
| #' method = "glm", | ||
| #' method.args = list(family = binomial), | ||
| #' response_type = "dichotomous" | ||
| #' ) | ||
| ard_emmeans_mean_difference <- function(data, formula, method, | ||
| method.args = list(), | ||
| package = "base", | ||
| response_type = c("continuous", "dichotomous"), | ||
| conf.level = 0.95, | ||
| primary_covariate = | ||
| stats::terms(formula) |> | ||
| attr("term.labels") |> | ||
| getElement(1L)) { | ||
| set_cli_abort_call() | ||
|
|
||
| # check package installation ------------------------------------------------- | ||
| check_pkg_installed(c("emmeans", package), reference_pkg = "cardx") | ||
| check_not_missing(data) | ||
| check_not_missing(formula) | ||
| check_not_missing(method) | ||
| check_class(data, c("data.frame", "survey.design")) | ||
| check_class(formula, cls = "formula") | ||
| check_string(package) | ||
| check_string(primary_covariate) | ||
| check_scalar(conf.level) | ||
| check_range(conf.level, range = c(0, 1)) | ||
| response_type <- arg_match(response_type, error_call = get_cli_abort_call()) | ||
|
|
||
| # construct primary model ---------------------------------------------------- | ||
| mod <- | ||
| construct_model( | ||
| x = data, formula = formula, method = method, | ||
| method.args = {{ method.args }}, | ||
| package = package, env = caller_env() | ||
| ) | ||
|
|
||
| # emmeans -------------------------------------------------------------------- | ||
| emmeans_args <- list(object = mod, specs = reformulate2(primary_covariate)) | ||
| if (response_type %in% "dichotomous") emmeans_args <- c(emmeans_args, list(regrid = "response")) | ||
| emmeans <- | ||
| withr::with_namespace( | ||
| package = "emmeans", | ||
| code = do.call("emmeans", args = emmeans_args) | ||
| ) | ||
|
|
||
| df_results <- | ||
| emmeans |> | ||
| emmeans::contrast(method = "pairwise") |> | ||
| summary(infer = TRUE, level = conf.level) | ||
|
|
||
| # convert results to ARD format ---------------------------------------------- | ||
| df_results |> | ||
| dplyr::as_tibble() |> | ||
| dplyr::rename( | ||
| conf.low = any_of("asymp.LCL"), | ||
| conf.high = any_of("asymp.UCL"), | ||
| conf.low = any_of("lower.CL"), | ||
| conf.high = any_of("upper.CL") | ||
| ) %>% | ||
| dplyr::select( | ||
| variable_level = "contrast", | ||
| "estimate", | ||
| std.error = "SE", "df", | ||
| "conf.low", "conf.high", "p.value" | ||
| ) %>% | ||
| dplyr::mutate( | ||
| conf.level = .env$conf.level, | ||
| method = | ||
| ifelse( | ||
| length(attr(stats::terms(formula), "term.labels") |> discard(~ startsWith(., "1 |"))) == 1L, | ||
| "Least-squares mean difference", | ||
| "Least-squares adjusted mean difference" | ||
| ), | ||
| across(everything(), as.list), | ||
| variable = "contrast", | ||
| group1 = .env$primary_covariate | ||
| ) |> | ||
| tidyr::pivot_longer( | ||
| cols = -c("group1", "variable", "variable_level"), | ||
| names_to = "stat_name", | ||
| values_to = "stat" | ||
| ) |> | ||
| dplyr::left_join(.df_ttest_stat_labels(primary_covariate), by = "stat_name") |> | ||
| dplyr::mutate( | ||
| context = "emmeans_mean_difference", | ||
| stat_label = dplyr::coalesce(.data$stat_label, .data$stat_name), | ||
| warning = list(NULL), | ||
| error = list(NULL), | ||
| fmt_fn = map(.data$stat, \(.x) if (is.numeric(.x)) 1L else NULL) # styler: off | ||
| ) |> | ||
| cards::tidy_ard_column_order() %>% | ||
| {structure(., class = c("card", class(.)))} # styler: off | ||
| } |
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