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#' A `<summarised_result>` object filled with mock data
#' @return An object of the class `<summarised_result>` with mock data.
#' @description Creates an object of the class `<summarised_result>` with mock data
#' for illustration purposes.
#'
#' @export
#'
#' @examples
#' mockSummarisedResult()
#'
#'
mockSummarisedResult <- function() {
# TO modify when PatientProfiles works with omopgenerics
# number subjects
result <- dplyr::tibble(
"cdm_name" = "mock",
"group_name" = "cohort_name",
"group_level" = c(rep("cohort1", 9), rep("cohort2", 9)),
"strata_name" = rep(c(
"overall", rep("age_group &&& sex", 4), rep("sex", 2), rep("age_group", 2)
), 2),
"strata_level" = rep(c(
"overall", "<40 &&& Male", ">=40 &&& Male", "<40 &&& Female",
">=40 &&& Female", "Male", "Female", "<40", ">=40"
), 2),
"variable_name" = "number subjects",
"variable_level" = NA_character_,
"estimate_name" = "count",
"estimate_type" = "integer",
"estimate_value" = round(10000000*stats::runif(18)) |> as.character(),
"additional_name" = "overall",
"additional_level" = "overall"
) |>
# age - mean
dplyr::union_all(
dplyr::tibble(
"cdm_name" = "mock",
"group_name" = "cohort_name",
"group_level" = c(rep("cohort1", 9), rep("cohort2", 9)),
"strata_name" = rep(c(
"overall", rep("age_group &&& sex", 4), rep("sex", 2), rep("age_group", 2)
), 2),
"strata_level" = rep(c(
"overall", "<40 &&& Male", ">=40 &&& Male", "<40 &&& Female",
">=40 &&& Female", "Male", "Female", "<40", ">=40"
), 2),
"variable_name" = "age",
"variable_level" = NA_character_,
"estimate_name" = "mean",
"estimate_type" = "numeric",
"estimate_value" = c(100*stats::runif(18)) |> as.character(),
"additional_name" = "overall",
"additional_level" = "overall"
)
)|>
# age - standard deviation
dplyr::union_all(
dplyr::tibble(
"cdm_name" = "mock",
"group_name" = "cohort_name",
"group_level" = c(rep("cohort1", 9), rep("cohort2", 9)),
"strata_name" = rep(c(
"overall", rep("age_group &&& sex", 4), rep("sex", 2), rep("age_group", 2)
), 2),
"strata_level" = rep(c(
"overall", "<40 &&& Male", ">=40 &&& Male", "<40 &&& Female",
">=40 &&& Female", "Male", "Female", "<40", ">=40"
), 2),
"variable_name" = "age",
"variable_level" = NA_character_,
"estimate_name" = "sd",
"estimate_type" = "numeric",
"estimate_value" = c(10*stats::runif(18)) |> as.character(),
"additional_name" = "overall",
"additional_level" = "overall"
)
) |>
# medication - count
dplyr::union_all(
dplyr::tibble(
"cdm_name" = "mock",
"group_name" = "cohort_name",
"group_level" = c(rep("cohort1", 9), rep("cohort2", 9)),
"strata_name" = rep(c(
"overall", rep("age_group &&& sex", 4), rep("sex", 2), rep("age_group", 2)
), 2),
"strata_level" = rep(c(
"overall", "<40 &&& Male", ">=40 &&& Male", "<40 &&& Female",
">=40 &&& Female", "Male", "Female", "<40", ">=40"
), 2),
"variable_name" = "Medications",
"variable_level" = "Amoxiciline",
"estimate_name" = "count",
"estimate_type" = "integer",
"estimate_value" = round(100000*stats::runif(18)) |> as.character(),
"additional_name" = "overall",
"additional_level" = "overall"
)
) |>
# medication - percentage
dplyr::union_all(
dplyr::tibble(
"cdm_name" = "mock",
"group_name" = "cohort_name",
"group_level" = c(rep("cohort1", 9), rep("cohort2", 9)),
"strata_name" = rep(c(
"overall", rep("age_group &&& sex", 4), rep("sex", 2), rep("age_group", 2)
), 2),
"strata_level" = rep(c(
"overall", "<40 &&& Male", ">=40 &&& Male", "<40 &&& Female",
">=40 &&& Female", "Male", "Female", "<40", ">=40"
), 2),
"variable_name" = "Medications",
"variable_level" = "Amoxiciline",
"estimate_name" = "percentage",
"estimate_type" = "percentage",
"estimate_value" = c(100*stats::runif(18)) |> as.character(),
"additional_name" = "overall",
"additional_level" = "overall"
)
) |>
# medication - count
dplyr::union_all(
dplyr::tibble(
"cdm_name" = "mock",
"group_name" = "cohort_name",
"group_level" = c(rep("cohort1", 9), rep("cohort2", 9)),
"strata_name" = rep(c(
"overall", rep("age_group &&& sex", 4), rep("sex", 2), rep("age_group", 2)
), 2),
"strata_level" = rep(c(
"overall", "<40 &&& Male", ">=40 &&& Male", "<40 &&& Female",
">=40 &&& Female", "Male", "Female", "<40", ">=40"
), 2),
"variable_name" = "Medications",
"variable_level" = "Ibuprofen",
"estimate_name" = "count",
"estimate_type" = "integer",
"estimate_value" = round(100000*stats::runif(18)) |> as.character(),
"additional_name" = "overall",
"additional_level" = "overall"
)
) |>
# medication - percentage
dplyr::union_all(
dplyr::tibble(
"cdm_name" = "mock",
"group_name" = "cohort_name",
"group_level" = c(rep("cohort1", 9), rep("cohort2", 9)),
"strata_name" = rep(c(
"overall", rep("age_group &&& sex", 4), rep("sex", 2), rep("age_group", 2)
), 2),
"strata_level" = rep(c(
"overall", "<40 &&& Male", ">=40 &&& Male", "<40 &&& Female",
">=40 &&& Female", "Male", "Female", "<40", ">=40"
), 2),
"variable_name" = "Medications",
"variable_level" = "Ibuprofen",
"estimate_name" = "percentage",
"estimate_type" = "percentage",
"estimate_value" = c(100*stats::runif(18)) |> as.character(),
"additional_name" = "overall",
"additional_level" = "overall"
)
) |>
dplyr::mutate(result_id = as.integer(1)) |>
omopgenerics::newSummarisedResult(
settings = dplyr::tibble(
"result_id" = as.integer(1),
"result_type" = "mock_summarised_result",
"package_name" = "visOmopResults",
"package_version" = utils::packageVersion("visOmopResults") |>
as.character()
)
)
return(result)
}
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