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Initialize an Enrollment Flow

Source: R/core.R
enroll.Rd

Entry point for building an EQUATOR-style enrollment diagram from a single starting population. Accepts either a data.frame (data mode, where counts are computed automatically from exclusion expressions) or a starting count n (manual mode, where counts are supplied explicitly at each step).

Usage

enroll(data = NULL, id = NULL, n = NULL, label = "Study Population")

Arguments

data

A data.frame or data.table in which each row represents one participant. When supplied, exclusion expressions passed to exclude() are evaluated against this data to compute counts automatically. If NULL (default), the flow operates in manual mode.

id

Character string naming the participant ID column in data. Defaults to the first column. Ignored in manual mode.

n

Integer. Starting population count for manual mode. Must be a non-negative scalar. Ignored when data is supplied.

label

Character string for the top-level box in the diagram. Default is "Study Population".

Value

An object of class "selecta" containing the data (if supplied), mode, starting count, label, and an empty step list. Subsequent pipeline functions (exclude(), stratify(), endpoint(), etc.) append steps to this object.

Details

enroll() begins every single-source pipeline and fixes the operating mode for all subsequent steps. Supplying data (with id) selects data mode, in which later exclude() and stratify() steps filter and partition the dataset and counts are derived from the data. Alternatively, supplying n instead selects manual mode, in which counts are taken from the numbers given at each step. The two modes are mutually exclusive, and the resulting object is intended to be extended with the pipe operator. For diagrams with several entry sources that converge (PRISMA, MOOSE), use sources() instead of enroll().

See also

sources for multi-source entry, exclude for adding exclusion criteria, flowchart for rendering

Other flow construction functions: assess(), combine(), endpoint(), exclude(), phase(), sources(), stratify()

Examples

# Manual mode
enroll(n = 500, label = "Assessed for eligibility")
#> selecta flow (manual mode)
#>   Starting N: 500
#>   Steps: 0

# Data mode
enroll(selectaex2, id = "patient_id", label = "Study Population")
#> selecta flow (data mode)
#>   Starting N: 2,400
#>   Steps: 0

# Minimal CONSORT pipeline
enroll(n = 500) |>
  exclude("Ineligible", n = 65) |>
  allocate(labels = c("Treatment", "Control"), n = c(218, 217)) |>
  endpoint("Analyzed")
#> selecta flow (manual mode)
#>   Starting N: 500
#>   Steps: 3
#>   [1] exclude: "Ineligible" (n = 65)
#>   [2] stratify: Treatment, Control
#>          label: "Randomized"
#>   [3] endpoint: "Analyzed"