dfMergeVariablesRelevel: Merge variables, keeping type, and optionally relevel factors

In ctrdata: Retrieve and Analyze Clinical Trials in Public Registers

Merge variables, keeping type, and optionally relevel factors

Description

Merge variables in a data frame such as returned by dbGetFieldsIntoDf into a new variable, and optionally also map its values to new levels. See ctrdata-trial-concepts for pre-defined cross-register concepts that are already implemented based on merging fields from different registers and calculating a new field.

Usage

dfMergeVariablesRelevel(df = NULL, colnames = "", levelslist = NULL)

Arguments

df	A data.frame with the variables (columns) to be merged into one vector.
colnames	A vector of names of columns in 'df' that hold the variables to be merged, or a selection of columns as per select.
levelslist	A names list with one slice each for a new value to be used for a vector of old values (optional).

Value

A vector, with the type of the columns to be merged

Examples

dbc <- nodbi::src_sqlite(
  dbname = system.file("extdata", "demo.sqlite", package = "ctrdata"),
  collection = "my_trials",
  flags = RSQLite::SQLITE_RO)
df <- dbGetFieldsIntoDf(
  fields = c(
    "protocolSection.eligibilityModule.healthyVolunteers",
    "f31_healthy_volunteers",
    "eligibility.healthy_volunteers"
  ),
  con = dbc
)

table(
  dfMergeVariablesRelevel(
    df = df,
    colnames = 'matches("healthy")'
))

ctrdata documentation built on April 3, 2025, 8:12 p.m.