create_generic_input_parameters: Create generic input parameters

In EQUALPrognosis: Analysing Prognostic Studies

Create generic input parameters

Description

This function simply checks whether the input parameters are correct and if correct, creates a list from the input parameters. This also makes some corrections when possible (i.e., when there were minor correctable issues in the input parameters).

Usage

create_generic_input_parameters(general_title, simulations, simulations_per_file,
seed, df, outcome_name, outcome_type, outcome_time, outcome_count, verbose)

Arguments

general_title	A general title for your analysis
simulations	The number of simulations required. Usually at least 300 to 500 simulations are a minimum. Increasing the simulations leads to more reliable results. The default value of 2000 simulations should provide reasonably reliable results.
simulations_per_file	This is to manage the memory requirements. The default value of 20 simulations per file should work in most instances.
seed	Please see prepare_datasets for details.
df	The dataset used for the analysis. This must be provided as a dataframe. Data in files can be converted to dataframes with appropriate field types using process_data.
outcome_name	Name of the colummn that contains the outcome data. This must be a column name in the 'df' provided as input.
outcome_type	One of 'binary', 'time-to-event', 'quantitative'. Count outcomes are included in 'quantitative' outcome type and can be differentiated from continuous outcomes by specifying outcome_count as TRUE. Please see examples below.
outcome_time	The name of the column that provides the follow-up time. This is applicable only for 'time-to-event' outcome. For other outcome types, enter NA.
outcome_count	TRUE if the outcome was a count outcome and FALSE otherwise.
verbose	TRUE if the outcome message must be displayed and FALSE otherwise.

Value

outcome	The outcome containing the processing details. If some corrections were made, the corrections are included in the outcome. If there was a fatal error, the reason for the fatal error is provided.
generic_input_parameters	A list with information for further analyses. If there was a fatal error, the reason for the fatal error is displayed and generic_input_parameters is NULL.

Author(s)

Kurinchi Gurusamy

See Also

process_data prepare_datasets

Examples

# Correct parameters ####
# Binary outcome
# verbose is TRUE, therefore, the outcome message will be displayed
results <- create_generic_input_parameters(
general_title = "Prediction of penguin species", simulations = 2000,
simulations_per_file = 20, seed = 1, df = penguins, outcome_name = "species",
outcome_type = "binary", outcome_time = NA, outcome_count = FALSE, verbose = TRUE)
generic_input_parameters <- results$generic_input_parameters
generic_input_parameters

# Time-to-event outcome
library(survival)
# The field 'status' is provided as numeric. This must be converted to factor. In
# this example, we can convert this to factor using a command. For conversion of more
# columns, please use process_data function.
colon$status <- factor(as.character(colon$status))
# verbose is FALSE, therefore, the outcome message will not be displayed, but the
# outcome is stored.
results <- create_generic_input_parameters(
general_title = "Prediction of colon cancer death", simulations = 2000,
simulations_per_file = 20, seed = 1, df = colon, outcome_name = "status",
outcome_type = "time-to-event", outcome_time = "time", outcome_count = FALSE,
verbose = FALSE)
# Display outcome
results$outcome
# Display generic_input_parameters
generic_input_parameters <- results$generic_input_parameters
generic_input_parameters

# Continuous outcome
# verbose is not supplied, therefore, the outcome message will be displayed as
# this is the default.
results <- create_generic_input_parameters(
general_title = "Prediction of iris petal length", simulations = 2000,
simulations_per_file = 20, seed = 1, df = iris, outcome_name = "Petal.Length",
outcome_type = "quantitative", outcome_time = NA, outcome_count = FALSE)
generic_input_parameters <- results$generic_input_parameters
generic_input_parameters

# Count outcomes
results <- create_generic_input_parameters(
general_title = "Prediction of warp breaks", simulations = 2000,
simulations_per_file = 20, seed = 1, df = warpbreaks, outcome_name = "breaks",
outcome_type = "quantitative", outcome_time = NA, outcome_count = TRUE)
generic_input_parameters <- results$generic_input_parameters
generic_input_parameters

# Non fatal errors ####
results <- create_generic_input_parameters(
general_title = "", simulations = "Use default",
simulations_per_file = "Use default", seed = "Use default",
df = warpbreaks, outcome_name = "breaks",
outcome_type = "quantitative", outcome_time = "Use default", outcome_count = TRUE,
verbose = TRUE)
generic_input_parameters <- results$generic_input_parameters
generic_input_parameters

# Fatal error ####
# Note the dataframe name supplied within quotes.
results <- create_generic_input_parameters(
general_title = "", simulations = "Use default",
simulations_per_file = "Use default", seed = "Use default",
df = "warpbreaks", outcome_name = "breaks", outcome_type = "quantitative",
outcome_time = "Use default", outcome_count = TRUE, verbose = TRUE)
generic_input_parameters <- results$generic_input_parameters
generic_input_parameters

EQUALPrognosis documentation built on Feb. 4, 2026, 5:15 p.m.