create_generic_input_parameters: 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)

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.

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.

Author

Kurinchi Gurusamy

Examples

Run this code

# 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