function.submit_choices: Wrapper Function That Performs the Analysis and Generates the Standalone Codes

Description

This function is a wrapper function that chooses the correct analysis function to perform, saves the results in a zip folder, and generates the code for the standalone analysis.

Usage

function.submit_choices(Predefined_lists, rv, code_prefix, no_data_choices)

Value

Analysis_results: Analysis results includes the results of the last called analysis, a plan which includes all previous analysis performed in the session with the data set, and a standard alone R code which allows reproducibility of results.

Arguments

Predefined_lists: A list supplied by 'EQUAL-STATS' application
rv: A list supplied by 'EQUAL-STATS' application based on user input
code_prefix: Code that forms the start of the standalone code
no_data_choices: A list of functions that do not require data upload

Author

Kurinchi Gurusamy

References

https://sites.google.com/view/equal-group/home

Examples

Run this code

# Create simulated data ####
data <- cbind.data.frame(
  `Subject ID` = c(
    "S0001", "S0002", "S0003", "S0004", "S0005",
    "S0006", "S0007", "S0008", "S0009", "S0010",
    "S0011", "S0012", "S0013", "S0014", "S0015",
    "S0016", "S0017", "S0018", "S0019", "S0020",
    "S0021", "S0022", "S0023", "S0024", "S0025",
    "S0026", "S0027", "S0028", "S0029", "S0030"),
  `Centre` = c(
    "C_0001", "C_0002", "C_0002", "C_0002", "C_0002",
    "C_0001", "C_0001", "C_0003", "C_0001", "C_0003",
    "C_0001", "C_0002", "C_0002", "C_0001", "C_0003",
    "C_0002", "C_0002", "C_0003", "C_0001", "C_0002",
    "C_0002", "C_0002", "C_0002", "C_0003", "C_0002",
    "C_0001", "C_0003", "C_0001", "C_0001", "C_0001"),
  `Treatment` = c(
    "Intensive rehabilitation", "Intensive rehabilitation", "Standard rehabilitation",
    "Intensive rehabilitation", "Intensive rehabilitation", "Intensive rehabilitation",
    "Intensive rehabilitation", "Intensive rehabilitation", "Intensive rehabilitation",
    "Standard rehabilitation", "Intensive rehabilitation", "Standard rehabilitation",
    "Standard rehabilitation", "Intensive rehabilitation", "Intensive rehabilitation",
    "Intensive rehabilitation", "Standard rehabilitation", "Standard rehabilitation",
    "Intensive rehabilitation", "Standard rehabilitation", "Intensive rehabilitation",
    "Intensive rehabilitation", "Standard rehabilitation", "Intensive rehabilitation",
    "Intensive rehabilitation", "Standard rehabilitation", "Standard rehabilitation",
    "Intensive rehabilitation", "Standard rehabilitation", "Intensive rehabilitation"),
  `Obesity status` = c(
    "Obese", "Non-obese", "Obese", "Non-obese", "Non-obese",
    "Obese", "Obese", "Obese", "Non-obese", "Obese",
    "Non-obese", "Non-obese", "Obese", "Non-obese", "Obese",
    "Obese", "Non-obese", "Obese", "Obese", "Obese",
    "Non-obese", "Non-obese", "Non-obese", "Obese", "Obese",
    "Non-obese", "Obese", "Obese", "Obese", "Obese"),
  `Unable to walk independently at 6 weeks` = c(
    "unable", "able", "able", "unable", "able",
    "able", "unable", "unable", "unable", "unable",
    "able", "unable", "able", "unable", "unable",
    "able", "unable", "unable", "unable", "unable",
    "able", "able", "able", "able", "unable",
    "able", "able", "unable", "able", "unable"),
  `Mobility score at 6 months` = c(
    86, 65.1, 48, 99.8, 73.4, 70, 74.7, 36.5, 64.6, 85.4,
    41.7, 60.1, 73.3, 42.4, 55.3, 47.3, 85.9, 63, 64.6, 101.8,
    108.1, 72.3, 96.4, 87.5, 66.2, 92.9, 47.7, 55.8, 56.4, 133.8),
  `Pain at 6 weeks` = c(
    "3_severe", "1_mild", "1_mild", "2_moderate", "1_mild",
    "1_mild", "2_moderate", "2_moderate", "1_mild", "3_severe",
    "1_mild", "2_moderate", "1_mild", "3_severe", "3_severe",
    "1_mild", "2_moderate", "3_severe", "2_moderate", "2_moderate",
    "1_mild", "1_mild", "1_mild", "1_mild", "2_moderate",
    "1_mild", "1_mild", "2_moderate", "1_mild", "2_moderate"),
  `Number of falls within 6 months` = c(
    3, 2, 3, 2, 2, 1, 4, 2, 2, 5,
    3, 2, 2, 2, 5, 3, 2, 2, 3, 4,
    3, 1, 2, 2, 2, 7, 2, 1, 1, 8),
  `Mobility score at 12 months` = c(
    90, 69.1, 52, 103.8, 77.4, 74, 78.7, 40.5, 68.6, 89.4,
    45.7, 64.1, 77.3, 46.4, 59.3, 51.3, 89.9, 67, 68.6, 105.8,
    112.1, 76.3, 100.4, 91.5, 70.2, 96.9, 51.7, 59.8, 60.4, 137.8) ,
  `Admission to care home` = c(
    "Not admitted", "Not admitted", "Admitted", "Not admitted", "Admitted",
    "Admitted", "Not admitted", "Admitted", "Admitted", "Not admitted",
    "Admitted", "Admitted", "Not admitted", "Not admitted", "Not admitted",
    "Not admitted", "Admitted", "Admitted", "Not admitted", "Not admitted",
    "Not admitted", "Admitted", "Not admitted", "Admitted", "Admitted",
    "Admitted", "Admitted", "Admitted", "Admitted", "Not admitted"),
  `Follow-up` = c(
    10, 8, 8, 8, 12, 12, 11, 10, 8, 7,
    8, 6, 9, 6, 9, 8, 10, 8, 11, 9,
    6, 9, 12, 9, 8, 11, 12, 9, 10, 11)
)
# Simulate lists provided by EQUAL-STATS
entry <- list()
entry <- lapply(1:15, function(x) entry[[x]] <- '')
Predefined_lists <- list(
  main_menu = c(
    'Calculate summary measures',
    'Create plots',
    'Check distribution',
    'Compare sample mean versus population mean',
    'Compare groups/variables (independent samples)',
    'Compare groups/variables (paired samples or repeated measures)',
    'Find the correlation (quantitative variables)',
    'Calculate measurement error',
    'Find the diagnostic accuracy (primary data)',
    'Perform sample size and power calculations (primary data)',
    'Perform survival analysis',
    'Perform regression analysis',
    'Analyse time series',
    'Perform mixed-effects regression',
    'Perform multivariate regression',
    'Generate hypothesis',
    'Perform sample size and power calculations (effect size approach)',
    'Make correct conclusions (effect size approach)',
    'Find the diagnostic accuracy (tabulated data)'
  ),
  menu_short = c(
    'Summary_Measures',
    'Create_Plots',
    'Check_Distribution',
    'Compare_Sample_Pop_Means',
    'Compare_Groups',
    'Repeated_Measures',
    'Correlation',
    'Measurement_Error',
    'Diagnostic_Accuracy_Primary',
    'Sample_Size_Calculations_Primary',
    'Survival_Analysis',
    'Regression_Analysis',
    'Time_Series',
    'Mixed_Effects_Regression',
    'Multivariate_Regression',
    'Generate_Hypothesis',
    'Sample_Size_Calculations_Effect_size',
    'Make_Conclusions_Effect_size',
    'Diagnostic_Accuracy_Tables'
  )
)
rv <- list(
  StorageFolder = tempdir(),
  first_menu_choice = NA,
  second_menu_choice = NA,
  entry = entry,
  import_data = NULL,
  same_row_different_row = NA
)
no_data_choices <- c("Generate_Hypothesis", "Sample_Size_Calculations_Effect_size",
"Make_Conclusions_Effect_size", "Diagnostic_Accuracy_Tables")
code_prefix <- ""
# Store the data in a folder
data_file_path = paste0(tempdir(), "/data.csv")
write.csv(data, file = data_file_path, row.names = FALSE, na = "")
# Load the necessary packages and functions ####
library(stringr)
library(DescTools)
library(zip)
rv$import_data <- function.read_data(data_file_path)
# Update choices ####
rv$first_menu_choice <- "Summary_Measures"
rv$second_menu_choice <- NA
rv$entry[[1]] <- "Obesity status"
rv$entry[[2]] <- "Treatment"
rv$entry[[3]] <- "EQUAL-STATS choice"
Results <- function.submit_choices(Predefined_lists, rv, code_prefix, no_data_choices)

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