Run the Shiny App for performing one-way ANOVA on data from a Randomized block design.

App allows user to import data through excel/.csv files or through clipboard and user can select the post-hoc test method and download the report which contains anova results and plots

Usage

oneway_rbd()

Value

This function runs a local instance of the Shiny app in your default web browser. The app interface allows users to upload data, select analysis method, and download outputs.

Details

This Shiny app is part of the visvaR package and is designed for analysis of variance on data from randomized block design (one factor) and user can download the report in word format. The analysis of variance was performed using R's aov() function (Chambers & Hastie, 1992; R Core Team, 2024), which implements the classical ANOVA methodology developed by Fisher (1925).To use custom fonts, please install the extrafont package and run extrafont::font_import() and extrafont::loadfonts().

References

Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd, Edinburgh. Scheffe, H. (1959). The Analysis of Variance. John Wiley & Sons, New York. R Core Team (2024). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/

Author

Ramesh Ramasamy

Mathiyarsai Kulandaivadivel

Tamilselvan Arumugam

Examples

# Example 1: Basic usage
if(interactive()) {
  oneway_rbd()
}

# Example 2: Sample workflow with plant growth experiment
if(interactive()) {
  # Prepare sample data
  plant_data <- data.frame(
    Treatment = rep(c("Control", "Low", "Medium", "High"), each = 3),
    Replication = rep(1:3, times = 4),
    Plant_Height = c(25.3, 24.8, 25.1,  # Control
                     27.6, 28.1, 27.9,  # Low
                     30.2, 29.8, 30.5,  # Medium
                     26.8, 27.2, 26.5), # High
    Leaf_Count = c(8, 7, 8,    # Control
                   10, 11, 10,  # Low
                   12, 13, 12,  # Medium
                   9, 8, 9)     # High
  )

  # Save as Excel file
  write.xlsx(plant_data, "plant_data.xlsx")

  # Launch the app
  oneway_rbd()

  # Instructions for users:
  # 1. Click "Choose .xlsx or .csv" and select plant_data.xlsx
  # 2. Select post-hoc test method (e.g., "Tukey HSD")
  # 3. Customize plot appearance if desired:
  #    - Choose bar color
  #    - Select font style
  #    - Adjust font size
  # 4. Click "Analyze"
  # 5. View results in different tabs
  # 6. Download Word report

  # Clean up
  unlink("plant_data.xlsx")
}

# Example 3: Using clipboard data
if(interactive()) {
  # Copy this to clipboard:
  # Treatment,Replication,Yield
  # Control,1,45.2
  # Control,2,44.8
  # Control,3,45.5
  # Treatment1,1,48.6
  # Treatment1,2,49.2
  # Treatment1,3,48.9
  # Treatment2,1,52.3
  # Treatment2,2,51.8
  # Treatment2,3,52.7

  oneway_rbd()
  # Click "Use Clipboard Data" after copying data
}

# Example 4: Multiple response variables
if(interactive()) {
  # Create data with multiple responses
  multi_response_data <- data.frame(
    Treatment = rep(c("Control", "Treatment1", "Treatment2"), each = 4),
    Replication = rep(1:4, times = 3),
    Height = rnorm(12, mean = c(rep(20,4), rep(25,4), rep(30,4)), sd = 2),
    Weight = rnorm(12, mean = c(rep(50,4), rep(60,4), rep(70,4)), sd = 5),
    Length = rnorm(12, mean = c(rep(10,4), rep(12,4), rep(15,4)), sd = 1)
  )

  # Save as Excel file
  write.xlsx(multi_response_data, "multi_response.xlsx")

  # Launch the app
  oneway_rbd()
  }