Run the Shiny App for performing one-way ANOVA on data from a completely randomized design.
Source:R/oneway_crd.R
oneway_crd.RdApp 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
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 completely randomized 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/
Examples
# Example 1: Basic usage
if(interactive()) {
oneway_crd()
}
# 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_crd()
# 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_crd()
# 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_crd()
# App will analyze all response variables (Height, Weight, Length)
# and generate separate analyses and plots for each
# Clean up
unlink("multi_response.xlsx")
}
# Example 5: Working with data frame in memory
if(interactive()) {
# Create data frame
yield_data <- data.frame(
Variety = rep(c("V1", "V2", "V3", "V4"), each = 3),
Replication = rep(1:3, times = 4),
Grain_Yield = c(
4.5, 4.7, 4.6, # V1
5.2, 5.0, 5.3, # V2
4.8, 4.9, 4.7, # V3
5.5, 5.4, 5.6 # V4
)
)
# Save temporarily and analyze
write.xlsx(yield_data, "temp_data.xlsx")
oneway_crd()
unlink("temp_data.xlsx")
}