PooledSPD: Pooled Split Plot Design Analysis

In CANE: Comprehensive Groups of Experiments Analysis for Numerous Environments

Pooled Split Plot Design Analysis

Description

This function conducts a pooled analysis of variance (ANOVA) using the split plot design (SPD) for data collected across multiple locations or years. In this design, subplot effects are estimated with greater precision. For more details see Dean et al. (2017)<doi:10.1007/978-3-319-52250-0> and Ruíz et al. (2024)<doi:10.1007/978-3-031-65575-3>.

Usage

PooledSPD(
  data,
  Response,
  Location,
  Replication,
  MainPlot,
  SubPlot,
  alpha,
  Mult_Comp_Test
)

Arguments

data	A data frame containing the experimental data.
Response	A numeric variable representing the dependent variable (response).
Location	A factor indicating different locations or years.
Replication	A factor indicating replications.
MainPlot	A factor which require larger plot sizes.
SubPlot	A factor which require smaller plot sizes.
alpha	A numeric value specifying the significance level for Bartlett’s test.
Mult_Comp_Test	An integer specifying the type of multiple comparison test: 1 = Tukey's honestly significant difference (Tukey's HSD) test 2 = Duncan's multiple range test (DMRT) 3 = least significant difference (LSD) test

Value

A list containing the following components:

• Individual_ANOVA: Summary of ANOVA results for each location or year.

• Location_wise: Multiple comparisons of subplots within each location or year.

• Bartlett_Test: Results of Bartlett's test for homogeneity of variances.

• Pooled_ANOVA: Combined (pooled) ANOVA table across all locations or years.

• Treatments_Comparison: Summary of pooled subplots comparisons using the selected multiple comparison test.

References

Dean A, Voss D, Draguljic D (2017)<doi:10.1007/978-3-319-52250-0>.

Ruíz JS, López OAM, Crossa J (2024)<doi:10.1007/978-3-031-65575-3>.

Examples

# Creating a sample dataset for Pooled Split Plot Design (SPD)
df <- data.frame(
  Location = factor(rep(c("Londan", "Agumbe"), each = 12)),  # Locations
  Replication = factor(rep(c(1, 2), each = 6, times = 2)),  # Replications
  MainPlot = factor(rep(c(1, 2), each = 3, times = 4)),  # Main plot factor
  SubPlot = factor(rep(1:3, times = 8)),  # Sub plot factor
  Yield = c(4940, 4810, 5150, 4900, 4920, 5070, 
            4830, 5110, 4920, 5020, 5110, 5230,
            4964, 4997, 5011, 5102, 4858, 4888, 
            5100, 5165, 4965, 5113, 5086, 5176)  # Yield values
)

# Running PooledSPD function on the dataset
out <- PooledSPD(df, "Yield", "Location", "Replication", "MainPlot", "SubPlot", 0.05, 1)

# Print results
print(out)

CANE documentation built on April 3, 2025, 9:25 p.m.