PooledLSD {CANE} | R Documentation |
Pooled Latin Square Design Analysis
Description
This function performs pooled analysis of variance (ANOVA) using the Latin square design for multiple locations or years. For more details see Montgomery (2017), 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
PooledLSD(
data,
Response,
Location,
Treatment,
Row,
Column,
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. |
Treatment |
A factor indicating the different treatments applied. |
Row |
A factor indicating rows. |
Column |
A factor indicating columns. |
alpha |
A numeric value specifying the significance level for Bartlett’s test. |
Mult_Comp_Test |
An integer specifying the type of multiple comparison test:
|
Value
A list containing the following components:
-
Individual_ANOVA: Summary of ANOVA results for each location or year.
-
Location_wise: Multiple comparisons of treatments 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 treatment comparisons using the selected multiple comparison test.
References
Dean A, Voss D, Draguljic D (2017)<doi:10.1007/978-3-319-52250-0>.
Montgomery DC (2017). Design and Analysis of Experiments. John wiley & sons.
Ruíz JS, López OAM, Crossa J (2024)<doi:10.1007/978-3-031-65575-3>.
Examples
# Creating a sample dataset for Pooled Latin Square Design (LSD)
df <- data.frame(
Location = factor(c(rep("Agra", 16), rep("Bihar", 16))), # Locations
Treatment = factor(c(4, 2, 3, 1, 3, 1, 4, 2, 1, 4, 2, 3, 2, 3, 1, 4,
4, 2, 3, 1, 3, 1, 4, 2, 1, 4, 2, 3, 2, 3, 1, 4)), # Treatments
Row = factor(rep(1:4, each = 4, times = 2)), # Row factor
Column = factor(rep(1:4, times = 8)), # Column factor
Yield = c(29.1, 18.9, 29.4, 5.7, 16.4, 10.2, 21.2, 19.1, 5.4, 38.8, 24, 37,
24.9, 41.7, 9.5, 28.9, 13, 27, 7, 24, 10, 13, 41, 39, 42, 26, 19, 20,
20, 35, 8, 38) # Yield values
)
# Running PooledLSD function on the dataset
out <- PooledLSD(df, "Yield", "Location", "Treatment", "Row", "Column", 0.05, 1)
# Print results
print(out)