| Title: | Analysis of Latin Square and Semi-Latin Square Designs |
| Version: | 0.4.1 |
| Description: | Provides functions for the analysis of Latin Square and Semi-Latin Square (Latin Rectangle) experimental designs, including analysis of variance (ANOVA), least significant difference (LSD) tests, and calculation of summary statistics. The implemented methods follow Munzert (1992, ISBN: 3-489-53410-7). |
| Depends: | R (≥ 4.0.0) |
| Imports: | openxlsx |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 8.0.0 |
| NeedsCompilation: | no |
| Packaged: | 2026-06-18 09:18:46 UTC; Heinrich.Holzner |
| Author: | Heinrich Holzner [aut, cre] |
| Maintainer: | Heinrich Holzner <heholzner@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2026-06-23 14:00:09 UTC |
Wrapper for Excel input
Description
Reads an Excel file and calls LQuad_df.
Usage
LQuad(
file_path,
sheet_name,
block_col,
column_col,
treatment_col,
response_cols
)
Arguments
file_path |
Path to Excel file |
sheet_name |
Sheet name |
block_col |
Column name for block factor |
column_col |
Column name for column factor |
treatment_col |
Column name for treatment factor |
response_cols |
Vector of response variable column names |
Value
A named list identical to the output of LQuad_df(), i.e.
ANOVA results, LSD values and means for each response variable.
Examples
file <- system.file("extdata", "munzert_example_tab4_9.xlsx",
package = "LatSquare")
res <- LQuad(
file_path = file,
sheet_name = "Kartoffeln",
block_col = "Block",
column_col = "Saeule",
treatment_col = "VNr",
response_cols = "ParzErtrag_in_kg"
)
res
Analysis of a Latin Square / Semi Latin Square
Description
Performs ANOVA for a Latin square or semi-Latin square (Latin rectangle) design and calculates LSD values and treatment means. The implemented methods follow Munzert (1992, ISBN: 3-489-53410-7).
Usage
LQuad_df(data, block_col, column_col, treatment_col, response_cols)
Arguments
data |
Data frame containing the experimental data |
block_col |
Column name for block factor |
column_col |
Column name for column factor |
treatment_col |
Column name for treatment factor |
response_cols |
Vector of response variable column names |
Value
A named list with one element per response variable. Each element contains:
- Design
List with design parameters: number of blocks, columns, treatments, factor a, number of observations, and type of design (Latin square or Latin rectangle).
- ANOVA
Data frame with analysis of variance including degrees of freedom (DF), sum of squares (SS), mean squares (MS), F-values and p-values.
- LSD
Data frame containing least significant difference values for significance levels 0.05 and 0.01.
- Means
List of means including overall mean as well as means for blocks, columns, and treatments.
Examples
file <- system.file("extdata", "munzert_example_tab4_9.xlsx",
package = "LatSquare")
dat <- openxlsx::read.xlsx(file, sheet = "Kartoffeln")
res <- LQuad_df(
data = dat,
block_col = "Block",
column_col = "Saeule",
treatment_col = "VNr",
response_cols = "ParzErtrag_in_kg"
)
res