Package {ofemeantest}

ofemeantest: On Farm Experimentation Mean Test

Description

Provides tools for comparing treatments in unreplicated on-farm experiments (OFE) using georeferenced data. The package includes functions for constructing spatial grids, estimating the effective sample size from spatial autocorrelation, performing repeated permutation tests, adjusting pairwise comparisons, and visualizing the results. It implements the OFE-mean test described in Córdoba, Paccioretti and Balzarini (2025) doi:10.1007/s11119-024-10206-0.

Author(s)

Maintainer: Pablo Paccioretti pablopaccioretti@agro.unc.edu.ar [copyright holder]

Authors:

• Pablo Paccioretti pablopaccioretti@agro.unc.edu.ar [copyright holder]

• Mariano Córdoba marianoacba@agro.unc.edu.ar [copyright holder]

• Monica Balzarini mbalzari@agro.unc.edu.ar

See Also

Useful links:

• https://ppaccioretti.github.io/ofemeantest/

• https://github.com/PPaccioretti/ofemeantest

• Report bugs at https://github.com/PPaccioretti/ofemeantest/issues

Build OFE grid and (initially) select all cells

Description

Build OFE grid and (initially) select all cells

Usage

all_cells_grid(data, cellsize, angle_deg = 0, buffer = 0, shift = c(0, 0))

Arguments

Value

An object of class 'ofe_grid' (a list) with:

• 'grid_all': 'sf' polygons of the full grid (with 'CellID').

• 'grid_sel': initially identical to 'grid_all' (no filtering yet).

• 'params': a named list of grid parameters (cellsize, shift, angle, buffer, CRS).

Filter OFE grid cells containing a single treatment

Description

Performs a spatial join between point data ('sf') and an OFE grid, identifies cells containing exactly one unique treatment, and returns an updated 'ofe_grid' object with only those eligible cells retained in its 'grid_sel' component.

Usage

filter_per_treatment(data, grid, x)

Arguments

Details

The function:

1. Validates the input types and column name.

2. Replaces spaces in treatment labels with dots and stores them in a temporary column '".trt"'.

3. Ensures that the grid has a '"CellID"' column (creates one if missing).

4. Joins points to grid cells via 'sf::st_intersects()'.

5. Aggregates per cell and keeps only cells containing a single unique treatment ('unique_trt == 1').

Points outside the grid are dropped ('left = FALSE' in the join).

Value

An updated 'ofe_grid' object whose 'grid_sel' component contains only polygons corresponding to single-treatment cells.

Get permutation runs

Description

Get permutation runs

Usage

get_perm_results(x)

Arguments

Value

data.frame with columns Comparison, p_value, run, etc.

One-line description of the grid parameters

Description

One-line description of the grid parameters

Usage

grid_params_label(params)

Arguments

Value

A character scalar, or 'NULL' when 'params' is empty.

Draw the grid selection with base graphics

Description

Draw the grid selection with base graphics

Usage

grid_plot_base(
  grid_all,
  grid_sel,
  data,
  main,
  legend,
  legend_pos,
  point_size = NULL,
  ...
)

Arguments

Value

Invisibly 'NULL'.

Draw the grid selection with ggplot2

Description

Draw the grid selection with ggplot2

Usage

grid_plot_ggplot(
  grid_all,
  grid_sel,
  data,
  main,
  legend,
  legend_pos,
  point_size = NULL
)

Arguments

Value

A 'ggplot' object.

Translate a legend position to ggplot2's vocabulary

Description

Lets the same ‘legend_pos' value work with either engine: base’s corner keywords collapse to the nearest ggplot2 side, and anything ggplot2 already understands (including a numeric 'c(x, y)') passes through untouched.

Usage

legend_pos_gg(pos, legend = TRUE)

Arguments

Value

A value suitable for 'ggplot2::theme(legend.position = )'.

Create an OFE grid and select valid cells

Description

Convenience wrapper that builds a grid with [all_cells_grid()] and filters cells using [select_grid()]. It is the main entry point for generating grids for on-farm experiment (OFE) analysis.

Usage

make_ofe_grid(
  data,
  x,
  cellsize,
  min_per_cell = 1L,
  angle_deg = 0,
  buffer = 0,
  shift = c(0, 0),
  return_points = FALSE
)

Arguments

Value

An 'ofe_grid' object returned by [select_grid()], containing the full grid, the selected cells, and associated metadata.

See Also

[all_cells_grid()], [select_grid()]

Examples

 grid_ofe <- make_ofe_grid(
   ofe_f2,
   x = "Treatment",
   cellsize = 9,
   min_per_cell = 1L,
   angle_deg = 0,
   buffer = 0,
   shift = c(0, 0),
   return_points = TRUE
 )
 plot_grid_selection(grid_ofe)

Effective sample size under spatial autocorrelation

Description

Heuristic function to adjust sample size 'n' by a spatial autocorrelation parameter 'rho'. Based on: Griffith, D.A., & Peres-Neto, P.R. (2006). Spatial Modeling in Ecology: The Flexibility of Eigenfunction Spatial Analyses. Ecology, 87(10), 2603–2613.

Usage

n_eff(n, rho)

Arguments

Value

numeric, effective sample size.

Regions with no neighbours in an 'nb' object

Description

In 'spdep', a region with an empty neighbour set is stored as the integer '0L'. This helper returns the positions of those regions.

Usage

nb_no_links(nb)

Arguments

Value

Integer vector of positions with an empty neighbour set.

On-Farm single strip treatment trial (Field F2)

Description

The impact of broadcast phosphorus (P) fertilization on corn was evaluated. The Fertilized strip received superphosphate at rates ranging from 250 to 500 kg ha-1 \[0-21-0\], while the Control strip received no P fertilizer (0 kg ha-1). Each strip was 2.2 ha in area, totaling 100 ha.

Usage

ofe_f2

Format

A sf object with 3070 rows and 3 variables:

Treatment

character, identifying Fertilized or Control strip

Yield_tn

numeric, corn grain yield in tn/ha

geom

sf geometry column

Details

Coordinate reference system is "WGS 84 / UTM zone 20S", EPSG:32720.

On-Farm single strip treatment trial (companion dataset)

Description

Companion on-farm experiment used to demonstrate the package on a second field. Same layout as [ofe_f2]: a single fertilized strip compared against an adjacent control strip on dense yield-monitor data, with yields cleaned following Vega et al. (2019).

Usage

ofe_p

Format

A sf object with 3070 rows and 3 variables:

Treatment

character, identifying Fertilized or Control strip

Yield_tn

numeric, grain yield in tn/ha

geom

sf geometry column

Details

Coordinate reference system is "WGS 84 / UTM zone 20S", EPSG:32720.

OFE permutation analysis

Description

Analyzes unreplicated on-farm experiments to support field-specific inference about treatment effects. Spatial statistical methods are combined with permutation tests to compare the means of two or more treatments.

Usage

ofemt(
  data,
  y,
  x,
  cellsize = 10,
  min_per_cell = 4,
  n_p = 1000,
  n_s = 200,
  alpha = 0.05,
  shift = c(0, 0),
  p_adjust_method = c("none", "bonferroni", "holm", "BH"),
  crs = NULL,
  keep_components = c("none", "light", "full"),
  grid = NULL,
  angle_deg = 0,
  buffer = 0,
  seed = 7L
)

Arguments

Details

The OFE-mean test accounts for spatial dependence when comparing treatments in unreplicated on-farm experiments. The procedure involves:

1. Aggregating the georeferenced observations within grid cells.

2. Estimating the spatial autocorrelation of the treatment-adjusted residuals.

3. Calculating the effective sample size (ESS) from the estimated spatial dependence.

4. Drawing repeated balanced subsamples whose size is determined by the ESS.

5. Performing pairwise permutation analysis of variance tests for each subsample.

6. Generating an empirical distribution of p-values for each treatment comparison.

The median of each empirical p-value distribution is reported as the p-value associated with the null hypothesis of no treatment effect.

For experiments with more than two treatments, all pairwise treatment comparisons are performed.

Multiplicity adjustment

When 'p_adjust_method != "none"', multiplicity adjustment is performed separately within each sampling run. [stats::p.adjust()] is applied to the 'choose(k, 2)' pairwise p-values obtained in that run, where 'k' is the number of treatments. The reported adjusted p-value is the median of the resulting empirical distribution of adjusted p-values.

The 'p_adj' column in 'perm_runs' contains the adjusted p-value from each sampling run. Therefore, [plot_pvalue_hist()] displays the empirical distribution used to calculate the reported median.

Compact letter display

Treatments are ordered by decreasing response before the compact letter display is generated. Treatments that do not share a letter are considered significantly different at the significance level specified by 'alpha'. Treatment labels are internally recoded before calling [multcompView::multcompLetters()] and subsequently restored. Consequently, labels containing spaces or special characters are preserved in the results.

Value

An object of class 'ofemt_result': a list with

'General information'

One-row data frame with the cell size, the number of cells in the full grid and in the selection, the min/median/max number of observations per selected cell, the number of cells entering the analysis ('n'), the effective sample size ('ESS'), the spatial autocorrelation estimate (‘Rho') and Moran’s *I*.

'Cells per treatment'

'table' of selected cells per treatment.

'ANOVA permutation test'

One row per pairwise comparison, with the median p-value across runs ('p_value') and its multiplicity-adjusted counterpart ('p_adj').

'Means comparison'

One row per treatment, sorted by decreasing median response, with the compact letter display.

'perm_runs'

The raw per-run output: 'n_s * choose(k, 2)' rows with columns 'Trt_1', 'Trt_2', 'Comparison', 'p_value' (the permutation p-value of that comparison in that run), 'p_adj' (the same value after adjusting within the run) and 'run' (run index, '1:n_s'). This is the empirical p-value distribution the method is built on; it is what [plot_pvalue_hist()] draws and what you would use to inspect the run-to-run variability behind the reported medians.

'params'

The settings actually used (grid geometry, 'n_p', 'n_s', 'alpha', 'p_adjust_method', 'seed', and 'grid_source', which records whether the grid was supplied or built internally).

'grid', 'cell_medians', 'points_joined'

Optional spatial components; see 'keep_components'.

References

Córdoba, M., Paccioretti, P. and Balzarini, M. (2025). A new method to compare treatments in unreplicated on-farm experimentation. Precision Agriculture, 26, Article 4. doi:10.1007/s11119-024-10206-0

See Also

[make_ofe_grid()], [plot_grid_selection()], [plot_pvalue_hist()]

Examples

  res <- ofemt(ofe_f2, y = "Yield_tn", x = "Treatment",
               cellsize = 10, min_per_cell = 4, alpha = 0.05)

  # Keep the geometries to inspect how the grid lands on the points
  res <- ofemt(ofe_f2, y = "Yield_tn", x = "Treatment",
               cellsize = 10, min_per_cell = 4,
               keep_components = "full")
  plot(res)

Plot the grid, the selected cells and the observations

Description

Draws the three layers that matter when tuning a grid, on one set of axes: the **full grid** in light grey, the **selected cells** (those that passed the single-treatment and 'min_per_cell' filters) shaded and outlined in black, and the **observations** as points. Seeing the points against the cell boundaries is the quickest way to judge the effect of 'cellsize', 'shift', 'angle_deg' and 'buffer'.

Usage

plot_grid_selection(
  x,
  data = NULL,
  points = TRUE,
  main = NULL,
  legend = TRUE,
  legend_pos = NULL,
  point_size = NULL,
  engine = c("ggplot2", "base"),
  ...
)

## S3 method for class 'ofe_grid'
plot(x, ...)

## S3 method for class 'ofemt_result'
plot(x, ...)

Arguments

Value

With 'engine = "ggplot2"', a 'ggplot' object. In non-interactive contexts (e.g. scripts or inside 'pdf()'), call 'print()' on the returned object to render it. With 'engine = "base"', invisibly 'NULL' — the function is called for the plot it draws.

See Also

[make_ofe_grid()], [ofemt()]

Examples

  g <- make_ofe_grid(ofe_f2, x = "Treatment", cellsize = 9, min_per_cell = 4)
  plot_grid_selection(g, data = ofe_f2)
  plot(g, data = ofe_f2)          # same thing

  res <- ofemt(ofe_f2, y = "Yield_tn", x = "Treatment", cellsize = 9,
               keep_components = "full")
  plot(res)                        # grid + selection + points, no extra args

  # Base graphics instead, or a ggplot you keep customising
  plot(res, engine = "base")
  plot(res) + ggplot2::labs(subtitle = "Lote 2")

Plot histogram(s) of permutation p-values per comparison

Description

Produces one histogram per pairwise comparison showing the empirical distribution of permutation *p*-values across the 'n_s' sampling runs of an ['ofemt_result']. Two reference lines are drawn on each panel: a solid line at the **median** of the distribution — the value [ofemt()] reports for that comparison — and a dashed line at the significance threshold **alpha**.

Usage

plot_pvalue_hist(
  results,
  which = c("auto", "adjusted", "raw"),
  bins = 30,
  engine = c("ggplot2", "base")
)

Arguments

Value

With 'engine = "ggplot2"', a 'ggplot' object. With 'engine = "base"', invisibly 'NULL'.

Examples

  res <- ofemt(ofe_f2, y = "Yield_tn", x = "Treatment", cellsize = 9,
               p_adjust_method = "bonferroni")
  plot_pvalue_hist(res)              # adjusted p-values
  plot_pvalue_hist(res, which = "raw")
  plot_pvalue_hist(res, engine = "base")

Print method for 'ofemt_result' objects

Description

Displays a concise summary of an ['ofemt_result'] object, including general information about the experimental grid, descriptive statistics, and permutation-based test results.

Usage

## S3 method for class 'ofemt_result'
print(x, ...)

Arguments

Details

This print method provides a human-readable summary in the console:

• **General information:** Cell size, number of selected cells, and per-cell observation counts (minimum, median, maximum).

• **Spatial statistics:** Sample size ('n'), effective sample size ('ESS'), spatial correlation ('Rho'), and Moran’s *I*.

• **Means comparison:** Shows the first 10 rows of the table of comparisons between treatment means.

• **ANOVA permutation test:** Displays pairwise tests summarizing median *p*-values and corrected *p*-values across permutation runs.

If any of these components are missing, they are simply skipped in the printed output.

Value

Invisibly returns the input object 'x', unchanged.

Examples

  res <- ofemt(ofe_f2, y = "Yield_tn", x = "Treatment")
  print(res)

Quote a column name for use in a formula

Description

Column names coming from real field data routinely contain spaces, '+', accents or parentheses. Backticking them keeps [stats::as.formula()] happy without forcing the user to rename anything.

Usage

quote_name(nm)

Arguments

Value

Character scalar, the backtick-quoted name.

Sample without the 'sample()' length-one trap

Description

'sample(x, k)' treats a length-one numeric 'x' as '1:x'. This helper always samples *from the elements* of 'x'.

Usage

sample_values(x, size)

Arguments

Value

A vector of 'size' elements of 'x'.

Filter grid by minimum observations and minimum number of treatments

Description

Spatially joins points to the grid, counts observations and distinct treatments per cell, and keeps only cells that satisfy both thresholds.

Usage

select_grid(grid, data, x, min_per_cell = 1L, return_points = FALSE)

Arguments

Value

An 'ofe_grid' (list) with updated 'grid_sel' and 'params'. Adds:

• 'cell_stats': a data.frame with per-cell 'n_obs', 'n_trt', and 'treatments' list.

• 'points_sel' (optional): the points that fall in the selected cells.

Evaluate an expression muffling ‘spdep'’s connectivity notes

Description

'spdep' emits a warning whenever a neighbour object is not fully connected ('"neighbour object has N sub-graphs"'). For the cell-median point pattern used here that is expected and harmless: the weights matrix is built from every cell's nearest-neighbour distance, so disconnected components simply reflect the shape of the trial. Only the *absence* of neighbours is a real problem, and that is checked explicitly by the caller (see [nb_no_links()]).

Warnings that do not mention sub-graphs are left untouched.

Usage

without_subgraph_warnings(expr)

Arguments

Value

The value of 'expr'.