Generate a Publication-Ready Table from an ERGM Object

S3 generic that dispatches to methods for fitted ergm objects or plain formula objects, calling the internal parsing engine and returning a formatted table.

Usage

tabulergm_table(object, ...)

# S3 method for class 'ergm'
tabulergm_table(
  object,
  include_description = FALSE,
  include_math = FALSE,
  include_attribute = FALSE,
  include_title = FALSE,
  format = c("data.frame", "html", "markdown"),
  figures_dir = NULL,
  override = NULL,
  override.title = NULL,
  override.desc = NULL,
  override.math = NULL,
  override.figure = NULL,
  override.citation = NULL,
  ...
)

# S3 method for class 'formula'
tabulergm_table(
  object,
  format = c("data.frame", "html", "markdown"),
  figures_dir = NULL,
  directed = NULL,
  include_title = FALSE,
  override = NULL,
  override.title = NULL,
  override.desc = NULL,
  override.math = NULL,
  override.figure = NULL,
  override.citation = NULL,
  ...
)

Arguments

object: A fitted ergm object or an ERGM formula.
...: Additional arguments passed to methods.
include_description: Logical. Include the term description column? Default FALSE.
include_math: Logical. Include the mathematical notation column? Default FALSE.
include_attribute: Logical. Include the attribute column? Default FALSE.
include_title: Logical. Include the short term-title column? Default FALSE.
format: Character. Output format: "data.frame" (default), "html", or "markdown". HTML and Markdown output require the knitr package.
figures_dir: Optional directory for figure assets when format = "markdown". When NULL, figures are copied automatically to the active knitr/Quarto/R Markdown figure path during non-interactive document rendering.
override: A named list keyed by term name, each element a named list of fields to replace, e.g. list(edges = list(title = "Density", citation = "doi:10.1234/x")). Valid fields are title, description (or desc), math, figure, and citation.
override.title, override.desc, override.math, override.figure: Named character vectors keyed by term name, e.g. override.title = c(edges = "Density"). These take precedence over override.
override.citation: A named list keyed by term name whose elements are citation specifications in the same form the YAML citation: field accepts: a bare key ("hunter2007"), a prefixed identifier ("doi:10.1016/j.socnet.2006.08.002"), a single entry list (list(key = "hunter2007", doi = "10.1016/j.socnet.2006.08.002")), or a list of such entries.
directed: Logical or NULL. Whether the network is directed. Passed to parse_ergm_formula(); when NULL (the default), directedness is inferred from the network on the left-hand side of the formula when possible.

Value

A data.frame (default), or a knitr_kable object when format is "html" or "markdown". When the term figures use drawing conventions (orange for focal attributes, orange/teal for mixing, squares/circles for bipartite modes), an explanatory note is appended below "html" and "markdown" tables. Terms carrying a citation get a (key) marker next to their description, and the matching [key] identifier lines are appended below the table.

Methods (by class)

tabulergm_table(ergm): Method for fitted ergm objects.

Calls parse_ergm_model() and returns a table with default columns term, figure, estimate, se, and pvalue. Optional columns (title, description, math, attribute) can be included via logical arguments. The title column, when included, is placed immediately after term.
tabulergm_table(formula): Method for formula objects.

Calls parse_ergm_formula() and returns a table with columns term, figure, math, and description. Coefficient statistics are excluded because no fitted model is available.

Examples

library(ergm)
fit <- readRDS(system.file("fits", "fit_edges.rds", package = "tabulergm"))
tabulergm_table(fit)
#> Warning: This object was fit with ‘ergm’ version 4.9.0 or earlier. Summarizing it with version 4.10 or later may return incorrect results or fail.
#>    term
#> 1 edges
#>                                                                                                         figure
#> 1 /tmp/RtmpQpSy5d/tabulergm-83bf88159c17a513202a912d589a0254-b6f3c9a3a81099857159db04549de0da-4-undirected.png
#>     estimate        se     pvalue
#> 1 -0.6931472 0.3162272 0.02838474
tabulergm_table(fit, include_description = TRUE)
#> Warning: This object was fit with ‘ergm’ version 4.9.0 or earlier. Summarizing it with version 4.10 or later may return incorrect results or fail.
#>    term
#> 1 edges
#>                                                                                                         figure
#> 1 /tmp/RtmpQpSy5d/tabulergm-83bf88159c17a513202a912d589a0254-b6f3c9a3a81099857159db04549de0da-4-undirected.png
#>     estimate        se     pvalue
#> 1 -0.6931472 0.3162272 0.02838474
#>                                                                                                                             description
#> 1 Counts the ties present in the network. Acts as the baseline density term, playing the role an intercept plays in a regression model.
tabulergm_table(fit, format = "markdown")
#> Warning: This object was fit with ‘ergm’ version 4.9.0 or earlier. Summarizing it with version 4.10 or later may return incorrect results or fail.
#> 
#> 
#> |term  |figure                                                                                                                        |   estimate|        se|    pvalue|
#> |:-----|:-----------------------------------------------------------------------------------------------------------------------------|----------:|---------:|---------:|
#> |edges |![](/tmp/RtmpQpSy5d/tabulergm-83bf88159c17a513202a912d589a0254-b6f3c9a3a81099857159db04549de0da-4-undirected.png){width=80px} | -0.6931472| 0.3162272| 0.0283847|

# Replace the shipped title and description for one term
tabulergm_table(
  fit,
  include_title = TRUE,
  include_description = TRUE,
  override.title = c(edges = "Density"),
  override.desc  = c(edges = "Baseline propensity to form ties.")
)
#> Warning: This object was fit with ‘ergm’ version 4.9.0 or earlier. Summarizing it with version 4.10 or later may return incorrect results or fail.
#>    term   title
#> 1 edges Density
#>                                                                                                         figure
#> 1 /tmp/RtmpQpSy5d/tabulergm-83bf88159c17a513202a912d589a0254-b6f3c9a3a81099857159db04549de0da-4-undirected.png
#>     estimate        se     pvalue                       description
#> 1 -0.6931472 0.3162272 0.02838474 Baseline propensity to form ties.
library(ergm)
tabulergm_table(network ~ edges + nodematch("gender"))
#>        term
#> 1     edges
#> 2 nodematch
#>                                                                                                         figure
#> 1 /tmp/RtmpQpSy5d/tabulergm-83bf88159c17a513202a912d589a0254-b6f3c9a3a81099857159db04549de0da-4-undirected.png
#> 2 /tmp/RtmpQpSy5d/tabulergm-a673ab51cffbb0c78cac452d4b806b45-b6f3c9a3a81099857159db04549de0da-4-undirected.png
#>                                        math
#> 1                        \\sum_{i<j} y_{ij}
#> 2 \\sum_{i<j} y_{ij} \\mathbf{1}(x_i = x_j)
#>                                                                                                                                                                                                                   description
#> 1                                                                                       Counts the ties present in the network. Acts as the baseline density term, playing the role an intercept plays in a regression model.
#> 2 Counts the ties joining nodes that share the same value of a categorical attribute, the standard measure of homophily. Setting diff = TRUE adds one statistic per attribute value (differential homophily). (mcpherson2001)

Generate a Publication-Ready Table from an ERGM Object

Usage

Arguments

Value

Methods (by class)

See also

Examples