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Simulate Group TNA Network Objects

Source: R/simulate_tna_networks.R
simulate_group_tna_networks.Rd

Simulate group TNA network objects (fitted group_tna models) for simulation studies with grouped/clustered data. Each network contains multiple groups (e.g., classrooms, teams) with their own transition patterns.

Usage

simulate_group_tna_networks(
  n_groups = 5,
  n_actors = 10,
  n_states = 8,
  seq_length_range = c(10, 30),
  use_learning_states = TRUE,
  categories = NULL,
  seed = NULL,
  verbose = TRUE,
  actors_per_group = NULL,
  min_seq_length = NULL,
  max_seq_length = NULL,
  learning_categories = NULL,
  ...
)

generate_group_tna_networks(...)

Arguments

n_groups

Integer. Number of groups in the network. Default: 5.

n_actors

Integer or integer vector. Number of actors per group. Accepts: single integer (fixed size), two integers like c(8, 12) (min/max), or a range like 5:15 (min/max taken from range). Default: 10.

n_states

Integer. Number of states/actions in the network. Default: 5.

seq_length_range

Integer vector of length 2. Range for sequence lengths per actor (min, max). Default: c(10, 30).

use_learning_states

Logical. If TRUE, uses learning action verbs as state names. Default: TRUE.

categories

Character vector or NULL. Which categories of learning verbs to use. Options: "metacognitive", "cognitive", "behavioral", "social", "motivational", "affective", "group_regulation", or "all". If NULL (default), randomly selects one category.

seed

Integer or NULL. Random seed for reproducibility. Default: NULL.

verbose

Logical. If TRUE, prints progress messages. Default: TRUE.

actors_per_group

Deprecated. Use n_actors instead.

min_seq_length

Deprecated. Use seq_length_range instead.

max_seq_length

Deprecated. Use seq_length_range instead.

learning_categories

Deprecated. Use categories instead.

...

Arguments passed to simulate_group_tna_networks.

Value

A group_tna model object (class "group_tna") containing:

networks

List of TNA networks, one per group

data

The underlying wide-format data

group

The grouping variable name

Details

This function generates a single group TNA network with multiple groups. It simulates long-format sequence data with group structure, converts it to wide format, and fits a group TNA model using tna::group_model().

Use Cases:

  • Simulating classroom-level learning behavior data

  • Generating team collaboration sequences

  • Creating multi-group datasets for method comparison

See also

simulate_tna_networks for individual TNA models, simulate_long_data for generating long-format group data, fit_network_model for model fitting.

Examples

if (FALSE) { # \dontrun{
# Generate a group TNA network with 4 groups, 15 actors each
group_net <- simulate_group_tna_networks(
  n_groups = 4,
  n_actors = 15,
  n_states = 5,
  seed = 42
)

# Variable group sizes using range notation
var_net <- simulate_group_tna_networks(
  n_groups = 5,
  n_actors = c(8, 15),
  seq_length_range = c(5, 25),
  seed = 123
)

# With specific learning category
ssrl_net <- simulate_group_tna_networks(
  n_groups = 6,
  n_actors = c(10, 20),
  categories = "group_regulation",
  seed = 456
)

# Access individual group networks
names(group_net)
group_net[[1]]$weights

# Old parameter names still work
group_net <- simulate_group_tna_networks(
  actors_per_group = 10,
  min_seq_length = 5,
  max_seq_length = 20,
  seed = 42
)
} # }