parameter_mapping_functions: Parameter Mapping and Condition Processing Utilities

is_core_parameter_x_conditionR Documentation

Parameter Mapping and Condition Processing Utilities

Description

A set of helper functions for processing parameter mappings across experimental conditions. These functions are used internally for building the model Boolean array.

Usage

is_core_parameter_x_condition(parameter_map_r, factors_r)

is_parameter_x_condition(parameter_map_r, factors_r)

get_stimulus_level_r(parameter_map_r, factors_r, accumulators_r)

get_factor_cells_r(parameter_map_r, factors_r, accumulators_r)

Arguments

parameter_map_r

A named list mapping parameters to conditions and factors. Example structure: list(A = "1", B = "1", t0 = "1", mean_v = "M", sd_v = "1", st0 = "1") Where:

  • '1' indicates this parameter is constant across conditions

  • "M" indicates this parameter is associated with the internal matching factor. It changes depends on whether it is a match (i.e., correct) response or a mismatched (i.e., incorrect) response.

  • Other strings indicate factor dependencies

factors_r

A named list of experimental factors and their levels. Example: list(S = c("red", "blue"))

accumulators_r

A character vector of accumulator names. Example: c("r1", "r2")

Details

These functions work together to:

  • Analyse parameter mappings across experimental conditions

  • Identify which parameters vary by conditions

  • Generate appropriate stimulus levels and factor combinations

Value

is_core_parameter_x_condition

Logical vector indicating whether core parameters (before associating with any conditions) are factor-dependent

is_parameter_x_condition

Logical vector indicating whether parameters are factor-dependent

get_stimulus_level_r

Character vector of stimulus levels for each accumulator

get_factor_cells_r

List of factor combinations for each accumulator

Examples

p_map <- list(A = "1", B = "1", t0 = "1", mean_v = "M", sd_v = "1", st0 = "1")
factors <- list(S = c("red", "blue"))
accumulators <- c("r1", "r2")

# Check which parameters are core (not condition-dependent)
is_core_parameter_x_condition(p_map, factors)

# Get stimulus levels for each accumulator
get_stimulus_level_r(p_map, factors, accumulators)

ggdmcModel documentation built on Aug. 8, 2025, 7:50 p.m.