add_method_factors: Adds Methods Factors to 'simulate_factors' Data

In latentFactoR: Data Simulation Based on Latent Factors

Adds Methods Factors to simulate_factors Data

Description

Adds methods factors to simulated data from simulate_factors. See examples to get started

Usage

add_method_factors(
  lf_object,
  proportion_negative = 0.5,
  proportion_negative_range = NULL,
  methods_factors,
  methods_loadings,
  methods_loadings_range = 0,
  methods_correlations,
  methods_correlations_range = NULL
)

Arguments

lf_object	Data object from simulate_factors. Data must be categorical. If data are not categorical, then there function with throw an error
proportion_negative	Numeric (length = 1 or factors). Proportion of variables that should have negative (or flipped) dominant loadings across all or each factor. Accepts number of variables as well. The first variables on each factor, up to the corresponding proportion, will be flipped. Set to 0 to not have any loadings flipped. Defaults to 0.50
proportion_negative_range	Numeric (length = 2). Range of proportion of variables that are randomly selected from a uniform distribution. Accepts number of number of variables as well. Defaults to NULL
methods_factors	Numeric
methods_loadings	Numeric
methods_loadings_range	Numeric
methods_correlations	Numeric
methods_correlations_range	Numeric

Value

Returns a list containing:

data	Biased data simulated data from the specified factor model
unbiased_data	The corresponding unbiased data prior to replacing values to generate the (biased) data
parameters	Bias-adjusted parameters of the lf_object input into function
original_results	Original lf_object input into function

Author(s)

Alexander P. Christensen <[e-mail]>, Luis Eduardo Garrido <[e-mail]>

References

Garcia-Pardina, A., Abad, F. J., Christensen, A. P., Golino, H., & Garrido, L. E. (2024). Dimensionality assessment in the presence of wording effects: A network psychometric and factorial approach. Behavior Research Methods.

Examples

# Generate factor data
two_factor <- simulate_factors(
  factors = 2, # factors = 2
  variables = 6, # variables per factor = 6
  loadings = 0.55, # loadings between = 0.45 to 0.65
  cross_loadings = 0.05, # cross-loadings N(0, 0.05)
  correlations = 0.30, # correlation between factors = 0.30
  sample_size = 1000, # number of cases = 1000
  variable_categories = 5 # 5-point Likert scale
)

# Add methods factors
two_factor_methods_effect <- add_method_factors(
  lf_object = two_factor,
  proportion_negative = 0.50,
  methods_loadings = 0.20,
  methods_loadings_range = 0.10
)

latentFactoR documentation built on May 29, 2024, 3:02 a.m.