add_method_factors {latentFactoR} | R Documentation |
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 |
proportion_negative |
Numeric (length = 1 or |
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 |
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) |
parameters |
Bias-adjusted parameters of the |
original_results |
Original |
Author(s)
Alexander P. Christensen <alexpaulchristensen@gmail.com>, Luis Eduardo Garrido <luisgarrido@pucmm.edu>
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
)