sim24ccfa21: Simulated CCFA data (dichotomous) with LD and a minor...
In LAWBL: Latent (Variable) Analysis with Bayesian Learning
sim24ccfa21 R Documentation
Simulated CCFA data (dichotomous) with LD and a minor factor/trait
Description
Categorical CFA data simulated based on 24 items, 4 factors, 2 categories
and local dependence; factorial correlation Φ=.3.
The last factor/trait is minor (measured by cross-loadings only).
Usage
sim24ccfa21
Format
A list with components:
datA dataset with simulated responses of 1000 individuals to 24 items
qlamLoading pattern and values used to simulated the data
LDLocal dependence between items (LD effect = .3)
LAWBL documentation built on May 16, 2022, 9:06 a.m.
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| sim24ccfa21 | R Documentation |
Simulated CCFA data (dichotomous) with LD and a minor factor/trait
Description
Categorical CFA data simulated based on 24 items, 4 factors, 2 categories and local dependence; factorial correlation Φ=.3. The last factor/trait is minor (measured by cross-loadings only).
Usage
sim24ccfa21
Format
A list with components:
datA dataset with simulated responses of 1000 individuals to 24 items
qlamLoading pattern and values used to simulated the data
LDLocal dependence between items (LD effect = .3)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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