Splitting your dataset
During the measure development process, it's important to conduct EFA and CFA on separate datasets because using the same dataset can lead to inflated model fit statistics. Instead, you can split your dataset in half, then use one half for the EFA and the other half for the CFA.
Deze oefening maakt deel uit van de cursus
Factor Analysis in R
Oefeninstructies
- Split the dataset in half using two sets of indices to determine which rows belong to each dataset.
- Use the first set of indices to create a dataset for your EFA, then use the second set for your CFA dataset.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Establish two sets of indices to split the dataset
N <- nrow(gcbs)
indices <- seq(1, ___)
indices_EFA <- sample(indices, floor((.5*___)))
indices_CFA <- indices[!(indices %in% ___)]
# Use those indices to split the dataset into halves for your EFA and CFA
gcbs_EFA <- gcbs[___, ]
gcbs_CFA <- gcbs[___, ]