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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.

Cet exercice fait partie du cours

Factor Analysis in R

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Instructions

  • 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.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# 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[___, ]
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