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PyGrinder: a Python toolkit for grinding data beans into the incomplete for real-world data simulation by introducing missing values with different missingness patterns, including MCAR (complete at random), MAR (at random), MNAR (not at random), sub sequence missing, and block missing
Este estudio investiga la efectividad de la imputación múltiple en el análisis factorial confirmatorio (AFC) con datos de liderazgo, donde se simularon valores perdidos (MCAR) en un 40% de la muestra.