{'fraction_non_alphanumeric': 0.024390243902439025, 'fraction_numerical': 0.0, 'mean_word_length': 4.868131868131868, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Exploratory Factor Analysis (EFA) Programs in R

We provide a brief overview of two R packages that can conduct exploratory factor analysis (EFA): psych and EFAutilities. After introducing EFA and the exemplar data used in this paper we discuss best practices for EFA. Next, we describe the approaches used in the two packages for EFA. During this explanation, we provide sample code and discuss the usage and results of two empirical datasets. Finally, we highlight the similarities and distinctions of each package on modeling EFA.