{'fraction_non_alphanumeric': 0.0327613104524181, 'fraction_numerical': 0.0124804992199688, 'mean_word_length': 5.551020408163265, '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}}
The Urry Method of Approximating the Item Parameters of Latent Trait Theory

This note demonstrates that the convenient and inexpensive procedure suggested by Urry (1974a) for approximating test models (i.e., the normal ogive and logistic models) tends to systematically underestimate ai (item discriminatory power) and overestimate /b i/ (item difficulty). A simple correction for error in estimated ability (θ) is presented which serves to eliminate these biases. Implications for item screening and for item parameterization via maximum likelihood methods and via Urry's more recently developed estimation procedure (1974b) are discussed.