{'fraction_non_alphanumeric': 0.02269170579029734, 'fraction_numerical': 0.014084507042253521, 'mean_word_length': 5.49238578680203, '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}}
Simulation study comparing interval estimates for the recombination fraction

Three interval estimation procedures were evaluated to determine the method which provides the most accurate estimates for the recombination fraction, θ. The lod–0.83 support interval, the jackknife confidence interval, and the confidence interval based on estimated asymptotic standard error were compared by calculating the coverage probabilities of each. Family data that were simulated under the model of a single fully penetrant, dominant disease locus at some distance, θ, from fully informative matings were used. Comparisons were based on 1,000 random samples of size 20, 60, and 100 families. In addition, a methodology for obtaining prediction intervals for θ was developed. This procedure is of practical use and does not require asymptotic assumptions based on large sample theory. The results provide an a priori idea about precision of the estimates, as well as empirical interval estimates of θ. Graphs of the authors' Monte Carlo intervals are presented for these simulations. Investigators studying different traits, however, could condition specifically on the family structure and distribution of the disease they are investigating and obtain similar graphs. ©1995 Wiley‐Liss, Inc.