{'fraction_non_alphanumeric': 0.013289036544850499, 'fraction_numerical': 0.0, 'mean_word_length': 5.598540145985401, '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}}
Confounding and effect measure modification in reproductive medicine research.

The majority of research within reproductive and gynecologic health, or investigating ART, is observational in design. One of the most critical challenges for observational studies is confounding, while one of the most important for discovery and inference is effect modification. In this commentary, we explain what confounding and effect modification are and why they matter. We present examples illustrating how failing to adjust for a confounder leads to invalid conclusions, as well as examples where adjusting for a factor that is not a confounder also leads to invalid or imprecise conclusions. Careful consideration of which factors may act as confounders or modifiers of the association of interest is critical to conducting sound research, particularly with complex observational studies in reproductive medicine.