دانلود مقاله ISI انگلیسی شماره 132743
ترجمه فارسی عنوان مقاله

مثبت کاذب و سایر خطاهای آماری در تحلیل استاندارد حرکات چشم در خواندن

عنوان انگلیسی
False positives and other statistical errors in standard analyses of eye movements in reading
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
132743 2017 15 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Memory and Language, Volume 94, June 2017, Pages 119-133

ترجمه کلمات کلیدی
آمار، مثبت کاذب، تست فرضیه صفر، ردیابی چشم، خواندن، پردازش احکام،
کلمات کلیدی انگلیسی
Statistics; False positives; Null-hypothesis testing; Eye-tracking; Reading; Sentence processing;
پیش نمایش مقاله
پیش نمایش مقاله  مثبت کاذب و سایر خطاهای آماری در تحلیل استاندارد حرکات چشم در خواندن

چکیده انگلیسی

In research on eye movements in reading, it is common to analyze a number of canonical dependent measures to study how the effects of a manipulation unfold over time. Although this gives rise to the well-known multiple comparisons problem, i.e. an inflated probability that the null hypothesis is incorrectly rejected (Type I error), it is accepted standard practice not to apply any correction procedures. Instead, there appears to be a widespread belief that corrections are not necessary because the increase in false positives is too small to matter. To our knowledge, no formal argument has ever been presented to justify this assumption. Here, we report a computational investigation of this issue using Monte Carlo simulations. Our results show that, contrary to conventional wisdom, false positives are increased to unacceptable levels when no corrections are applied. Our simulations also show that counter-measures like the Bonferroni correction keep false positives in check while reducing statistical power only moderately. Hence, there is little reason why such corrections should not be made a standard requirement. Further, we discuss three statistical illusions that can arise when statistical power is low, and we show how power can be improved to prevent these illusions. In sum, our work renders a detailed picture of the various types of statistical errors than can occur in studies of reading behavior and we provide concrete guidance about how these errors can be avoided.