2015
DOI: 10.1097/bsd.0000000000000285
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Type I, Type II, and Occasionally Type III

Abstract: An important part of planning a study is deciding what risk of drawing incorrect conclusions is acceptable. Type I error occurs when a study draws a false-positive conclusion. A false negative, not appreciating a difference when one exists, is known as type II error. This article reviews the difference between the 2 common types of error and discusses conventions used to set acceptable error levels.

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Cited by 4 publications
(5 citation statements)
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“…Sample size is another important feature that must always be evaluated. An inadequate number of participants in a study may contribute to errors during the detection of group differences [53]. Among all TMS studies included in the current systematic review, Galhardoni et al, 2014 [30] had the largest sample 33 participants), while Lindholm et al, 2015 [34]; 2016 [33] had the smallest.…”
Section: Discussionmentioning
confidence: 99%
“…Sample size is another important feature that must always be evaluated. An inadequate number of participants in a study may contribute to errors during the detection of group differences [53]. Among all TMS studies included in the current systematic review, Galhardoni et al, 2014 [30] had the largest sample 33 participants), while Lindholm et al, 2015 [34]; 2016 [33] had the smallest.…”
Section: Discussionmentioning
confidence: 99%
“…55 Type III error occurs when the null hypothesis is correctly rejected but for the wrong reason. 55…”
Section: Power and Sample Size Calculationsmentioning
confidence: 99%
“…Type I error, or α error, is the probability of rejecting the null hypothesis when the null hypothesis is correct (rejection error). 55 The type II error of β error is the probability of failing to reject the null hypothesis when the alternative hypothesis is correct (acceptance or failure to reject error). 55 Type III error occurs when the null hypothesis is correctly rejected but for the wrong reason.…”
Section: Study Design and Statistical Considerationsmentioning
confidence: 99%
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“…Furthermore, the interpretation of the superiority of any shorter combination of items as evidence of selective anosmia could represent an example of error type 3: to get the right answer to the wrong question (85,86). Although our data, as well as Hawkes and Shephard(21) and others (3,(22)(23)(24)(25)27) correctly reject the null hypothesis that all items on the test are the same, they do not prove that the difference between items is due to selective anosmia to the odors presented.…”
Section: Discussionmentioning
confidence: 99%