Alpha Risk

(redirected from Type 1 error)

Alpha Risk

When testing a hypothesis, the risk of rejecting a piece of data that should have been accepted. Many tests reject some data as unusable or irrelevant. Alpha risk is the probability that the wrong data will be eliminated from the sample. It is also called type I error or alpha error. See also: Beta risk.
Mentioned in ?
References in periodicals archive ?
In the absence of outliers the mean estimate and type 1 error of the two parameters were acceptable for all three models; however, the empirical standard error was much larger than the asymptotic standard error for the classical and semi-parametric models while these two types of standard error were similar in magnitude in the rank regression model.
In lending, correspondingly, a Type 1 error would be rejecting a good loan, while a Type 2 error would be writing a bad loan, the economist said.
For example, a Type II error rate of 15 percent is associated with a Type 1 error rate of 21 percent in 1996, while Type I error rates of more than 21 percent are associated with a 15 percent Type II error rate for the years 1997-2004.
This result should be interpreted cautiously as the type 1 error in this study is huge.
If prophylactic use of B1 eventually turns into a type 1 error, little will have been lost in such a failed experiment.
If we conclude from the results of a trial that 2 therapies are of different effectiveness, when in reality they are the same, we have committed what is known as a type 1 error. The probability of making a type 1 error is termed the alpha.
Additional threats to validity resulted from use of the .10 alpha level and three pairwise comparisons, which elevated the probability of Type 1 error, i.e., the possibility that the observed differences resulted from chance.
The probability of rejecting the null hypothesis when it is true is called type 1 error or alpha ([alpha]) or level of statistical significance.
However, Lee and Gurland (1977) showed analytically that the Type 1 error rate of the one-sample t-test may differ greatly when sampling from distributions which have the same skewness and kurtosis.
FAST Factor 5 0.721 [***] Cash Flow Factor 1 0.937 [***] Cash Flow Factor 2 -0.591 [***] Log L -90.3 -94.7 Psuedo [R.sup.2] 27% 23% Type 1 Error Rates (%) Total Individual FAST FAST Type II Error Rates RBC RBC score Factors 5 Percent 89 68 52 64 10 Percent 66 52 45 36 15 Percent 50 48 39 32 20 Percent 39 39 34 27 25 Percent 27 30 25 25 30 Percent 25 25 23 14 Consistent Cash Flow Type II Error Rates FAST Factors Factors 5 Percent 66 55 10 Percent 57 48 15 Percent 41 41 20 Percent 36 36 25 Percent 30 27 30 Percent 30 27 Note: 244 Solvent Companies, 44 Insolvent Companies.
In this task, the error scores are calculated by combining type 1 (when the participant completes the sentence with a word somewhat related to the target word) and type 3 errors (when the individual produces a word that fits the sentence when instructed to produce a word irrelevant to the sentence context) following the classical procedure of giving 1 point to type 1 errors and 3 points to type 3 errors (Burgess & Shallice, 1996).