Introductory statistics students learn that hypothesis tests in­ volve two types of error. If we reject a true null hypothesis, a Type I error occurs. If we fail to reject a false null hypothesis, a Type II error occurs. Students become adept at using tables to find critical values that control the probability of a Type I error. However, the calculations needed to control the probabil­ ity of a...

spinal muscular atrophy (sma) is an autosomal recessive neuromuscular disorder caused by homozygous deletion of the survival motor neuron gene 1 (smn1) in more than 90% of patients. according to the age of onset and severity of the disease, sma is classified into three groups: type i (severe), type ii (intermediate) and type iii (mild). as reported, the smn2 gene, centromeric copy gene, showed ...

BACKGROUND Power for assessing interactions during data analysis is often poor in epidemiologic studies. This is because epidemiologic studies are frequently powered primarily to assess main effects only. In light of this, some investigators raise the Type I error rate, thereby increasing power, when testing interactions. However, this is a poor analysis strategy if the study is chronically und...

introduction: idiopathic pulmonary fibrosis (ipf) is a relentlessly progressive and usually fatal lung disease of unknown etiology for which no effective treatments currently exist. in the adults type i and ii pneumocytes, forms components of the alveolar epithelial cells. in this study, we investigated the effect of thalidomide on the alveolar epithelial cells (type i and ii pneumocytes) in th...

BACKGROUND Short scales are typically used in the social, behavioural and health sciences. This is relevant since test length can influence whether items showing DIF are correctly flagged. This paper compares the relative effectiveness of discriminant logistic regression (DLR) and IRTLRDIF for detecting DIF in polytomous short tests. METHOD A simulation study was designed. Test length, sample...

in this paper a novel process monitoring scheme for reducing the type і and type іі error rates in the monitoring phase is proposed. first, the proposed approach uses an augmented data matrix to implement the process dynamic. then, we apply independent component analysis (ica) transformation to the augmented data matrix, and eliminate the outliers using the local outlier factor (lof) algorithm....

Pattern classification seeks to minimize error of unknown patterns, however, in many real world applications, type I (false positive) and type II (false negative) errors have to be dealt with separately, which is a complex problem since an attempt to minimize one of them usually makes the other grow. Actually, a type of error can be more important than the other, and a trade-off that minimizes ...