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, 2021 In this paper (Rubin, 2021), I consider two types of Type I error probability. The Neyman-Pearson Type I error rate refers to the maximum frequency of incorrectly rejecting a null hypothesis if a test was to be repeatedly reconducted on a series of different random samples that are all drawn from the exact same null population.
Mark Rubin
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Why Welchs test is Type I error robust [PDF]
Tutorials in Quantitative Methods for Psychology, 2016 The comparison of two means is one of the most commonly applied statistical procedures in psychology. The independent samples t-test corrected for unequal variances is commonly known as Welchs test, and is widely considered to be a robust alternative to
Derrick, B., White, P.
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Type I Error Control for Tree Classification [PDF]
Cancer Informatics, 2014 Binary tree classification has been useful for classifying the whole population based on the levels of outcome variable that is associated with chosen predictors.
Sin-Ho Jung, Yong Chen, Hongshik Ahn
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Type I error control for cluster randomized trials under varying small sample structures [PDF]
BMC Medical Research Methodology, 2021 Background Linear mixed models (LMM) are a common approach to analyzing data from cluster randomized trials (CRTs). Inference on parameters can be performed via Wald tests or likelihood ratio tests (LRT), but both approaches may give incorrect Type I ...
Joshua R. Nugent, Ken P. Kleinman
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Hypothesis testing, type I and type II errors
Industrial Psychiatry Journal, 2009 Hypothesis testing is an important activity of empirical research and evidence-based medicine. A well worked up hypothesis is half the answer to the research question.
Amitav Banerjee +4 more
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, 2022 Type-I error rates of tests for different values of K and n.
Kwun Chuen Gary Chan (3641947) +3 more
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Methods for nonparametric statistics in scientific research. Overview. Part 2
Теория и практика переработки мяса, 2022 The use of nonparametric methods in scientific research provides a number of advantages. The most important of these advantages are versatility and a wide range of such methods.
M. A. Nikitina, I. M. Chernukha
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Requirements for Minimum Sample Size for Sensitivity and Specificity Analysis [PDF]
Journal of Clinical and Diagnostic Research, 2016 Sensitivity and specificity analysis is commonly used for screening and diagnostic tests. The main issue researchers face is to determine the sufficient sample sizes that are related with screening and diagnostic studies. Although the formula for sample
Mohamad Adam Bujang, Tassha Hilda Adnan
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Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression [PDF]
PeerJ, 2016 Background Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for ...
Jeffrey A. Walker
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Type I error and power rates: A comparative analysis of techniques in differential item functioning
International Journal of Assessment Tools in Education, 2023 The main purpose of this study is to examine the Type I error and statistical power ratios of Differential Item Functioning (DIF) techniques based on different theories under different conditions.
Bayram Bıçak +1 more
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