Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research. [PDF]
Neuron, 2022 In basic neuroscience research, data are often clustered or collected with repeated measures, hence correlated. The most widely used methods such as t test and ANOVA do not take data dependence into account and thus are often misused.
Yu Z +5 more
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A tutorial on using the paired t test for power calculations in repeated measures ANOVA with interactions. [PDF]
Behav Res Methods, 2023 The a priori calculation of statistical power has become common practice in behavioral and social sciences to calculate the necessary sample size for detecting an expected effect size with a certain probability (i.e., power).
Langenberg B +4 more
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Attach importance of the bootstrap t test against Student's t test in clinical epidemiology: a demonstrative comparison using COVID-19 as an example. [PDF]
Epidemiol Infect, 2021 Student's t test is valid for statistical inference under the normality assumption or asymptotically. By contrast, although the bootstrap t test was proposed in 1993, it is seldom adopted in medical research.
Zhao S +7 more
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Sample-size determination for the Bayesian t test and Welch's test using the approximate adjusted fractional Bayes factor. [PDF]
Behav Res Methods, 2021 When two independent means μ1 and μ2 are compared, H0 : μ1 = μ2, H1 : μ1≠μ2, and H2 : μ1 > μ2 are the hypotheses of interest. This paper introduces the R package SSDbain, which can be used to determine the sample size needed to evaluate these hypotheses ...
Fu Q, Hoijtink H, Moerbeek M.
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Analysis of Bayesian posterior significance and effect size indices for the two-sample t-test to support reproducible medical research. [PDF]
BMC Med Res Methodol, 2020 Background The replication crisis hit the medical sciences about a decade ago, but today still most of the flaws inherent in null hypothesis significance testing (NHST) have not been solved.
Kelter R.
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Application of student's t-test, analysis of variance, and covariance. [PDF]
Ann Card Anaesth, 2019 Student's t test (t test), analysis of variance (ANOVA), and analysis of covariance (ANCOVA) are statistical methods used in the testing of hypothesis for comparison of means between the groups.
Mishra P +4 more
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More about the basic assumptions of t-test: normality and sample size. [PDF]
Korean J Anesthesiol, 2019 Most parametric tests start with the basic assumption on the distribution of populations. The conditions required to conduct the t-test include the measured values in ratio scale or interval scale, simple random extraction, normal distribution of data ...
Kim TK, Park JH.
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T test as a parametric statistic. [PDF]
Korean J Anesthesiol, 2015 In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ2) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ2/n).
Kim TK.
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Analysis of t-test misuses and SPSS operations in medical research papers. [PDF]
Burns Trauma, 2019 In medical research papers, the selection of appropriate statistical methods serves as one of the pivotal premises to ensure the quality of papers and credibility of their results [1–3]. To correctly perform the statistical analysis of quantitative data,
Liang G, Fu W, Wang K.
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Statistical notes for clinical researchers: the independent samples t-test. [PDF]
Restor Dent Endod, 2019 https://rde.ac The t-test is frequently used in comparing 2 group means. The compared groups may be independent to each other such as men and women. Otherwise, compared data are correlated in a case such as comparison of blood pressure levels from the ...
Kim HY.
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