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Equivalent statistics and data interpretation [PDF]
Behavior Research Methods, 2016 Recent reform efforts in psychological science have led to a plethora of choices for scientists to analyze their data. A scientist making an inference about their data must now decide whether to report a p value, summarize the data with a standardized effect size and its confidence interval, report a Bayes Factor, or use other model comparison methods.
openaire +3 more sources
Common pitfalls in statistical analysis: Clinical versus statistical significance
Perspectives in Clinical Research, 2015 In clinical research, study results, which are statistically significant are often interpreted as being clinically important. While statistical significance indicates the reliability of the study results, clinical significance reflects its impact on ...
Priya Ranganathan +2 more
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Nonparametric statistical tests for the continuous data: the basic concept and the practical use [PDF]
Korean Journal of Anesthesiology, 2016 Conventional statistical tests are usually called parametric tests. Parametric tests are used more frequently than nonparametric tests in many medical articles, because most of the medical researchers are familiar with and the statistical software ...
Francis Sahngun Nahm
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Common pitfalls in statistical analysis: The perils of multiple testing
Perspectives in Clinical Research, 2016 Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple subgroups or for multiple end-points. This amplifies the probability of a false-positive finding.
Priya Ranganathan +2 more
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Testing Linear Regressions by StatsModel Library of Python for Oceanological Data Interpretation
AQUATIC SCIENCES AND ENGINEERING, 2019 The study area is focused on the Mariana Trench, west Pacific Ocean. The research aim is to investigate correlation between various factors, such as bathymetric depths, geomorphic shape, geographic location on four tectonic plates of the sampling points ...
Polina Lemenkova
semanticscholar +1 more source
Interpretation and identification of within-unit and cross-sectional variation in panel data models
PLoS ONE, 2020 While fixed effects (FE) models are often employed to address potential omitted variables, we argue that these models’ real utility is in isolating a particular dimension of variance from panel data for analysis.
J. Kropko, R. Kubinec
semanticscholar +1 more source
Frontiers in Neurology, 2017 We present the first quantitative analysis of atypical teratoid rhabdoid tumors (ATRT) in adults, including two patients from our own institutions. These are of interest as one occurred during pregnancy and one is a long-term survivor.
Christopher Dardis +13 more
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Data transformation: a focus on the interpretation
Korean Journal of Anesthesiology, 2020 Several assumptions such as normality, linear relationship, and homoscedasticity are frequently required in parametric statistical analysis methods. Data collected from the clinical situation or experiments often violate these assumptions.
Dong Kyu Lee
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Is the Bland-Altman plot method useful without inferences for accuracy, precision, and agreement? [PDF]
Revista de Saúde PúblicaOBJECTIVE This study aims to propose a comprehensive alternative to the Bland-Altman plot method, addressing its limitations and providing a statistical framework for evaluating the equivalences of measurement techniques.
Paulo Sergio Panse Silveira +2 more
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Interpretation of omics data analyses
Journal of Human Genetics, 2020 Omics studies attempt to extract meaningful messages from large-scale and high-dimensional data sets by treating the data sets as a whole. The concept of treating data sets as a whole is important in every step of the data-handling procedures: the pre ...
Ryo Yamada +4 more
semanticscholar +1 more source