Results 51 to 60 of about 30,603,790 (296)

Type I error rates in the first set of simulations.

, 2022
Type I error rates in the first set of simulations.
Rui Chen (95310), Ran Tao (81449), Quan Wang (31224), Qiang Wei (187077), Ying Ji (285782), Bingshan Li (174021)   +5 more
core   +1 more source

Enteropathogenic E. coli shows delayed attachment and host response in human jejunum organoid‐derived monolayers compared to HeLa cells

FEBS Letters, EarlyView.
Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi, Pilar Samperio Ventayol, Natalie Burkard, Nicolas Schlegel, Carmen Aguilar, Sina Bartfeld   +5 more
wiley   +1 more source

Type I error for the five approaches.

, 2013
Type I error for the five approaches.
Yen-Feng Chiu (73688), Yao-Hwei Fang (442743)   +1 more
core   +1 more source

Power and type I error comparison for cluster poisson data.

, 2022
Power and type I error comparison for cluster poisson data.
Mike M. O’Shea (12867295), Fei Zou (188420), James G. Xenakis (12867292), Rebecca C. Fry (36658), Baiming Zou (12867289), Hudson P. Santos (6903485)   +5 more
core   +1 more source

Diversity and complexity in neural organoids

FEBS Letters, EarlyView.
Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley   +1 more source

An open-source software program for performing Bonferroni and related corrections for multiple comparisons

Journal of Pathology Informatics, 2011
Increased type I error resulting from multiple statistical comparisons remains a common problem in the scientific literature. This may result in the reporting and promulgation of spurious findings.
Kyle Lesack, Christopher Naugler
doaj   +1 more source

The type I error rate estimations.

, 2015
The type I error rate estimations.
Lizhen Xu (677402), Williams Turpin (320798), Andrew D. Paterson (135194), Wei Xu (28953)   +3 more
core   +1 more source

The human gut microbiome across the life course

FEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero, Basak Bahcivanci, Antonietta Hayhoe, Animesh Acharjee, Ezgi Özkurt   +4 more
wiley   +1 more source

Primary outcomes, secondary outcomes, and their relevance to how many papers are published from a study: A primer for authors, reviewers, and editors

Indian Journal of Psychiatry
In research, outcomes are often categorized as primary and secondary. The primary outcome is the most important one; it determines whether the study is considered ‘successful’ or not. Secondary outcomes are chosen because they provide supporting evidence
Vikas Menon, Samir Kumar Praharaj, Chittaranjan Andrade   +2 more
doaj   +1 more source

Erratum regarding “Optimizing effective numbers of tests by vine copula modeling”

Dependence Modeling, 2020
We correct the definition of the family-wise error rate in our previous article “Optimizing effective numbers of tests by vine copula modeling”.
Steffen Nico, Dickhaus Thorsten
doaj   +1 more source