Statistical Analysis: An Integral Part of Clinical Research Practices

1987 ◽  
Vol 5 (4) ◽  
pp. 231-244
Author(s):  
Eucharia Nnadi Okolo
2021 ◽  
Vol 41 (7) ◽  
pp. 609-613
Author(s):  
Masato HIRABAYASHI ◽  
Katsushi DOI ◽  
Noritaka IMAMACHI ◽  
Tomomune KISHIMOTO ◽  
Yoji SAITO

2020 ◽  
Author(s):  
Kyoshiro Sasaki ◽  
Yuki Yamada

A Registered Reports system is key to preventing questionable research practices. Under this system, manuscripts, including their detailed protocols (i.e., hypothesis, experimental design, sample size, and methods of statistical analysis), are reviewed prior to data collection. If a protocol manuscript is accepted, publication of the full manuscript including the results and discussion is guaranteed in principle regardless of whether the collected data support the registered hypothesis. However, this assurance of publication might be broken under the impact of the COVID-19 pandemic. The present paper reports the first author’s real-life experience related to the collapse of the assurance of publication in the Registered Reports system and discusses the disbenefits of this collapse. Furthermore, we propose the implementation of a journal section specific to protocol manuscripts as a solution to the crisis of the Registered Reports system.


Cephalalgia ◽  
1993 ◽  
Vol 13 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Jürgen Michael Klotz

After almost 40 years of research on EEG computer analysis, present clinical applications of this method remain limited. At the present time, EEG mapping is suited primarily for research. Despite the pitfalls of an uncritical application of EEG mapping, progress in clinical research made possible by EEG mapping techniques has been considerable. Some problems of data acquisition, display and statistical analysis are discussed in this paper. For headache research examination of the activated EEG, especially with photic stimulation, has greater diagnostic importance than mapping under resting conditions.


1989 ◽  
Vol 2 (1) ◽  
pp. 34-40
Author(s):  
Lee Baer ◽  
David K. Ahern

2020 ◽  
Vol 183 (3) ◽  
pp. E3-E5
Author(s):  
Rolf H H Groenwold ◽  
Olaf M Dekkers

The validity of any biomedical study is potentially affected by measurement error or misclassification. It can affect different variables included in a statistical analysis, such as the exposure, the outcome, and confounders, and can result in an overestimation as well as in an underestimation of the relation under investigation. We discuss various aspects of measurement error and argue that often an in-depth discussion is needed to appropriately assess the quality and validity of a study.


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