Selected Topics in Statistical Analysis of Clinical Research

1989 ◽  
Vol 2 (1) ◽  
pp. 34-40
Author(s):  
Lee Baer ◽  
David K. Ahern
2021 ◽  
Vol 41 (7) ◽  
pp. 609-613
Author(s):  
Masato HIRABAYASHI ◽  
Katsushi DOI ◽  
Noritaka IMAMACHI ◽  
Tomomune KISHIMOTO ◽  
Yoji SAITO

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.


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.


1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.


Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.


1984 ◽  
Vol 48 (8) ◽  
pp. 448-452
Author(s):  
LA Tedesco ◽  
JE Albino ◽  
WM Feagans ◽  
RS Mackenzie

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