scholarly journals On the analysis of very small samples of Gaussian repeated measurements: an alternative approach

2017 ◽  
Vol 36 (6) ◽  
pp. 958-970 ◽  
Author(s):  
Philip M. Westgate ◽  
Woodrow W. Burchett
Keyword(s):  
Repeated Measurements ◽  
Small Samples ◽  
Alternative Approach

scholarly journals Decision Strategies for Absorbance Readings from an Enzyme-Linked Immunosorbent Assay—A Case Study about Testing Genotypes of Sugar Beet (Beta vulgaris L.) for Resistance against Beet Necrotic Yellow Vein Virus (BNYVV)

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 956
Author(s):  
Thomas M. Lange ◽  
Martin Wutke ◽  
Lisa Bertram ◽  
Harald Keunecke ◽  
Friedrich Kopisch-Obuch ◽  
...  
Keyword(s):  
Sugar Beet ◽  
Beta Vulgaris ◽  
Immunosorbent Assay ◽  
Area Under The Curve ◽  
Bayes Factors ◽  
Yellow Vein ◽  
Small Samples ◽  
Enzyme Linked Immunosorbent Assay ◽  
Virus Concentration ◽  
Alternative Approach

The Beet necrotic yellow vein virus (BNYVV) causes rhizomania in sugar beet (Beta vulgaris L.), which is one of the most destructive diseases in sugar beet worldwide. In breeding projects towards resistance against BNYVV, the enzyme-linked immunosorbent assay (ELISA) is used to determine the virus concentration in plant roots and, thus, the resistance levels of genotypes. Here, we present a simulation study to generate 10,000 small samples from the estimated density functions of ELISA values from susceptible and resistant sugar beet genotypes. We apply receiver operating characteristic (ROC) analysis to these samples to optimise the cutoff values for sample sizes from two to eight and determine the false positive rates (FPR), true positive rates (TPR), and area under the curve (AUC). We present, furthermore, an alternative approach based upon Bayes factors to improve the decision procedure. The Bayesian approach has proven to be superior to the simple cutoff approach. The presented results could help evaluate or improve existing breeding programs and help design future selection procedures based upon ELISA. An R-script for the classification of sample data based upon Bayes factors is provided.

scholarly journals Dyslexia treatment studies: A systematic review and suggestions on testing treatment efficacy with small effects and small samples

2021 ◽  
Author(s):  
Enrico Toffalini ◽  
David Giofrè ◽  
Massimiliano Pastore ◽  
Barbara Carretti ◽  
Federica Fraccadori ◽  
...  
Keyword(s):  
Systematic Review ◽  
Effect Size ◽  
Treatment Efficacy ◽  
Multiple Testing ◽  
Poor Response ◽  
Population Level ◽  
Learning Disorders ◽  
Repeated Measurements ◽  
Response To Treatment ◽  
Small Samples

AbstractPoor response to treatment is a defining characteristic of reading disorder. In the present systematic review and meta-analysis, we found that the overall average effect size for treatment efficacy was modest, with a mean standardized difference of 0.38. Small true effects, combined with the difficulty to recruit large samples, seriously challenge researchers planning to test treatment efficacy in dyslexia and potentially in other learning disorders. Nonetheless, most published studies claim effectiveness, generally based on liberal use of multiple testing. This inflates the risk that most statistically significant results are associated with overestimated effect sizes. To enhance power, we propose the strategic use of repeated measurements with mixed-effects modelling. This novel approach would enable us to estimate both individual parameters and population-level effects more reliably. We suggest assessing a reading outcome not once, but three times, at pre-treatment and three times at post-treatment. Such design would require only modest additional efforts compared to current practices. Based on this, we performed ad hoc a priori design analyses via simulation studies. Results showed that using the novel design may allow one to reach adequate power even with low sample sizes of 30–40 participants (i.e., 15–20 participants per group) for a typical effect size of d = 0.38. Nonetheless, more conservative assumptions are warranted for various reasons, including a high risk of publication bias in the extant literature. Our considerations can be extended to intervention studies of other types of neurodevelopmental disorders.

scholarly journals The analysis of very small samples of repeated measurements II: A modified Box correction

2010 ◽  
Vol 29 (27) ◽  
pp. 2838-2856 ◽  
Author(s):  
Simon S. Skene ◽  
Michael G. Kenward
Keyword(s):  
Repeated Measurements ◽  
Small Samples

scholarly journals Article numbers as a leading indicator of publication time

2021 ◽  
Vol 31 (1) ◽  
pp. e41065
Author(s):  
Jimmie Leppink
Keyword(s):  
Correlation Function ◽  
Cross Correlation ◽  
Repeated Measurements ◽  
Cross Correlation Function ◽  
Small Samples ◽  
Outcome Variable ◽  
Leading Indicator ◽  
Single Subjects ◽  
Statistical Program ◽  
Publication Time

Aims: in health professions education (HPE), the use of statistics is commonly associated with somewhat larger samples, whereas smaller samples or single subjects (i.e., N = 1) are usually labelled as needing some kind of ‘qualitative’ approach. However, statistical methods can be very useful in small samples and for individual subjects as well, especially where we have time series of repeated measurements of the same outcome variable(s) of interest. The aim of this article is twofold: to demonstrate an example of a cross-correlation function for single subjects in a HPE context and to suggest a few settings in HPE where this cross-correlation function can be of use.Method: the example uses data from a recent Open Access publication on among others article numbers and publication time in a number of major HPE journals to examine the relation between the number of articles published and median publication time over time in the zero-cost Open-Source statistical program R version 4.0.5.Results: as to be expected, the number of articles published appears somewhat of a leading indicator of publication time: both number of articles in year ‘y’ and number of articles in year ‘y minus 1’ correlate > 0.6 with median publication time in year ‘y’, while correlations of other time differences (e.g., number of articles in year ‘y minus 2’ and median publication time in year ‘y’, or median publication time in year ‘y’ and number of articles in year ‘y plus 1’) are substantially smaller.Conclusion: in line with recent literature, this article demonstrates that the cross-correlation function can be used in the context of small samples and single subjects. While the example focusses on article numbers and publication times, it can equally be applied in for example studying relations between knowledge, skills and attitude in individuals, or relations between behaviors of individuals working in pairs or small groups.

V940: Pre-Pubic SPARC for Stress Urinary Incontinence: An Alternative Approach for Scarred Retzius Space

2004 ◽  
Vol 171 (4S) ◽  
pp. 249-249
Author(s):  
Paulo Palma ◽  
Cassio Riccetto ◽  
Marcelo Thiel ◽  
Miriam Dambros ◽  
Rogerio Fraga ◽  
...  
Keyword(s):  
Urinary Incontinence ◽  
Stress Urinary Incontinence ◽  
Alternative Approach
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