Researchers are frequently asked to justify the sample size used in their quantitative inquiries. Such a justification can be provided through a power analysis. Conducting power analyses, however, can raise some difficult issues regarding the specification of the size of the effect, testing for interaction effects, the role of covariates, and the use of an estimated effect size in the power analysis. The authors present methods for conducting power analyses along with a discussion of these issues, and they make available SAS programs that can be used to implement the power analyses that are discussed.
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http://dx.doi.org/10.1177/0163278703255248 | DOI Listing |
Nutrition
December 2024
Hacettepe University, Department of Internal Medicine, Division of Geriatric Medicine, Ankara, Turkey.
Background And Aim: Malnutrition is strongly related to mortality in intensive care unit (ICU) patients. The Patient- and Nutrition-Derived Outcome Risk Assessment Score (PANDORA) is a novel mortality prediction tool encompassing nutritional assessment. Since there is limited evidence regarding the power of PANDORA in predicting mortality in critically ill patients, we aimed to evaluate the benefit of adding PANDORA to the Global Leadership Initiative on Malnutrition (GLIM) for mortality prediction in the ICU setting by comparing it with the other valid mortality predictors.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
December 2024
IVF Unit, Hillel Yaffe Medical Center, Hadera, Israel; Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa 3109601, Israel.
Research Question: Can attenuated total reflection-Fourier transform infrared spectroscopy combined with machine learning techniques be used to develop a real-time diagnostic modality for chronic endometritis by analysing endometrial biopsies obtained during hysteroscopy?
Design: Women undergoing hysteroscopy for infertility assessment were enrolled in this prospective study from January 2020 to March 2021. Endometrial biopsies were evaluated using a spectrophotometer, and subsequently via histopathology, including immunohistochemical staining for the multiple myeloma oncogene-1 (MUM-1). Spectroscopy analyses of the positive and the negative chronic endometritis groups were compared across various cut-offs of MUM-1 positive cells per 10 high-power fields (HPF).
Front Physiol
December 2024
Department of Sport and Exercise Science, Paris Lodron University Salzburg, Salzburg, Austria.
Introduction: Our recent meta-analyses have demonstrated that high-intensity interval training (HIIT) causes a range of mean changes in various measures and predictors of endurance and sprint performance in athletes. Here, we extend the analyses to relationships between mean changes of these measures and consider implications for understanding and improving HIIT that were not apparent in the previous analyses.
Methods: The data were mean changes from HIIT with highly trained endurance and elite other (mainly team sport) athletes in studies where two or more measures or predictors of performance were available.
Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants (25,255 non-responders and 110,216 responders). We performed genome-wide association meta-analyses, genetic correlation analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization.
View Article and Find Full Text PDFCase-control genome-wide association studies (GWAS) are often used to find associations between genetic variants and diseases. When case-control GWAS are conducted, researchers must make decisions regarding how many cases and how many controls to include in the study. Depending on differing availability and cost of controls and cases, varying case fractions are used in case-control GWAS.
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