Sample size calculation

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Principles of sample size calculation

In most areas in life, it is difficult to work with populations and hence researchers work with samples. The calculation of the sample size needed depends on the data type and distribution. Elements include consideration of the alpha error, beta error, clinically meaningful difference, and the variability or standard deviation. The final number arrived at should be increased to include a safety...

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Sample size calculation: Basic principles

Addressing a sample size is a practical issue that has to be solved during planning and designing stage of the study. The aim of any clinical research is to detect the actual difference between two groups (power) and to provide an estimate of the difference with a reasonable accuracy (precision). Hence, researchers should do a priori estimate of sample size well ahead, before conducting the stu...

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sample size calculation in medical studies

optimum sample size is an essential component of any research. the main purpose of the sample size calculation is to determine the enough number of units needed to detect the unknown clinical parameters or the treatment effects or the association after data gathering. it is not uncommon for studies to be underpowered and failing to detect the existed treatment effects due to inadequate sample s...

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Sample size calculation in metabolic phenotyping studies

The number of samples needed to identify significant effects is a key question in biomedical studies, with consequences on experimental designs, costs and potential discoveries. In metabolic phenotyping studies, sample size determination remains a complex step. This is due particularly to the multiple hypothesis-testing framework and the top-down hypothesis-free approach, with no a priori known...

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Sample size calculation in medical studies

Optimum sample size is an essential component of any research. The main purpose of the sample size calculation is to determine the number of samples needed to detect significant changes in clinical parameters, treatment effects or associations after data gathering. It is not uncommon for studies to be underpowered and thereby fail to detect the existing treatment effects due to inadequate sampl...

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ژورنال

عنوان ژورنال: International Journal of Ayurveda Research

سال: 2010

ISSN: 0974-7788

DOI: 10.4103/0974-7788.59946