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Sample size in clinical trials – challenges and approaches

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Tomski A., Gorzawska B.

Przegląd Statystyczny

2022

vol. 69

issue 4

20-28

Sample size estimation is a necessary and crucial step in clinical trial research. Statistical requirements, limited patient availability and high financial risk of a clinical trial necessitate the proper calculation of this measure. The aim of this paper is to discuss the reasons why the estimation of the sample size is important and, based on the obtained results, to show how this process may be completed in selected cases. Stochastic simulations based on the Monte Carlo methods approach are applied. Therefore, new challenges facing this area of research are mentioned.

Estimation of Bias and Variance of Sample Median by Jacknife and Bootstrap Methods

100%

Pruska K., University of Łódź C. o. S. M.

Acta Universitatis Lodziensis. Folia Oeconomica

2007

vol. 206

In the paper the estimation of sample median bias and variance by jackknife and bootstrap methods are considered. Monte Carlo analysis of properties of estimators is presented (mean of bias and mean of variance for some groups of experiments). Sensitivity of distribution of sample median to changes of the sample size is investigated.

W pracy przedstawione są wyniki, przeprowadzonej przez autora, analizy Monte Carlo własności estymatorów typu jackknife i bootstrap mediany z próby z uwzględnieniem wpływu liczebności próby.

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1 Acta Universitatis Lodziensis. Folia Oeconomica

1 Przegląd Statystyczny

1 Gorzawska B.

1 Pruska K.

1 Tomski A.

1 University of Łódź C. o. S. M.

1 2023

1 2007

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Sample size in clinical trials – challenges and approaches

Estimation of Bias and Variance of Sample Median by Jacknife and Bootstrap Methods