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SIPBS is a major research centre in Scotland focusing on 'new medicines', 'better medicines' and 'better use of medicines'. This includes the exploration of nanoparticles and nanomedicines within the wider research agenda of bionanotechnology, in which the tools of nanotechnology are applied to solve biological problems. At SIPBS multidisciplinary approaches are also pursued to improve bioscience understanding of novel therapeutic targets with the aim of developing therapeutic interventions and the investigation, development and manufacture of drug substances and products.

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Using GPower software to determine the sample size from the pilot study

Alotaibi, Sultan Refa D and Roussinov, Dmitri (2016) Using GPower software to determine the sample size from the pilot study. In: The 9th Saudi Students Conference, 2016-02-13, University of Birmingham.

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Abstract

Recently, the estimation of the sample size is very important topic for the researchers, so it is an indispensable process for obtaining good results. There are two way to determine the sample size which are from literature review and from the pilot study. In this poster, we will focus on power analysis to get suitable sample size for our research. This power analysis is conducted to assess the minimum sample size requirement. GPower software application is used to perform a priori power analysis for the study taking multiple regression analysis for the validation of the measurement model. The required power was set at 1- β = 0.80. Level of significance was kept at α = 0.05. Effect size was kept at small range value of 0.02. For the measurement model each proposed latent construct has four indicators and the number of predictors is taken as 7. Using these settings, power curve was extracted. Figure 1 gives the power curve for different values of power ranging from 0.5 to 0.95. Power analysis clearly indicates that to achieve, power of 0.80, a total sample size of n = 725 is needed for this study. Therefore using the literature and thumb rule method and results of power analysis indicate that the total sample size needed for the study is around n = 750. Therefore, 800 respondents are taken as the optimal sample size for the investigation.