Point of data saturation was assessed using resampling methods in a survey with open-ended questions

Abstract : Objective: To describe methods to determine sample sizes in surveys using open-ended questions and to assess how resampling methods can be used to determine data saturation in these surveys. Study Design and Setting: We searched the literature for surveys with open-ended questions and assessed the methods used to determine sample size in 100 studies selected at random. Then, we used Monte Carlo simulations on data from a previous study on the burden of treatment to assess the probability of identifying new themes as a function of the number of patients recruited. Results: In the literature, 85% of researchers used a convenience sample, with a median size of 167 participants (interquartile range [IQR] 5 69e406). In our simulation study, the probability of identifying at least one new theme for the next included subject was 32%, 24%, and 12% after the inclusion of 30, 50, and 100 subjects, respectively. The inclusion of 150 participants at random resulted in the identification of 92% themes (IQR 5 91e93%) identified in the original study. Conclusion: In our study, data saturation was most certainly reached for samples O150 participants. Our method may be used to determine when to continue the study to find new themes or stop because of futility.
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Journal of Clinical Epidemiology, Elsevier, 2016, 80, pp.88-96. 〈10.1016/j.jclinepi.2016.07.014〉
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Dernière modification le : lundi 11 décembre 2017 - 15:16:01

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Viet-Thi Tran, Raphael Porcher, Bruno Falissard, Philippe Ravaud. Point of data saturation was assessed using resampling methods in a survey with open-ended questions. Journal of Clinical Epidemiology, Elsevier, 2016, 80, pp.88-96. 〈10.1016/j.jclinepi.2016.07.014〉. 〈inserm-01368815〉

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