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2. Vollert J, Maier C, Attal N, et al. Stratifying patients with peripheral neuropathic pain based on sensory profiles: algorithm and sample size recommendations.
The data captured the key perspectives for the case study and met the minimum sample size recommendations was met (Collins, 2010).
The sample size for our study was relatively small compared to other conjoint analysis studies and sample size recommendations [ 69, 88].
In this paper we aim to develop sample size recommendations for multivariable models of time-to-event data, based on their prognostic ability.
The researcher should go beyond these minimum sample size recommendations when data are non-normal (e.g. skewed or kurtotic) or incomplete, so it was debatable whether this standard had been met in our analysis.
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In this situation the most often cited sample size recommendation is the rule of '10 events per variable' (EPV) which originated from two simulation studies [ 12, 13].
The 'rule of thumb' sample size recommendation for psychometric analyses of new summated scales is five to 10 subjects per item, to reduce the effect of chance [ 19, 22].
This sample size meets recommendations for phenomenological studies [ 14, 27].
Due to the limited sample size definite dose recommendations can not be made based on our findings.
Currently there seem to be very few sample size calculations or recommendations for developing or validating multivariable models which are based on the prognostic ability of a model, rather than the significance of its coefficients.
To reach a 'good sample size' according to recommendations for methodological quality and test-retest reliability analysis [ 20], we aimed at 50 to 99 participants with FOF total scores at both t1 and t2.
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