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To generate more-accurate prediction models, we varied sample sizes for both the training and testing data sets.
Because the number of ED visits each week varied, sample sizes were generated from a list of weekly visit frequencies.
Potential explanations for this discrepancy may lie in cultural and/or social variances, varied sample sizes (China: 508; Nigeria: 132; Australia: 121; England: 47), different methods for categorization of patients, and dissimilar patient selection criteria.
Using realistic fixed estimates of the mean and standard deviation of effects and costs at population level (based on Hakkaart-van Roijen et al., 2006), we simulated a large number of trials in which we systematically varied sample sizes between n = 10 to n = 500 per group (n = 10, 25, 50, 75, 150, 500).
We varied sample sizes between 5,000 and the entire sample.
This method can be adopted for investigation of varied sample sizes, and the specificity and sensitivity of the method can be tailored to suit the objectives of each investigation.
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We recommend testing against existing protocols (such as one presented in this paper) in simulated or real data with known predictive signal using datasets in which the experimenter varies sample sizes [44], [45].
In these analyses, we vary sample size of the training set (N), the number of genotyped SNPs (P), the fraction of SNPs exerting a causal influence (f C ), and the SNP-based heritability (hSNP).
However, the power of such tests may vary with sample sizes, and in our case these varied widely with colony size.
Fixed costs are those that do not vary with sample sizes and design alternatives, but are common to all alternatives, for example cost for administration or research.
The samples are varied in sample size, gender distribution, age, and exercise addiction scores.
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