Exact(1)
In order to explore the reasons for the most substantial biases, we tested a number of alternate assumptions for the worst performing scenario, Scenario B. As might be expected, keeping the population size at 1 million but increasing the sampled size 100 times from 170 to 17,000 did little to reduce the amplitude of bias but did reduce the size of our confidence intervals substantially.
Similar(59)
Increasing the sample size results in an increased frequency of detecting marker/phenotype associations [ 40].
Because the margin of sampling error is related to the size of the sample, increasing the sample size for a particular subgroup through the use of oversampling allows for estimates to be made with a smaller margin of error.
Although it is challenging to collect data in forensic samples future studies should increase the statistical power by increasing the sample size and examine more subtle effects.
Error in sampling can be reduced by increasing the sample size.
Stratified sampling allows increasing the sample size in a region by a few to many additional sample units.
Increasing the sample size by a factor of 10 would increase the accuracy of the results.
Approximately results are consistent by increasing the sample size.
It is simply seen that the value of error decreases by increasing the sample size.
However, increasing the sample size could improve the performance of the OLS-based model.
Weaknesses in data can be effectively addressed by increasing the sample size.
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