Evaluating the marginal effect of sample size in the median sample size of 16 yielded a marginal effect of −0.006.
The estimated marginal effect of sample size and dimension in our study may help policy-makers to compare the results of different studies with different sample sizes and dimensions in the country.
Marginal change in sample size for r + 1 compared to r assessments is therefore: This equation does not require that measurements be equally spaced or that correlations between measurements be constant.
The inconsistent results may be attributed to different molecular mechanisms of carcinogenesis among cancers, small sample size, marginal statistical significance and different ethnicities of study populations.
+ unpublished data * Mean correlation between baseline measures **Mean correlation between follow-up measures *** Mean correlation between baseline and follow-up measures Table 2 shows the marginal relative decreases in sample size given various numbers of assessments and correlations.
The significant differences of the distributions in the contingency tables can also be explained by the known fact that such measures like the marginal homogeneity test are sample size dependent.
Given the large sample size, even marginal correlations were significant.
Sample size for the quantitative study was calculated based on single proportion formula by assuming 50% prevalence and 5% marginal error to yield maximum sample size.
In addition, EVSI also allows the evaluation of marginal returns associated with increased sample size formally taking uncertainty into account (eg, say that an additional 100 patients when only 500 have been recruited would be likely to provide more value than when 20,000 have been recruited).
The marginal significance may have reflected low sample size.
