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1 ting information from prior adult trials and thereby reduce the sample size.

2 hich the number of covariates is typically much larger than the sample size.

3 ears to significantly affect the error by up to 4 mmHg over the sample size.

4 s face a number of experimental design decisions, including the sample size.

8 or treatment effects, even with many covariates relative to the sample size, and without "sparsity" assumptions.

9 f continuous coverage from 6 months to 1 or 2 years reduced the sample size available without lowering the percentage of

10 This limitation can be partly overcome by increasing the sample size, but this comes at a higher cost.

14 se GWAS, defined as ratio of the log-transformed p-value to the sample size, in larger samples was larger than in smaller

15 rection methods may raise sensitivity to 87%-95% and reduce the sample size increase to less than 27%.

20 e number of SNPs dramatically increases to half million but the sample size is still limited to thousands, the traditiona

21 ollected, and for phenotypes that are difficult to collect, the sample size might be insufficient to achieve the desired

23 e event frequency, treatment effect (hazard ratio; HR), and the sample size needed for future trials for the CompEx versu

24 d due to cost constraints, making it necessary to determine the sample size needed to build an accurate classifier based

25 Measured inter-run variability provides insight regarding the sample size needed to discriminate between microenvironme

26 s in 2001 to 2010; P = .11), with a concomitant increase in the sample size of clinical trials over the same time period

28 ine on different stages of diabetic retinal dysfunction, or the sample size of the present study may be too small to dete

29 e measure of ASB derived from multiple measures, maximizing the sample size over different age ranges.

31 n NHANES cycles were included (1999-2000 to 2011-2012), and the sample size per cycle ranged from 4861 to 6212.

32 f the relationship between the components of a binary CE on the sample size requirement (SSR) has not been addressed.

33 removed some unmeasured confounding; however, this reduced the sample size, resulting in wide confidence intervals.

34 the emergent smaller-is-stronger size effect is related to the sample-size scaling of the distribution of flaws.

35 IS) methods were combined to reduce the model dimensions at the sample size; second, a grouped penalized regression was a

37 The dependence on various parameters such as the sample size, the number of truly influential variables or

38 opology also depends on the number of transmitted lineages, the sample size, the time of the sample relative to transmiss

39 ross the differentially expressed genes, and then calculate the sample size to achieve a desired average power while cont

41 the pressure ulcer prevention care bundle was effective but the sample size too small to detect this.

42 ION: No evidence of benefit for ketamine was found although the sample size used was small; however, the results excluded

43 To increase statistical power, we expanded the sample size via genotyping and imputation in a further 11

44 previously accrued data, with alpha of 0.05 and power 80%, the sample size was calculated as 35 patients for each group

50 recorded the intervention and its comparator, the setting, the sample size, whether enrollment was completed or interrup

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