ライフサイエンスコーパス: have @1 power to detect

1 The study had 80% power to detect 60% differences in T-cell frequencies

2 The study had 80% power to detect a 0.3 log(10) decrease in HIV-1 RNA l

3 The study had 80% power to detect a 25% increase in TTP assuming a TTP

4 The study had 80% power to detect a 4% difference in infarct size with

5 Our study had 80% power to detect a 4.9% mutation frequency in POAG pat

6 The study had 80% power to detect an odds ratio (OR) of 2.5.

7 The trial had 80% power to detect hazard ratio (HR), 0.714 by intent-to

8 For the primary end point, the analysis had 88% power to detect a 25% reduction and 70% power to dete

9 nd point was progression-free survival, for which the study had 90% power to detect a 50% improvement (from 4 to 6 months

10 This trial had 90% power to detect a 50% improvement in median PFS from

11 The study had 90% power to detect the differences between our anticipat

12 We had 97% power to detect a four-point difference in scores, wh

13 type I error rate adjusted for multiple testing, this study had 99% power to detect a SNP, with minor allele frequency of

14 We had 99% power to detect the lower bound of the reported effec

15 ls to estimate incidence (relative standard error, 30%) and had >80% power to detect a 50% reduction in incidence.

16 Thus, for each end point, the study had >90% power to detect a clinically important increased ris

17 Under various alternative hypotheses, HBSP had adequate power to detect modest genetic associations in c

18 recombination hotspot is present in all populations and we had insufficient power to detect it in the non-African data.

19 -score methods with segregation analysis-derived parameters had less power to detect linkage than ASP tests.

20 However, the study may have had limited power to detect a significant difference.

21 However, the study may have had limited power to detect clinically important differences,

22 onal study, baseline data were self-reported, and the study had limited power to detect differences between white and Afr

23 However, this study had limited power to detect independent significance of ESVI

24 lipidemia, from involvement in DN pathogenesis as our study had limited power to detect variants of small effect size.

25 This study had low power to detect an effect for specific or rare cancer

26 A test for interaction was not significant, but had low power to detect an interaction.

27 two sets of disease-related common phenotypes for which we had statistical power to detect large numbers of common varia

28 reported increase in survival in two of the trials, neither had sufficient power to detect significant benefit for perfus

29 The study was designed to have 80% power to detect a difference of 10% in 5-year overal

30 If we want to have enough power to detect siRNAs with moderate effects, sam

31 ect sizes corresponding to an odds ratio of 1.2, but should have good power to detect effects at an odds ratio of 2 or mo

32 Simulations show our integrative methods to have higher power to detect disease-related genes than non-in

33 Joint-multiple population analysis should have higher power to detect QTL shared among multiple familie

34 ose are expended on rare haplotypes for which studies would have insufficient power to detect association even if it exis

35 es of weak effect, and consequently, individual studies may have insufficient power to detect linkage.

36 However, most randomized coronary artery patient trials have insufficient power to detect significant differences in

37 However, such studies have limited power to detect genes containing multiple rare v

38 constrained by the relatively small samples sizes and thus have limited power to detect small to moderate associations.

39 It is also clear that these mapping strategies have little power to detect polygenic factors, and some new s

40 tion, Tajima's D, Fu and Li's D, and haplotype homozygosity have lower power to detect population-specific selection usin

41 power to detect QTL shared among multiple families, but may have lower power to detect rare QTL.

42 This means twin study designs have more power to detect heritable effects in variance compo

43 Our calculations show that multiallelic markers always have more power to detect LD than do diallelic markers (under

44 variance component models of myopia, whereas family studies have more power to detect shared environment effects.

45 ions and the numbers of mutations fixed between populations have substantial power to detect even very weak selection.

46 To have sufficient power to detect a reasonably modest differenc

47 However, this study did not have sufficient power to detect adverse birth outcomes.

48 Analysis and simulations show that we have sufficient power to detect such departures under varying

49 variable selective pressures across codons in the gene and have the power to detect amino acid residues under either pos

50 ies typically focus on single-locus analysis, which may not have the power to detect the majority of genuinely associated