ライフサイエンスコーパス: the sample size

1 mance to random sampling can be achieved with a fraction of the sample size.

2 ite-dimensional space with dimension that grows faster than the sample size.

3 es is dependent on the gene-specific disease prevalence and the sample size.

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

5 at are unimportant for prediction must significantly exceed the sample size.

6 nte Carlo simulations to determine the relationship between the sample size and the accuracy of the sample mean and varia

7 The variability in the sample size and the subjects participating in the experim

8 All studies had a high risk of bias, primarily due to the sample size, and statistical methods used to develop and

9 In sum, linear models keep improving as the sample size approaches ~10,000 subjects.

10 g that the importance of the network structure increases as the sample size becomes smaller.

11 The sample size calculation was based upon a target differenc

12 The sample size determination was based on standard practice

13 haracterizing metal plasticity and towards comprehension of the sample size effects that limit the mechanical reliability

14 Determining the sample size for adequate power to detect statistical sign

15 ressed genes (DEGs) on the top than others, especially when the sample size gets bigger or when the heterogeneity level o

16 As compared with intermediate-risk cohorts, the sample size in these trials was smaller and the total num

17 For the sample size included, TI > 0.36 signified statistical sig

18 challenging to build good predictive models especially when the sample size is limited and the number of features is high

19 iances and also to control false discovery rates, even when the sample size is small (n=10).

20 When the sample size is small or the expression levels of a gene a

21 FB tends to find more biologically relevant genes even when the sample size is small.

22 of genetic variants) times simpler than that of GEMMA when the sample size is way smaller than the number of markers.

23 statistics or data science usually learn early on that when the sample size n is large relative to the number of variable

24 nfer whether a reported difference would likely recur, with the sample size n used for statistical tests representing bio

25 However, the sample size necessary for animal studies requires increas

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

27 re(s) or phenotype(s), it is critically important to assess the sample size needed to detect a hypothesized difference wi

28 o be used for DNAm profiling, users are required to specify the sample size, number of differentially methylated CpGs, ef

29 FI was significantly (all P<0.05) correlated with the sample size, number of events, statistical power, journal

30 The sample size of 11 patients is small but was considered su

31 -analyzed with TWAS using a fixed-effects model weighted by the sample size of each data set.

32 Power analysis is essential to decide the sample size of metagenomic sequencing experiments in a ca

33 analysis with public summary statistics, more than doubling the sample size of previous meta-analyses.

34 ial that was part of the 2-by-2 factorial design, and (iii) the sample size of the household survey was not prespecified.

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

36 By artificially inflating the sample size, pseudoreplication contributes to irreproduci

37 Among the 11 included studies published in 2003-2018, the sample size ranged from 3 to 551 participants.

38 rating scores and objective service performance and lowered the sample size required for obtaining reliable, averaged cro

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

40 hic, calligraphic, or medical images), and less affected by the sample size, suggesting that the optimal network structur

41 The extent of bias depends on the sample size, the (unknown) population allele frequencies,

42 The sample size to detect a 5% change in lung involvement wit

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

44 Depending on specification, the sample size varied between 95,320 and 102,318 mother-infa

45 The sample size was calculated for the exploratory efficacy e

46 The main simulation results were: (1) When the sample size was large (n = 340), the true positive rates

47 When the sample size was large and the proportion of outliers was

48 (2) When the sample size was small, the main problem was low TPR, whic

49 in those patients was shorter than the whole MMP cohort and the sample size was small.

50 Although limited by the sample size, we observed no increase in mortality, organ