ライフサイエンスコーパス: sample size

1 ng the power gained by a twofold increase in sample size.

2 replicated (p>0.05), despite our much larger sample size.

3 the rate of change of SADs as a function of sample size.

4 rmer is considerably lower than the combined sample size.

5 underpowered for mortality because of small sample size.

6 significance, possibly because of the small sample size.

7 om prior adult trials and thereby reduce the sample size.

8 e prespecified given the anticipated limited sample size.

9 ng prior adult data can reduce the necessary sample size.

10 directly from DIA data in studies of a large sample size.

11 overy of genetic risk factor despite reduced sample size.

12 included datasets even when controlling for sample size.

13 lyze family-based sequence data with a small sample size.

14 covariates is typically much larger than the sample size.

15 isease has been hampered by study design and sample size.

16 studies included an appropriately calculated sample size.

17 children's hospitals, depending on available sample size.

18 elevant degree within the limitations of our sample size.

19 tation of this study is the relatively small sample size.

20 ohort bias, biological variation and limited sample size.

21 ly affect the error by up to 4 mmHg over the sample size.

22 to 10 months, the ALSFRS-R required a lower sample size.

23 ects of topical formulations using a limited sample size.

24 generalizable due to cohort bias and limited sample size.

25 % of therapy, albeit on the basis of a small sample size.

26 data are now available for exceedingly large sample sizes.

27 produced mixed results, and most had modest sample sizes.

28 ant associations and the need for very large sample sizes.

29 es of intelligence with substantially larger sample sizes.

30 of CNV to risk has been hampered by limited sample sizes.

31 ly unknown and progress is hampered by small sample sizes.

32 inable updating, inclusive cohorts and large sample sizes.

33 timating network properties given only small sample sizes.

34 nt in cohort studies and studies with larger sample sizes.

35 edious, thus limiting such analyses to small sample sizes.

36 er from serious limitations, including small sample sizes.

37 specific functional effects, with achievable sample sizes.

38 sist in designing experiments and estimating sample sizes.

39 ar for Engelmann spruce, likely due to small sample sizes.

40 t continuous data in studies that have small sample sizes.

41 omputationally tractable even for very large sample sizes.

42 statistical approaches and increasing study sample sizes.

43 sociation study (GWAS) of Han Chinese with a sample size 2.7 times the largest previously published G

44 interpreted in light of the relatively small sample size (3 studies) and its post-hoc nature, it prov

45 udy with few strong study designs with large sample sizes; (5) research from low-income and middle-in

46 makes inferring network structure from small sample sizes, a necessity given the technical difficulty

47 of Asian adults above 18 years old and with sample size above 50.

48 Our findings imply that substantially larger sample sizes across ages and lifestyles are required to

49 This is possibly due to small sample size, allelic heterogeneity, small effect sizes o

50 The large sample size allowed analysis of the associations between

51 Increasing sample size also had a positive effect on GCN.

52 vidences were mostly unaffected by an uneven sample size, although clustering results in reference po

53 A simulated sample size analysis, in which g was used as the endpoin

54 Also, the sample size analyzed by these assays is limited due to t

55 Expansion of sample size and a more balanced representation of taxono

56 ges of pore diameter, pore space, pore type, sample size and associated pore connectivity, as well as

57 cal framework for interpretation focusing on sample size and composition, nonlinearity, and unmeasure

58 R) in diabetic patients are limited by small sample size and contradictory results.

59 Future increases in sample size and denser genotyping might facilitate the i

60 ischemic heart disease have been limited by sample size and design.

61 statistical software that took into account sample size and different treatment groups, and limited

62 s have been relatively scarce and limited in sample size and duration, and the effect estimates have

63 uence of different normalisation approaches, sample size and intervention effects on funnel plot asym

64 data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variabl

65 This demonstrates, despite a small sample size and limited sampling, the feasibility of cha

66 s, seen in the outcome studies with a larger sample size and longer follow-up.

67 Large sample size and low dispersion generally make Type-I err

68 studies and meta-analyses, namely inadequate sample size and methodological heterogeneity.

69 Despite substantially increased sample size and more complete coverage of low-frequency

70 Despite our large sample size and multiple datasets available, we could no

71 as for these extreme values as a function of sample size and number of segregating sites.

72 Further trials with a larger sample size and objective clinically relevant end points

73 were translated to trial design in terms of sample size and power.

74 regation Consortium (ExAC) data to show that sample size and ratio interact to influence the number o

75 However, likely due to the smaller sample size and sample-to-sample heterogeneity, our pred

76 were assessed by 14 parameters representing sample size and shape.

77 ions, with power being influenced further by sample size and SNP density.

78 s main limitations were the relatively small sample size and stable, well-compensated population.

79 udy limitations include the relatively small sample size and the absence of data relating to adaptive

80 onal surveys offers the advantage of a large sample size and the elimination of many biases typically

81 Ls, we observed a strong correlation between sample size and the proportion of loci with AH (R(2) = 0

82 The variability in the sample size and the subjects participating in the experi

83 severe when the primary studies had a small sample size and when an intervention effect was present.

84 ction of an emerging pathogen within imposed sample size and/or cost constraints, and demonstrate its

85 Studies with larger sample sizes and additional biomarkers will expand the c

86 es of musical abilities should involve large sample sizes and an unbiased genome-wide approach, with

87 eatment response in OCD, studies with larger sample sizes and detailed information on drug dosage and

88 ing the proliferation of studies using small sample sizes and diverse designs, limited replication, p

89 r radiotherapy of bone metastases have small sample sizes and do not use specific questionnaires.

90 these savings should be invested to increase sample sizes and hence power, since the currently underp

91 s that can be estimated reliably given small sample sizes and is an accurate fingerprint of every top

92 components are inferred correctly, although sample sizes and times since admixture can influence the

93 ed experimental design that considers larger sample sizes and/or greater study replication.

94 Although small samples sizes and multiple comparisons were of concern,

95 ies were constrained by the relatively small samples sizes and thus have limited power to detect smal

96 fter accounting for mycorrhizal association, sample size, and climatic range, foliar delta(15)N in P.

97 s with lower quality, and studies with small sample size, and were almost absent in cohort studies an

98 Mendelian randomization requires large sample sizes, and power was limited to provide precise e

99 radioligand, low-resolution scanners, small sample sizes, and psychotic patients being on antipsycho

100 harts are few in number, were based on small sample sizes, and were not population based.

101 with high quality and/or sufficiently large sample size are more likely to report significant IPE.

102 Large sample sizes are needed for sublingual immunotherapy (SL

103 and other complex genetic disorders, larger sample sizes are needed to identify specific risk loci.

104 H4 emissions are too narrow, and that larger sample sizes are required in future studies to achieve t

105 gression methods appear to perform best when sample sizes are sufficient and adequate statistical cap

106 fficiency of experimental studies, even when sample sizes are very small, as is currently prevalent i

107 up was small, and future studies with larger samples sizes are required to investigate to what extent

108 ial pickup, the sampling reproducibility and sampling size are discussed, and the oligomer distributi

109 Further studies in larger sample sizes, as well as with interventions to increase

110 hen possible), or plotting the SMD against a sample size-based precision estimate, are more reliable

111 ct decreased (undercoverage) with increasing sample size because of increasing precision.

112 Although challenges of sample size, both recognized and unrecognized phenotypic

113 ion can be partly overcome by increasing the sample size, but this comes at a higher cost.

114 ic Shock 3.0 definition would have decreased sample size by about half.

115 The Septic Shock 3.0 definition decreased sample size by half and increased 28-day mortality rates

116 The increase in sample size by UK Biobank raised the number of reconstit

117 Sample size calculation and power estimation are essenti

118 Power analysis and sample size calculation are challenging in the context o

119 The sample size calculation was based upon a target differen

120 Sample size calculations (ratio of patients who received

121 minimal important difference will facilitate sample size calculations for clinical studies evaluating

122 results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants

123 Small sample sizes common in next-generation sequencing studie

124 showed that none of the factors considered (sample size, contextual level at which income inequality

125 tion of our study and met the assessment and sample size criteria were invited to participate.

126 Although based on a limited sample size, differences between volar and subungual/int

127 In order to control for differences in sample size during effect size computation, studies were

128 as reported in 21.8%, blinding in 32.7%, and sample size estimation in 2.3%.

129 Randomization, blinding, sample size estimation, and considering sex as a biologi

130 reclinical studies, randomization, blinding, sample size estimation, and inclusion of both sexes were

131 INTERPRETATION: Despite the small sample size for a genome-wide association study, and ack

132 ted the detailed sub-populations and related sample size for each study; (v) Importantly, we performe

133 Limitations include the small sample size for the genetic analysis, which was underpow

134 With currently available technology sample sizes for experiments are typically small, meanin

135 ided conservative results but required large sample sizes for high sensitivity.

136 Limitations include the smaller sample sizes for non-European ancestries and the inabili

137 computing BDA-optimal type 1 error rates and sample sizes for oncology RCTs.

138 Obtaining large sample sizes for pediatric SLIT trials is challenging, b

139 ays as a clinical endpoint may allow smaller sample sizes for trials evaluating RSV antivirals.

140 To determine if PFS provides feasible sample sizes for trials with mutation carriers who have

141 through collaborative efforts to build large samples sizes for case/control analyses for a number of

142 n that information is withheld even when the samples sizes for the former is considerably lower than

143 y determined the percentage RC and effective sample size from each article.

144 Caucasian cohorts, with a combined effective sample size >39,000 individuals.

145 ression analyses showed that age, gender and sample size had no moderating effects on the outcome of

146 This is so because sample sizes have remained small.

147 pharyngeal carcinoma (NPC) risk with a small sample size in a low incidence area.

148 r its potential use as an endpoint to reduce sample size in clinical trials.

149 euroticism, likely because of limitations on sample size in previous studies.

150 esearch has evolved conventions for choosing sample size in randomized clinical trials that rest on t

151 While power was affected by small sample size in the mouse study, the BALF metabolome appe

152 lasma creatinine as outcome could reduce the sample size in trials by 21.5% at 18 months.

153 fortunately, these datasets often have small sample sizes in some tissues.

154 Our work doubles the sampling size in similar environmental studies, and nove

155 ratio of the log-transformed p-value to the sample size, in larger samples was larger than in smalle

156 culosis (PTB) are variously limited by small sample sizes, inadequate dosing regimens, and high basel

157 Our sample size included 5073 beneficiaries: 55% were female

158 und between overall prevalence estimates and sample size, income classification, and method of data c

159 As sample size increases, schizophrenia GWAS results show i

160 n a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele f

161 te of the multinational nature of the study, sample size is a limiting factor for generalization of t

162 When sample size is small (5 in each group), our proposed Bon

163 control false discovery rates, even when the sample size is small (n=10).

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

165 d P-values are known to be conservative when sample size is small, especially for the important case

166 Although the sample size is small, we could also see that various com

167 lysis with increased numbers of variants and sample sizes is needed, followed by sequencing approache

168 aria, although an extended study with larger sample sizes is required to confirm this finding.

169 This may be related in part to sample size issues, which also preclude analysis in pote

170 dered definitive, and for studies with small sample sizes it is necessary before publication.

171 Future research needs to involve advanced sample size justification, innovative solutions to incre

172 Despite the relatively small sample sizes, lack of longer-term data on efficacy, and

173 regressions gain increased power with large sample size, large log2 fold-change, and low dispersion.

174 % CI, -0.55 to -0.11]; P = .005) and a lower sample size (lg) (beta = 0.15 [95% CI, 0.06 to 0.23]; P

175 t too fine a scale, this approach overlooks: sample size limitation arising from sparse tree distribu

176 Here, we address sample size limitations by integrating tumor genomics da

177 However, these methods scale poorly with sample size, limiting resolution in the recent past, and

178 Even though the small sample size limits definite conclusions, our cross-secti

179 study of nutritional approaches with larger sample sizes, longer duration, or a primary endpoint mor

180 urons in experiment: when inferred via small sample sizes, many networks may be indistinguishable des

181 % CI: -0.01, 0.66 SD; P = 0.06), but a small sample size may have compromised the precision of the ef

182 eral ongoing prospective studies with larger sample sizes may provide answers, and newer devices may

183 dological limitations including insufficient sample size, mixed intervention effects and counter-intu

184 ss, because of undercoverage increasing with sample size, most confidence intervals will be over prec

185 pies, which have been limited by their small sample sizes; most studies have been uncontrolled.

186 , HAPRAP performs well with a small training sample size (N < 2000) while other methods become subopt

187 A limitation of our study is its small sample size (n = 29), a subset of the patients treated o

188 seven comparisons tested, CompEx reduced the sample size needed by at least 50%.

189 treatment effect (hazard ratio; HR), and the sample size needed for future trials for the CompEx vers

190 analysis was conducted to estimate the DCIS sample size needed to detect the anticipated benefit of

191 usive approach may help to achieve the large sample sizes needed to detect susceptibility loci for de

192 imulation study to quantify the reduction in sample size, number of patients treated with the standar

193 On the basis of our power calculation, a sample size of 120 women was anticipated.

194 e, incomplete, or ungradable MRI), leaving a sample size of 243 for final analysis (mean [SD] age, 72

195 ule as the combination arm) and with a final sample size of 454 patients.

196 blished summary statistics, yielding a total sample size of 59,957 subjects.

197 hs were included, resulting in a final study sample size of 641.

198 The 156 trials had a median sample size of 91.5 (range, 13-2593) patients/eyes, and

199 used on adults aged at least 18 years with a sample size of at least 100.

200 Due to the limited sample size of available periodontitis cohorts and the u

201 tion of this preliminary study was the small sample size of each cohort.

202 s of this study include the relatively small sample size of each VRC01 administration regimen and mis

203 tors are shown to increase with a decreasing sample size of individuals and with an increasing value

204 duration of less than 4 weeks, or an overall sample size of less than ten patients were excluded.

205 data with a large effect size of d = 1 and a sample size of n = 18 per group, sequential frequentist

206 However, the sample size of RNA methylation experiment is usually ver

207 g limitation in this field is the number and sample size of studies performed to characterize the eti

208 ey limitation of the analysis is the limited sample size of the ACCORD-BP trial, which expanded confi

209 length of stay are limited due to the small sample size of those studies.

210 ted power of the analysis owing to the small sample size of those with impaired vision, we found an e

211 quent meta-analysis with arcOGEN for a total sample size of up to 23,425 cases and 236,814 controls.

212 betes alleles will be associated with BMI in sample sizes of >500 000 if the prevalence of those dise

213 trials and equivalently reduce the required sample sizes of clinical trials.

214 Furthermore, because of various constraints, sample sizes of individuals can be quite small (say <50

215 studies and 12 previous systematic reviews (sample sizes of primary studies ranging from 62 to more

216 The small sample sizes of some previous eQTL studies have limited

217 s, covering a subnanosecond time window with sample sizes of tens of nanometers and thus suitable to

218 Due to modest effect sizes, large sample sizes of tens to hundreds of thousands of individ

219 oot, and mouth disease (HFMD) based on large sample size or evaluation of detection for more enterovi

220 or preservation of holotype specimens, small sample size, or the lack of evidence for ecological dive

221 cing data accumulate in progressively larger sample sizes, our method will enable increasingly high-r

222 rived from multiple measures, maximizing the sample size over different age ranges.

223 included smaller P value (P < 0.001), larger sample size (P = 0.001), larger number of events (P = 0.

224 Study sample size, patient age, follow-up time, timing of MRD

225 he evidence is limited and hampered by small sample sizes, paucity of randomized control studies and

226 For required sample size, PFS with a motor diagnosis or total motor s

227 This study is limited by its sample size, precluding more detailed analyses of driver

228 Strengths include large sample size, prospective design, and virtually complete

229 its in the cell structure (microvilli), (ii) sample size (QB waveform), (iii) latency distribution (t

230 mplemented adjusting for stage distribution, sample size, race, year of publication, type and quality

231 esigned to work under the high-dimension low-sample-size regime, and can borrow information across di

232 rganic components, together with the minimal sample size required, demonstrate the value of this new

233 pproach is not yet practically feasible with sample sizes required for adequate statistical power.

234 a powerful strategy for achieving the large sample sizes required for identification of variants und

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

236 We propose to circumvent this large sample size requirement by evaluating relationships betw

237 be decreased by 5 cm H2O or more can reduce sample size requirement by more than 50% without increas

238 perimental treatments can reduce the overall sample size requirement by up to 30% compared with stand

239 importance of studying minority populations; sample size requirements and efficient study designs for

240 This inflates sample size requirements and increases the cost and diff

241 ug of C of most AAs was +/-0.02 Fm, although sample size requirements are larger for similar uncertai

242 black women at high risk for HIV infection, sample size requirements for an RCT with HIV incidence a

243 Improved sensitivity predicts smaller sample size requirements when ADCOMS is used in early AD

244 ge number of hypotheses and relatively small sample sizes, results from whole-genome expression studi

245 mbined to reduce the model dimensions at the sample size; second, a grouped penalized regression was

246 Additional studies in larger sample sizes should be performed to confirm if overall p

247 Because of the large sample size, some statistical differences lacked clinica

248 value selection, treatment method, country, sample size, stage and cancer type.

249 tion, particularly of the results from small sample size studies.

250 lty and validity by focusing on recent large sample-size studies that have been validated in a separa

251 o cancer therapeutics to choose an alpha and sample size that minimize the potential harm to current

252 We give simple sufficient conditions on sample sizes that ensure existence of epsilon-optimal tr

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

254 wnstream research is challenged by the small sample size, the rare event nature, and the multiple tes

255 Importantly, when plotted as function of sample size, the raw moments of the SADs of arthropods h

256 Despite a limited sample size, the results suggest that the intervention p

257 s on the number of transmitted lineages, the sample size, the time of the sample relative to transmis

258 For medium or large sample sizes, the Bon-EV procedure has improved FDR cont

259 Even for relatively moderate sample sizes, the proposed testing framework is able to

260 Although non-comparative with a small sample size, these data support the use of this regimen

261 utious due to multiple comparisons and small sample size, these results provide preliminary evidence

262 s pattern was observed with relatively small sample sizes, these data indicate that variations in COM

263 Despite its small sample size, this trial showed that, in patients with EG

264 reference panel needs to scale with the GWAS sample size; this has important consequences for the app

265 ally expressed genes, and then calculate the sample size to achieve a desired average power while con

266 hic measurements are limited by insufficient sample size to assess the effects of age, sex, race, and

267 eity of these disorders often requires large sample sizes to identify a critical mass of individuals

268 ach should be useful in research with modest sample sizes to investigate developmental, multivariate

269 Poisson prior demonstrates less bias toward sample size under certain conditions than the GLMs or pr

270 ng significant differences to be detected at sample sizes up to 20% smaller than in naive trials.

271 ies are driven by the malaria diagnostic and sample size used to inform the model.

272 benefit for ketamine was found although the sample size used was small; however, the results exclude

273 ents and thus reconstruct the SAD for larger sample sizes using a procedure borrowed from the field o

274 Sample size varied between 30 and 352 participants, and

275 Sample sizes varied between experiments and are noted in

276 The total sample sizes vary among projects because of missing data

277 The final analytic sample size was 1,124,162 biological children.

278 The estimated sample size was 47 patients; maintenance was deemed effi

279 Study sample size was between 24 and 252 patients in exclusive

280 The sample size was calculated for the exploratory efficacy

281 Sample size was calculated to provide 90% power and a di

282 The required sample size was estimated for a 2-arm prediagnosis clini

283 Only 56% of the intended sample size was recruited.

284 The target sample size was set to demonstrate a response rate of 40

285 Given that our sample size was underpowered to detect genome-wide signi

286 ng non-parametric methods when the simulated sample size was up to 5,000 individuals.

287 exclude a small effect size due to a limited sample size, we further analyzed imputed rs2735383 genot

288 Despite a modest sample size, we identified 2,707 independent caQTLs (at

289 With this small sample size, we observed significant reduction of white

290 Utilizing this unprecedented sample size, we show that while highest individual sampl

291 etics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide associati

292 , 68%, and 60%, respectively, and unweighted sample sizes were 16 410, 15 425, 13 538, and 15 624, re

293 Complete case sample sizes were 401 917 (waist circumference models),

294 Though sample sizes were generally too small to conduct formal

295 with mitoxantrone data and showed that small sample sizes were sufficient to achieve 80% power (16, 4

296 This study was limited by the small sample size, which was a result of the rarity of individ

297 igh HLA polymorphism necessitates very large sample sizes, which have not been available until recent

298 We show that for finite sample sizes with increasing number of null predictors,

299 regardless of world region, national income, sample size, year, or mean HAZ in the 0-3 month age band

300 al modifiers (world region, national income, sample size, year, or mean HAZ in the 0-3 month age band