ライフサイエンスコーパス: variance

1 line: 4.4 (3.5; 5.8) (P = 0.016, analysis of variance).

2 the bone surface and analyzed by analysis of variance.

3 also evidence to support underlying genetic variance.

4 or structural) exists at a defined level of variance.

5 statistics toward a given mean with minimal variance.

6 cantly increases the proportion of explained variance.

7 life were assessed using one-way analysis of variance.

8 on loci explain only a small fraction of the variance.

9 distributions with different means and equal variance.

10 ighted each summary statistic by its inverse variance.

11 nvironmental factors explained the remaining variance.

12 oups using chi-squared tests and analysis of variance.

13 essed with Poisson regression or analysis of variance.

14 co-expression that is due to shared genetic variance.

15 n) associated with an additional 3.2% of the variance.

16 plaining approximately 12% of the phenotypic variance.

17 sk scores account for 0.9 to 2.6% of the HRV variance.

18 trial were computed by the t test with equal variance.

19 mposite model using multivariate analysis of variance.

20 and statistically compared using analysis of variance.

21 that in control regions by using analysis of variance.

22 ECT E3 ubiquitin ligase that may explain the variance.

23 n additive maternal and common environmental variances.

24 S-SCZ explained 2.0% (p = 6.15e(-16)) of MDD variance, 2.6% (p = 2.88e(-10)) for MDD with higher symp

25 differences from young controls (YC) and YC variance according to reference region.

26 o define kinematics synergies that maximized variance across either different object locations or gri

27 ne's test to assess equality of the residual variances across genotype groups.

28 We call this method Differential Variance Analysis (DVA), since it focuses on the varianc

29 t energy input of 54 J/g and pH of 12.0, and variance analysis indicated that pH value played a more

30 Non-stationary variance analysis revealed a reduction in maximal GABA-e

31 order explained 0.6% (p = 2.97e(-05)) of MDD variance and 1.1% (p = 1.30e(-05)) for MDD with age at o

32 s and spatial datasets to look for trends in variance and autocorrelation (persistence).

33 l parameters were assessed using analysis of variance and Bonferroni post hoc tests.

34 r moments of the stochastic variables (mean, variance and covariance).

35 chological adaptations sensitive to seasonal variance and food shortages.

36 re small contributors to the total technical variance and have only minor effects on downstream analy

37 plaining 81% (95% CI, 78%-84%) of phenotypic variance and individual environmental factors explaining

38 owerful against alternatives with a shift in variance and is accurate in change-point estimation, as

39 Analysis of variance and Mann-Whitney U tests with post hoc correcti

40 This model accounts for 59% of the total variance and presents a good fit with the data (root mea

41 and is an increasing function of the spatial variance and skew in fitness.

42 ating triggered activity, the latency period variance and SR Ca load had the greatest influences.

43 Importantly, both the variance and the non-Gaussian statistical features in di

44 ups were determined with one-way analysis of variance and Tukey multiple comparisons tests.

45 ared between groups by using the analysis of variance and were analyzed relative to group, total cumu

46 d two-sample Welch's t-test assuming unequal variance and Z test of comparison of proportions.

47 t negative binomial distributions with their variances and means linked by local regressions, and in

48 ing values and estimates of additive genetic variance, and create spurious temporal trends in predict

49 in "trans" and explaining 10.3% of eNO level variance, and rs1441519 (P = 1.6 x 10(-6)), which is loc

50 we show that ORNs adapt to stimulus mean and variance, and that adaptation and saturation contribute

51 Analysis of variance (ANOVA) and receiver operating characteristic (

52 numerical techniques along with Analysis of variance (ANOVA) and Taguchi optimization method for opt

53 An analysis of variance (ANOVA) was performed to compare mean IOP value

54 Kruskal-Wallis analysis of variance (ANOVA)-on-Ranks with post-hoc Mann-Whitney U-t

55 Autoregressive variance appears to be driven by multi-day recovery from

56 es to a Gaussian distribution whose mean and variance are determined by physically meaningful paramet

57 Hence, all the data for variance as a function of mean expression collapse onto

58 est eQTL explaining 87% (0.052/0.060) of the variance attributed to all identified cis- and trans-eQT

59 There was variance between countries but no significant temporal t

60 unveil anchors in position 2 or 3 with high variances between allotypes, and a less variable anchor

61 ery of analytes with statistically different variances between sample classes.

62 .05E-05, 1-way repeated measures analysis of variance, Bonferroni threshold).

63 tes can be either severely biased or of high variance, both leading to spurious results; (ii) even if

64 We use a multiple-variance Brownian motion approach in association with ev

65 coefficient of variation (rather than SD or variance), but distinct best metrics were seen for indiv

66 Reversible mutagenesis overcomes clonal variance by permitting functional annotation of the geno

67 nmental factors, we demonstrate that genetic variance can be detected for dog personality traits asse

68 In the present context these variances come from the regressions of shape on some exo

69 Analysis of variance compared differences among conditions.

70 strong additive genetic influences based on variance components analyses, and that the common geneti

71 sulin resistance] by using family data and a variance components approach.

72 cted genetic values, and these two resultant variance components are used for calculating the unbiase

73 We estimated h(2)g using a variance components method with variants having a minor

74 We used these variance components to design an algorithm for a managed

75 U cannot be used in the presence of multiple variance components.

76 imple Cox model, robust standard errors in a variance-correction model, random effect in a frailty mo

77 Variance-correction models may be useful if predictor se

78 urement is characterized by a coefficient-of-variance (COV) ranging from 2% to 8% across this entire

79 white matter integrity was investigated with variance decomposition methods.

80 curred primarily at odor transduction, while variance-dependent gain control occurred at both transdu

81 PC2 ('transience'), accounting for 27% of variance, described how much individuals used feeders an

82 35 nt partial deletion, were the only major variance detected between virulent and avirulent isolate

83 We also obtain an upper bound on the variance due to differences in behavior between the two

84 anterior cingulate cortex, 24%; analysis of variance, effect of diagnosis: P < .001 to P = .004).

85 r associations, several studies investigated variance eQTLs.

86 ies were weighted according to their inverse variance estimates.

87 hin-cluster correlation by a robust sandwich variance estimation approach, and assessed an interactio

88 Poisson regression with robust variance estimation provided prevalence ratios and 95% c

89 ssessed using Poisson regression with robust variance estimation.

90 generalized estimating equations and robust variance estimators and included adjustment for plasma H

91 The results confirm that parameter recovery variance exhibits power law decay as a function of the l

92 samples is needed to more precisely estimate variance explained and to establish the individual varia

93 iate GCTA-GREML found that the proportion of variance explained by all common single-nucleotide polym

94 probes, on average the proportion of genetic variance explained by all eQTL (hCOJO(2)) was 31% (0.060

95 The largest proportion of the variance explained by any biomarker (2.8%) and the large

96 population-level outcomes over and above the variance explained by article characteristics and common

97 The amount of variance explained by each feature space was then assess

98 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with s

99 We propose to estimate the proportion of variance explained by regression on genome-wide markers

100 phrenia battery yielded a single factor (54% variance explained) that served as the measure of genera

101 P European ancestry individuals (9.4% of the variance explained, p < 10(-6)), but lower in individual

102 NPA DeltaBPND (repeated-measures analysis of variance, F1,26 = 1.9, p = .18) between HCs and subjects

103 11)C]NPA BPND (repeated-measures analysis of variance, F1,26 = 3.34, p = .08) between the SCH and HC

104 An inverse variance fixed effects model was then used to undertake

105 Inverse variance fixed-effects models with odds ratio (OR) as th

106 mong variables was assessed with analysis of variance followed by linear regression.

107 significant positive predictor of the error variance for acute (R(2) = 0.20; P < 0.0001) and daily (

108 models revealed significant additive genetic variance for body weight, leg length, parasite burden, h

109 nd TERS data for each ligand indicate larger variance for nonspecific ligand-receptor interactions.

110 djusted models explained moderate amounts of variance for outcomes defined as risk of relapse (R(2)=0

111 We identified substantial genetic variance for several traits, including fetching tendency

112 measures-range difference and between-group variance-for adenocarcinoma rose by 3.2% and 6.8% per ye

113 ogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests n

114 roaches by comparing analytical variances to variances from statistical Monte Carlo simulations.

115 One assumption specifies whether the variance function of the number of parasites per host in

116 .33E-04, 1-way repeated measures analysis of variance); >90% were directionally consistent and reache

117 By weaning, genetic (co)variances had somewhat declined in weight and were not s

118 However, greater error variance in acute and daily EI with increasing RMR value

119 ic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 x 10(-7)).

120 r AO, together explained 41% of the observed variance in annual C. tetragona growth and likely repres

121 ve processes with the statistical pattern of variance in behavioural measures that partly reflect tho

122 that cerebellar metrics accounted for extra variance in both motor and cognitive performances, with

123 %-7.2%; P=1.00 x 10(-17)) of the total trait variance in both sexes, and we identified a twin heritab

124 ctors that explained an additional 31.02% of variance in brain activation patterns, associated with d

125 between microbes which explains about 10% of variance in co-occurrence data, but genome composition w

126 predictor as well, it explains up to 4% the variance in co-occurrence when all genomic-based indices

127 etention pattern significantly explained the variance in cognitive performance and clinical outcome m

128 ultimodal pattern associations explained the variance in cognitive performance and clinical outcome m

129 ether accounting for 20% (95% CI 17%-23%) of variance in cognitive test scores.

130 7.5% and 5.6% of the variance in compulsory admission occurred at LSOA level

131 ch resulted in a high degree of cell-to-cell variance in cytokine exposure.

132 Small-scale societies show higher but more variance in DCI and CL than contemporary states.

133 In order to estimate the variance in depression explained by the genetic vulnerab

134 evolving invasions exhibit greater mean and variance in dispersal distance.

135 shared by twin pairs explained all remaining variance in drink preferences.

136 The MPS approach predicted 10.9% variance in educational achievement, 4.8% in general cog

137 omposition and RMR do not explain the entire variance in EI, suggesting that other factors may contri

138 patients combined explained over 90% of the variance in enlarging lesion volume over the subsequent

139 DEC-medicated salt also lowered between-site variance in extinction timelines, especially when combin

140 genes account for about 15% of the observed variance in fMRI connectivity (and about 10% in alpha-ba

141 Our results indicate that controlling for variance in geographic spread in the fossil record signi

142 ontent or PLIN5+ LDs increased the explained variance in GIR (74.7% and 80.7% for PLIN5 protein conte

143 les, and initial studies of inter-individual variance in HCC have implicated genetic factors.

144 PRS did not explain variance in HCC.

145 from conscious Cx36 KO mice revealed higher variance in heart rate and blood pressure during rest an

146 uction potentials for x < 0.26, though large variance in literature values for certain material param

147 (SNPs) explained between 20% and 29% of the variance in MDD risk, and the heritability in MDD explai

148 a median of 75.7% (IQR 45.8% to 92%) of the variance in methylation associated with ethnicity.

149 However, we show that most of the variance in microbial time series is non-autoregressive.

150 explain approximately 39% of the phenotypic variance in MPB and highlight several plausible candidat

151 Z patients, the latter accounting for 37% of variance in negative symptoms.

152 Instead, increased variance in phyllotaxis in vip3 was observed at the meri

153 d [Formula: see text], and the environmental variance in population growth rate, [Formula: see text]

154 slation and explains approximately 5% of the variance in protein expression.

155 The apparent similarity of the variance in recombination rate among individuals between

156 tuations toward a uniform random state whose variance in regions of volume [Formula: see text] scales

157 etical and molecular approaches, we compared variance in reproductive success (V k*) and effective po

158 We utilized the large variance in response to antidepressant treatment occurri

159 This indicates that 29.66% of the total variance in right hippocampal volume is explained by HbA

160 Overall, the gBGC model explains 70% of the variance in SCU among genes.

161 strapped subsampling approach to account for variance in sequencing depth, and, coupled with a data s

162 are important, determining up to 85% of the variance in some cone system response parameters.

163 hese traits is variable, leading to enhanced variance in speed among replicate population expansions.

164 About 33% of the variance in students' performance is predicted by four p

165 , SERPING1) made unique contributions to the variance in superior frontal cortical thickness among al

166 strel that explains over half of the genetic variance in susceptibility to the Drosophila C virus (DC

167 counting for three-fourths of the phenotypic variance in Taiwan.

168 Variance in telomere dynamics among individuals is the p

169 Together, increased variance in temperature and lag effects interacted with

170 We propose a model in which the local variance in tension between junctions determines whether

171 ion of the data while preserving most of the variance in the data.

172 ith genetic load explaining up to 83% of the variance in the drug response.

173 han, PC2-tyrosine) that captured significant variance in the fluorescence spectra.

174 xed domains are likely to segregate when the variance in the intermolecular interaction strengths exc

175 s shown to capture the most inter-individual variance in the metabolic phenotype, which is of importa

176 stabilizing selection, which acts to reduce variance in the population without necessarily modifying

177 tivity in its ability to explain independent variance in the responses of individual voxels.

178 for its effect on the expression of genetic variance in the wild.

179 accounting for a considerable amount of the variance in these measures.

180 As a consequence, the variance in total breeding values was reduced to almost

181 es the feasibility to study phenotypic trait variance in tractable model organisms using unbiased mut

182 tutes the remaining approximately 80% of the variance in translation and explains approximately 5% of

183 ned is a measure of smear, and the resulting variance in unbiased single measurements depends on this

184 ve organs along the stem exhibited increased variance in vip3-1 and vip3-2 compared with the wild typ

185 iated approaches, by province, to respond to variances in care-seeking patterns and the capacities of

186 Our BAT method also had smaller variances in estimation of two-point recombination fract

187 eneity only explains a small fraction of the variances in longevity (5.9%), age at first reproduction

188 distribution, toxickinetic, and genotoxicity variances in murine animals.

189 While the largest variances in the latitudinal and longitudinal WPC locati

190 es and other entropic factors leads to large variances in the observed molecular conductance, especia

191 annual and seasonal timescales, the largest variances in the WPV and HC are due to the multi-decadal

192 Concomitantly, task-relevant shared variance increases, consolidating a manifold containing

193 real-time evolution of both correlation and variance indicators.

194 and genetic gain, in most GS models genetic variance is estimated from training samples with many tr

195 Sample variance is greatly reduced after normalization, hence t

196 northern hemisphere where temporal climatic variance is high.

197 In the proposed method, the genetic variance is simply the variance of the genetic values pr

198 icted through cross validation, the residual variance is the variance of the differences between the

199 and jitter) and shape (amplitude and width) variance, it is the mean delay that is critical to noise

200 nd acceptable repeatability (coefficients of variance </=30%) for 84.5% of about 9000 endogenous feca

201 in a square meter, regardless of whether the variance-mean relationship of parasites per host individ

202 We find empirically that the variance-mean relationship of the numbers of parasites p

203 fied common variants by fixed-effect inverse-variance meta-analysis.

204 ata were pooled by using the generic inverse-variance method with random-effects models and expressed

205 s ratios (ORs) by use of the generic inverse variance method with the use of random-effects models.

206 In this report, we show how spectral variance observed in surface-enhanced Raman scattering (

207 cal mixture model to estimate the biological variance of a gene and detect differentially expressed g

208 on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surroun

209 The accountability for the phenotypic variance of AF was 19.9% for genetic factors (heritabili

210 t specific heating loads resulting in larger variance of calculated mean SLP values.

211 In FRDA, 31% of the variance of cerebellar signs with the CCFS and 41% of th

212 gene explained 0.9% of sex- and age-adjusted variance of depressive symptoms in the discovery study,

213 Therefore, a significant proportion of the variance of entropy should be attributed to the malignan

214 lele as a function of phenotypic memory, the variance of expressible phenotypes, the rate of environm

215 Analyses of variance of FA and BOLD PSC were used to determine main

216 eal-time indicators based on correlation and variance of gray levels were optimized and then further

217 om the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unsel

218 in the mean monsoon rainfall and a weakening variance of its low-frequency ISO (LF-ISO) cycle.

219 univariate repeated-measurements analysis of variance of joint angle minima and maxima.

220 ve a more precise estimation of the mean and variance of measurement.

221 to assess the reproducibility and biological variance of metabolic phenotypes.

222 of network topological features such as the variance of the degree distribution, i.e. the distributi

223 oss validation, the residual variance is the variance of the differences between the observed phenoty

224 ance Analysis (DVA), since it focuses on the variance of the differential frames, obtained subtractin

225 populations, scaling up the expectation and variance of the dynamics of an ensemble of populations.

226 parsimonious model, explaining > 99% of the variance of the full model, comprised 8 predictors: age,

227 d method, the genetic variance is simply the variance of the genetic values predicted through cross v

228 ed fail to explain a large proportion of the variance of the traits/diseases.

229 dex accounts for as high as 75% of the total variance of typhoon intensity change.

230 Genetic (co)variances of AGD at birth and weight at birth differed i

231 rect statistical signatures, such as spatial variance or autocorrelation.

232 in robustness are not due to gene expression variance or dysregulation, but emerge from the nonlinear

233 and adolescents than in adults (analysis of variance, P = .0009).

234 ts of both T2 (repeated measures analysis of variance, P = .025) and T2* (P < .001).

235 One-way analysis of variance, paired t tests, concordance and Bland-Altman t

236 MDS), permutational multivariate analysis of variance (PERMANOVA) and random forest models.

237 GWAS, using SOJO increased the proportion of variance prediction for height by 65% without additional

238 n nanocrystalline Si-based materials using a variance-reduced Monte Carlo method with the full phonon

239 h produce uncorrelated and correlated neural variance, respectively, and examined how these signals'

240 Permutational multivariate analyses of variance revealed clear differentiation of ascidian symb

241 Decomposing variance revealed that covariation of bacterial clades w

242 ntial tilt model that captures both mean and variance signals but only examining one CpG site at a ti

243 d regularization that captures both mean and variance signals in DNA methylation data and takes into

244 e been developed that consider both mean and variance signals in order to improve statistical power o

245 ession changes were evaluated by analysis of variance (significant P value < .05), hierarchical clust

246 High-variance, slow-timescale primary odor representations ar

247 bited the highest stability with over 50% of variance specific to the child.

248 mpound Poisson mixed model (CP-fit), and the variance stabilizing transformed linear mixed model (VST

249 Data were analyzed by using analysis of variance, t test, or chi(2) test.

250 Statistical testing included analysis of variance, t tests, and permutation tests.

251 proposed here explain a larger proportion of variance than previously reported more complex methods t

252 neural responses independently predict more variance than psychometric measures.

253 st set, predicting 1.1%, 1.1%, and 1.6% more variance than the best single-score predictions.

254 WM and pons showed larger YC variances than other regions.

255 entify temporal and functional transcript co-variance that associates 5024 unnamed genes with distinc

256 eneous cell populations exhibit large clonal variance that can confound analyses and undermine reprod

257 his algorithm mimics attributes of discharge variance that drive fishery yield: prolonged low flows f

258 ngle protein complex may comprise functional variances that enable response and adaptation to varying

259 Groups were compared with analysis of variance, the Mann-Whitney U test, or the t test.

260 rajectory classes were tested by analysis of variance.Three body mass index (BMI; in kg/m(2)) traject

261 tinely isolated and subjected to analysis of variance to assess these NFC juices.

262 tests and with repeated-measures analysis of variance to compare groups on the rate of change in seru

263 phase imaging that relates refractive index variance to disorder strength, a parameter that is linke

264 leveraging both independent and coordinated variance to explore and consolidate neural patterns.

265 certainty approaches by comparing analytical variances to variances from statistical Monte Carlo simu

266 optimum) and imprecision (within-population variance) to the phenotypic mismatch (inaccuracy) of het

267 ary "targeting" step that optimizes the bias-variance tradeoff for the target parameter.

268 s and Permutational Multivariate Analysis of Variance Using Distance Matrices (PERMANOVA) were used t

269 A 2x2 analysis of variance using voxel-wise subsampling permutation tests

270 Estimates of mutational variance (VM) for male mating success and competitive fi

271 ions reported to USEPA or CARB, though large variance was observed and the reporting database did not

272 Significant variance was observed for MR imaging and direct MR arthr

273 Analysis of variance was performed to evaluate linear, quadratic and

274 lues (SUVs) were determined, and analysis of variance was performed, with group (smoker vs non-smoker

275 Analysis of variance was used for comparison of lipid profile, where

276 ransformation, repeated measures analysis of variance was used to detect groupwise regional and zonal

277 Analysis of variance was used to test the overall between-group diff

278 To account for between-trial variance we used mixed-effects modelling with a random e

279 ng that other factors may contribute to this variance.We aimed to investigate the associations betwee

280 schizophrenia were combined using an inverse-variance weighted fixed-effects approach.

281 Using inverse-variance weighted Mendelian randomization analysis, we f

282 the findings were then pooled using inverse-variance weighted meta-analysis.

283 ian randomization analyses using the inverse-variance weighted method to test for causality between l

284 A variance weighted t-test was used to identify differenti

285 traocular bleeding were pooled using inverse-variance, weighted, fixed-effects meta-analysis.

286 specific results in a fixed-effects, inverse variance-weighted meta-analysis.

287 s across studies using fixed-effects inverse-variance-weighted models, PCSK9 LOF variants were associ

288 s were meta-analyzed centrally using inverse-variance weighting.

289 Principal component analyses and analyses of variance were carried out with the aim of studying trend

290 est, paired t test, and Friedman analysis of variance were conducted to evaluate differences in noise

291 nn-Whitney test, and the one-way analysis of variance were used to compare ADCs between patient subse

292 In males, variances were small and there was difficulty in discrim

293 less of an autoregressive component to their variance, which suggests that diet is a major driver of

294 Managing desired components of discharge variance will lead to greater efficiency in the Lower Me

295 Our data show that NOx fluxes are largely at variance with modelled emission projections, suggesting

296 were compared by using a one-way analysis of variance with post hoc analysis for statistically signif

297 location explained 57% of the between-study variance, with CTT significantly longer in studies condu

298 sion, age explained 52% of the between-study variance, with older age associated with lower PAC-QOL s

299 ly by using the Friedman two-way analysis of variance, with P < .05 considered to indicate a statisti

300 Differences in the spectral variance within the SERS and TERS data for each ligand i