ライフサイエンスコーパス: inferential

1 perimental evidence for this has so far been inferential.

2 f calcification in cartilage degeneration is inferential.

3 s between KvLQT1 and cardiac IKs are largely inferential.

4 cardiovascular disease, the evidence is more inferential.

5 ents: the 20-min group showed no evidence of inferential ability (52%), whereas the 12- and 24-hr gro

6 evidence for a specific relationship between inferential abnormalities and delusional severity in sch

7 ion data all show signatures consistent with inferential adjustments in the Bayesian insight model.

8 the treated population (ATT), has a distinct inferential advantage over estimands characterizing the

9 Thanks to a purpose-built Bayesian inferential algorithm, EPISPOT accommodates functional i

10 nto either the traditional associationist or inferential alternatives that have dominated comparative

11 Both descriptive and inferential analyses were done with 95% confidence inter

12 es, performed fixed effect and random effect inferential analyses, tested for heterogeneous findings,

13 We performed two different inferential analyses: Lag sequential analysis to define

14 prevalence of different types of stress and inferential analysis for stress and independent variable

15 tion of postoperative motor outcomes and the inferential analysis of strabismus surgery in infant eye

16 Our method, named heterologous inferential analysis or HIA, combines conservational inf

17 Inferential analysis revealed significantly impaired (AC

18 Our inferential analysis suggests that a high degree of conn

19 arious histogenesis, using cDNA microarrays, inferential and descriptive statistics, and dynamic mapp

20 Together, our findings characterize the inferential and functional nature of social attention's

21 in pacing, its mechanistic action is largely inferential and indeed somewhat controversial.

22 tudies face significant and often overlooked inferential and interpretational challenges; we briefly

23 degeneration in osteoarthritis is primarily inferential and is based on correlative data.

24 e and overly simplistic, whereas surveys are inferential and often confound temperature with other dr

25 ing of Indigenous fire management is largely inferential and open to debate.

26 n epidemiology, offering simple yet powerful inferential and predictive tools in the study of diverse

27 s explaining why metacognitive judgments are inferential and sometimes diverge from task performance.

28 However, this evidence is only inferential, and because examples are known in which qua

29 amics outcomes were modeled using a Bayesian inferential approach and Markov chain Monte Carlo estima

30 tems and phenological questions to which our inferential approach could be applied.

31 mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylo

32 Unlike inferential approaches that examine the effects of indiv

33 undertook three independent unsupervised or inferential approaches to characterize proteome dynamics

34 neuroscience framework for understanding the inferential architecture of the lateral PFC, drawing upo

35 Among the 40 inferential articles that studied 10 or more patients, o

36 yliforms and their unusual teeth provide the inferential basis for a wide range of feeding ecologies.

37 It also provides a formal inferential basis for deciding when the spot is blank, n

38 We also discuss the inferential benefits of using point pattern models to ch

39 esentation power of neural networks with the inferential capacity of hierarchical models.

40 This dynamic process presents a unique inferential challenge to low temporal resolution neural

41 e propose some constructive responses to the inferential challenges posed by the small explanatory po

42 history, admixture graphs present formidable inferential challenges, and there is an increasing need

43 stood because of severe data limitations and inferential challenges.

44 l need to overcome substantial technical and inferential challenges.

45 ield a consistent signal despite an array of inferential challenges.

46 al cortex (MFC)(7) is involved in making new inferential choices when the options have not been previ

47 epresentation that explains how people learn inferential cognitive maps of social relations from dire

48 ta for pooled analyses is feasible, and high inferential comparability may be achieved.

49 dies using cultured cells, from which mainly inferential conclusions have been drawn as to the relati

50 tion clear between experimental evidence and inferential conclusions while providing a framework in w

51 niques, studied 10 or more patients, and had inferential conclusions.

52 cessitate a different set of statistical and inferential considerations when compared to non-spatial

53 in appraisals/reappraisals may update active inferential CP self-models, which then mediate appraisal

54 marked-point-process regression was used for inferential cumulative burden analysis.

55 ecessary data for computational modeling and inferential data mining.

56 ussed: mechanistic dynamical simulations and inferential data mining.

57 rapy in 45% of all patients referred and had inferential/decision-making value in another 44%.

58 These inferential decisions are thought to engage a number of

59 anatomy and neuronal computation underlying inferential decisions.

60 it is unknown how information that leads to inferential deductions are encoded and manipulated at th

61 her fine-tuned MedFound to learn physicians' inferential diagnosis with a self-bootstrapping strategy

62 Reported p values are non-inferential due to hierarchical testing.

63 tial equivalence) and classification of this inferential equivalence as complete, partial, or impossi

64 The inferential equivalence of 3,551 cohort variables to the

65 hort variable with its reference definition (inferential equivalence) and classification of this infe

66 reference definitions and classifications of inferential equivalence; and 6) preparation and delivery

67 t lack representativeness and by inadvertent inferential error, and how GIScientists can lead toward

68 llustrate that scale limitations can lead to inferential errors in practice; yet to also show that ri

69 arahippocampal gyrus, was more activated for inferential errors in the donation than in the savings c

70 language, common in everyday speech, enables inferential errors that exacerbate perceived polarizatio

71 The authors suggest how to recognize inferential errors when they occur, describe how to prot

72 between studies and the high risk of type I inferential errors.

73 in secondary lymphoid organs, and we provide inferential evidence for a key role of the female reprod

74 he phospholipid bilayer, have yielded strong inferential evidence for an "umbrella-like" action of th

75 This finding (1) constitutes inferential evidence for the presence of functional VEGF

76 Inferential evidence indicates that macular pigments (lu

77 deaths across a range of study designs, and inferential evidence supports breast cancer screening fo

78 ls also have declarative memory, and whether inferential expression of memory depends on the hippocam

79 We present Spatially Transformed Inferential Force Map (STIFMap) which exploits computer

80 Thus, a statistical inferential formalism is needed to avoid imposing arbitr

81 o viral phylodynamics, we anticipate that an inferential framework developed around recombination wil

82 We propose an inferential framework for GSEA based on functional data

83 We analyse our data with a simulation-based inferential framework that can overcome some of the intr

84 The inferential framework that we develop here can be expand

85 a in January-February 2020, and developed an inferential framework to estimate the generation time di

86 mission embedded within a Bayesian synthesis inferential framework to jointly analyze syndromic, viro

87 Using a dynamical model-based inferential framework, we find that these mortality patt

88 n-herd transmission models within a rigorous inferential framework.

89 y expensive for large datasets, a variety of inferential frameworks and corresponding algorithms have

90 Because of its prospective and inferential functions, we hypothesized that it might be

91 Attempts to cross this inferential gap when comparing human intelligence to tha

92 rstood and operated, in that we rephrase the inferential goal as a classification problem, first pred

93 fining questions that make clear whether the inferential goal is descriptive or causal; 2) greater ut

94 Owing to high resource demands and varying inferential goals, current designs differentially emphas

95 The issues involved in obtaining inferential guarantees beyond consistency are briefly di

96 on, and have stronger and more interpretable inferential guarantees.

97 te how selection biases can pose substantive inferential hazards in observational studies of restorat

98 ght reduce precision at higher levels of the inferential hierarchy, biasing inference towards sensory

99 re, albeit suffering at times from immediate inferential imperfections as to their current state with

100 Inferential implications of admissions data on nearly th

101 We also discuss the inferential implications of community confounding and or

102 d one-sided p-values are used to reflect our inferential interest.

103 r ethnography; and (4) the pertinence of the inferential issues identified in the target article.

104 odified intention-to-treat analysis using an inferential joint model combining a mixed-effects model

105 ational memory was seen for the most distant inferential judgment (the B>E pair; sleep = 93%, wake =

106 dge of the hierarchy was tested by examining inferential judgments for novel "inference pairs" (B>D,

107 ts were tested on the trained pairs and made inferential judgments on novel pairings that could be so

108 ng superior performance for the more distant inferential judgments, a benefit that may operate below

109 ation with endogenous, internally generated, inferential knowledge and meaning.

110 e is known, however, about how and when this inferential knowledge emerges.

111 and prefrontal-parietal systems that enable inferential leaps through structural abstraction might c

112 sociated specifically with the adjustment of inferential learning on the basis of unpredictability.

113 We conclude with a discussion of the inferential limitations of neuroimaging and lesion studi

114 Inferential (linear) models identified a consistent nega

115 umptions and reconsidering the probabilistic inferential links between past material culture and cogn

116 note-text accurately, and some demonstrated inferential logic and external knowledge.

117 imental testing, computational modeling, and inferential logic.

118 ted using simulated datasets, validating our inferential machinery.

119 ependent young monkeys underwent testing for inferential measures of anxiety (ie, voluntary explorati

120 a moderately stressful novel environment for inferential measures of offspring anxiety (ie, maternal

121 thus provide direct empirical support for an inferential mechanism that naturally captures the charac

122 port relational memory network formation and inferential memory in the human brain.

123 mation of integrated memories and successful inferential memory performance.

124 uences might be important for supporting the inferential mental operations associated with the cognit

125 We outline an inferential method for performing one- and two-sample hy

126 In summary, the proposed inferential method provides an unbiased assessment of Pr

127 By applying the original inferential method using potential donor templates absen

128 it relationships estimated with conventional inferential methodology are likely to be significantly d

129 a software package for applying the Bayesian inferential methodology to problems in systems biology.

130 and cyclicity-were evaluated using Bayesian inferential methods in 142 men, naturally cycling women,

131 ent paper is twofold: (1) to devise a set of inferential methods on the correlation manifold and (2)

132 the-art of Bayesian phylodynamics and demand inferential methods with relatively low computational co

133 issues as well as the choice of study design inferential methods.

134 elying on pretrained classifiers or post hoc inferential methods.

135 are alleles, which remain poorly resolved by inferential methods.

136 ry data analysis prior to application of any inferential model and we present a framework to help sci

137 Here, we developed an inferential model built on the gene expression of multip

138 model accuracy) and bootstrapping (to enable inferential model comparison with simultaneous generaliz

139 estigating how brain mechanisms give rise to inferential, model-building explanations.

140 Our inferential modeling approach offers a framework for bio

141 evaluate habitat quality for jaguars and an inferential modeling framework adaptable to the conserva

142 Variable selection in inferential modelling is problematic when the number of

143 trices, employing an array of lesion-deficit inferential models responsive to the potentially distrib

144 d small sample sizes limit the complexity of inferential models.

145 ng limited availability of training sets for inferential models.

146 Statistical analyses included inferential non-linear models and free-text data mining.

147 l muscle growth and regeneration are largely inferential or do not directly address gene regulatory m

148 ent experimental techniques can provide only inferential or incomplete information about the protein-

149 rspective that potentially bridges these two inferential paradigms.

150 cult-to-render natural agent-based classical inferential paradoxes interfaced with task-specific envi

151 lausible architecture, it falls short of the inferential performance of belief propagation.

152 uals, phylogeographic studies have increased inferential power and the potential for applications to

153 Further exemplifying the inferential power of the dataset, we used NSD to build a

154 emonstrates a novel method that combines the inferential power of WQS and the predictive accuracy of

155 nown parameter values in order to assess the inferential power provided by each summary statistic.

156 y used in biogeographic studies have limited inferential power to separate the effects of historical

157 Great inferential power, however, carries a crucial vulnerabil

158 ays by this approach substantially increases inferential power, or the ability to detect differential

159 limitations of pandemic-era cohort size and inferential power, same-day discharge after gender-affir

160 To solve this inferential problem, we develop a quantitative test of l

161 imaging meta-analyses, address long-standing inferential problems in the neuroimaging literature and

162 In this work, we proposed a novel inferential procedure assisted by machine learning based

163 hat incorporates variable selection into the inferential procedure, for the identification of the imp

164 eing an infection source via this multi-step inferential procedure.

165 Inferential procedures are presented, and some extension

166 Classical statistical inferential procedures attempting to make valid inferenc

167 Our inferential procedures do not require sample splitting,

168 ver, given the latest findings that powerful inferential procedures for haplotype analyses can be con

169 clude the development of representations and inferential procedures for large-scale probabilistic inf

170 t end points, and we describe estimation and inferential procedures via inverse probability weighting

171 event endpoints, and describe estimation and inferential procedures via inverse probability weighting

172 bjects, 7 tasks, 3 resampling group sizes, 7 inferential procedures).

173 dels to assess which model best captured the inferential process and investigated whether it could se

174 tead, perceiving lifelikeness seems to be an inferential process and one might expect it to be cognit

175 results strongly support an active top-down inferential process in perception.

176 STATEMENT Perception can be thought of as an inferential process in which our brains integrate sensor

177 ision--and perception at large--is an active inferential process involving hierarchical brain systems

178 other factors (e.g. comprehension) with the inferential process of interest, and a failure to adequa

179 ver, for a teleological theory, rooted in an inferential process that extracts information about acti

180 on of communicative action is grounded in an inferential process that stems from fundamental computat

181 ysical-in this case neuronal-states, and the inferential process they entail.

182 by biasing perceptual decision-making - the inferential process underlying perception in which prior

183 eliance on prior beliefs formed early in the inferential process, a feature that correlated with incr

184 orating information presented earlier in the inferential process, may be a core computational mechani

185 tely assess and model the key aspects of the inferential process.

186 is bias is thought to reflect variability in inferential processes but empirical support for a cohesi

187 Alterations in inferential processes have long been proposed to underli

188 Affective reactions and inferential processes mediate the effects of emotional e

189 These findings suggest that inferential processes support transfer of rapidly acquir

190 ns influence observers' affective reactions, inferential processes, and behaviors across various doma

191 ome associations, it may impair more complex inferential processes, such as counterfactual learning f

192 sent either misremembering or the effects of inferential processes.

193 viously incompatible frameworks for temporal inferential processes.

194 l (and nonsocial) interaction, which trigger inferential processes.

195 gyrus is particularly involved during later inferential processing in story comprehension.

196 t-mode network, implicating these regions in inferential processing under increased uncertainty.

197 gyrus is particularly involved during early inferential processing, whereas the left hemisphere supe

198 being recruited when the task taps on higher inferential processing/mentalizing.

199 ument structure; (iv) logical operators; (v) inferential promiscuity; and (vi) abstract content.

200 We then examine the psychometric and inferential properties of combining EMA data with Kalman

201 As index properties are inferential properties of soils, changes in plasticity p

202 s from a simulation study designed to assess inferential properties of the models, and propose a modi

203 procedures with wide applicability and good inferential properties.

204 Models have been used for explanatory and inferential purposes, as well as in planning and impleme

205 t (Psittacus erithacus) abilities for visual inferential reasoning by exclusion were tested in two ex

206 rtex of neurosurgical patients performing an inferential reasoning task.

207 tion of separate memories forms the basis of inferential reasoning--an essential cognitive process th

208 ion in learning, blocking, often arises from inferential reasoning.

209 l for differential expression analysis using inferential replicate counts, extending the existing SAM

210 ing only the mean and variance from a set of inferential replicates ('compression') is sufficient to

211 xtend the Swish method to incorporate pseudo-inferential replicates and demonstrate improvements in c

212 ping reads and allows for the generation of 'inferential replicates', which reflect quantification un

213 Using these values, we generate 'pseudo-inferential' replicates from a negative binomial distrib

214 This paper systematically investigates the inferential reproducibility between the two approaches t

215 Inferential research commonly involves identification of

216 spatial context into the model denoised the inferential results and improved classification performa

217 Inferential results for tests based on these different m

218 Finally, integration may allow us to cross inferential scales through scaling complementarity.

219 stochastic platelet deposition model and an inferential scheme to estimate the biologically meaningf

220 This approach combines the inferential simplicity of WQS regression with the flexib

221 teaching through a common theoretical lens, inferential social learning provides an integrated accou

222 modelling flexibility and the ease of making inferential statements, these approaches are predominant

223 Datasets were analyzed with inferential statistic procedures.

224 DAVIS) to visualise the dataset, and applied inferential statistical analysis.

225 As with all inferential statistical methods, maximum likelihood is b

226 ing data were analyzed using descriptive and inferential statistical methods.

227 et their evaluation overwhelmingly relies on inferential statistical procedures.

228 tion of spatial techniques, based on GIS and inferential statistics (density analysis, hotspots tools

229 to improve the understanding and practice of inferential statistics among nursing researchers.

230 Cross-sectional data were analyzed using inferential statistics and exploratory structural equati

231 Between-group inferential statistics and machine learning were used to

232 Descriptive and inferential statistics assessed oral health outcomes and

233 The use of inferential statistics for QTL identification thus inclu

234 Inferential statistics included Chi-square, Pearson's co

235 Inferential statistics including chi-square and logistic

236 a combination of SAS 9.4 for descriptive and inferential statistics including logistic regression and

237 Inferential statistics support our proposed study design

238 ctive and reproducible comparison leveraging inferential statistics to bridge image data with other m

239 We also need to use descriptive and inferential statistics to measure, report, and analyze t

240 We apply inferential statistics to support the three-stage design

241 A number of descriptive and inferential statistics were performed using Stata 13.

242 Descriptive and inferential statistics were performed.

243 Limitations: The study was open label, no inferential statistics were planned, and only patients w

244 The study was open-label, no inferential statistics were planned, and sample sizes we

245 eatment assignments were not blinded, and no inferential statistics were planned.

246 Inferential statistics were used to compare the groups.

247 Inferential statistics were used to evaluate differences

248 Voxel-based morphometry and inferential statistics were used to explore GMV alterati

249 We employed unsupervised clustering, inferential statistics, and partial least squares discri

250 Descriptive and inferential statistics, both linear and multivariate reg

251 Using concepts of probability theory and inferential statistics, we present a comprehensive theor

252 data into effect sizes using descriptive and inferential statistics.

253 ety of packages tailored for descriptive and inferential statistics.

254 results compared using both descriptive and inferential statistics.

255 ersion 21 and analysed using descriptive and inferential statistics.

256 ersion 21 and analysed using descriptive and inferential statistics.

257 analysed statistically using descriptive and inferential statistics.

258 papers failed to report key descriptive and inferential statistics: the data needed to compute effec

259 The small sample size precluded use of inferential statistics; therefore, data were analysed us

260 qualitative shift toward increased use of an inferential strategy.

261 humans and nonhuman primates, we address the inferential strengths and limitations of lesion studies,

262 We briefly review its inferential strengths and weaknesses and present example

263 al expressions, replicating the fine-grained inferential structure characteristic of nonlinguistic th

264 The resulting experimental inferential structure determination (EISD) method is siz

265 The inferential structure determination (ISD) framework, whi

266 The inferential structure determination ensemble has similar

267 Overhauser effect peak intensity, we applied inferential structure determination to calculate the eCD

268 es in design of descriptive, predictive, and inferential studies; (4) innovative approaches to charac

269 rlying mechanism, these results offer strong inferential support for the hypothesis that cAMP signali

270 Likelihood-based inferential techniques, although controversial in the pa

271 rative approach, using different model-based inferential techniques, to analyse published datasets fr

272 38% of the 112 studies that used statistical inferential techniques.

273 ensoring of information and do not allow for inferential testing of the role that local processes pla

274 udinal analyses (12 trials [48%]), and basic inferential tests or general linear models (10 trials [4

275 Descriptive statistics and inferential tests were applied (p < 0.05).

276 abstract mental representations that support inferential thinking.

277 l is to help establish HMMs as a fundamental inferential tool for ecologists.

278 or the model to be useful as a predictive or inferential tool, some adjustments for the biology of th

279 roblems, using convex relaxation as the core inferential tool.

280 gitudinal DTI analysis, and developed global inferential tools using functional norms and a novel rob

281 racing genomics provides unique and powerful inferential tools.

282 w here that the human PFC has two concurrent inferential tracks: (i) one from ventromedial to dorsome

283 ts suggest a deeper cognitive source for the inferential typology than usually thought: Domain-genera

284 s have placed more emphasis on communicating inferential uncertainty (i.e., the precision of statisti

285 In contrast, we find that depicting both inferential uncertainty and outcome variability leads to

286 that the prevalent form of visualizing only inferential uncertainty can lead to significant overesti

287 Yet, the inherent inferential uncertainty in transcript-level abundance es

288 nd deriving transcriptional groups where the inferential uncertainty is too high to support a transcr

289 at the isoform level requires accounting for inferential uncertainty, caused by multi-mapping of RNA-

290 onparametric models do not take into account inferential uncertainty, leading to an inflated false di

291 ientific findings visualized as showing only inferential uncertainty, only outcome variability, or bo

292 oup of transcripts will have greatly reduced inferential uncertainty, thus allowing more robust and c

293 transcripts in an experiment based on their inferential uncertainty.

294 ate, in particular for transcripts with high inferential uncertainty.

295 ng the existing SAMseq method to account for inferential uncertainty.

296 an spectral signatures are commonly used for inferential understanding of the chemical environment fo

297 sing algorithm for grouping transcripts into inferential units that exploits the posterior correlatio

298 on - making it one of the biggest threats to inferential validity.

299 on of phenotypes, but have somewhat doubtful inferential value, at least when sample size is such tha

300 odeling to decouple biological variance from inferential variance.