ライフサイエンスコーパス: GEE

1 GEE analysis identified an interaction between the prese

2 GEE mice exhibit decreased GABAergic transmission onto D

3 GEE models showed that children had an exponential incre

4 GEE revealed that higher autism and ADHD traits and lowe

5 GEE-MEGAN reduces BVOC emission estimates by 31% and dec

6 nix-based cases (2.1 vs. 1.0 years; P=0.002, GEE model).

7 on earlier than limbus-based cases (P=0.002, GEE model).

8 common with fornix-based operations (P=0.01, GEE model).

9 The first GWA approach applied a GEE-based model to identify gene-based associations with

10 In a GEE linear regression model, the presence of F12-46C/T w

11 Additionally, GEE analysis revealed that serum vitamin D levels were n

12 Adjusted GEE models showed that living below poverty level was as

13 In adjusted GEE models, all levels of social media use were associat

14 activity improved motor performance in adult GEE(P0-P10) females.

15 Welch's t-test, ANOVA, and GEE were used to assess any significant differences betw

16 ms currently available for doing the REM and GEE modeling.

17 d late-onset severity showed no association; GEE OR = 1.65 [0.92; 2.94], p = .08 and 1.01 [0.97; 1.06

18 to be graded as higher and to be avascular (GEE model, both P < 0.0001).

19 ites were individually associated with IR by GEE (all false discovery rate-adjusted P values</=0.026)

20 al pulmonary function (REM) and categorical (GEE) types of respiratory data.

21 aeroallergen sensitization during childhood; GEE OR = 1.68 [1.08; 2.62], p = .02 and 1.08 [1.03; 1.12

22 The most potent inhibitor (Cinn-GEE) displayed a K(D) value of 1.3 microM against the N-

23 innamaldehyde resulted in an inhibitor (Cinn-GEE) of substantially increased potency against all thre

24 ((1)H) and delta 201 ((13)C), the PTP1B/Cinn-GEE complex showed three distinct cross-peaks at delta 7

25 site-directed mutagenesis and by using Cinn-GEE specifically labeled with (13)C at the aldehyde carb

26 sm of inhibition was investigated using Cinn-GEE specifically labeled with (13)C at the aldehyde carb

27 While Cinn-GEE alone showed a single cross-peak at delta 9.64 ((1)H

28 Similar experiments with Cinn-GEE that had been labeled with (13)C at the benzylic pos

29 In the combined GEE model including adalimumab and etanercept, a body-ma

30 xposure during the first ten postnatal days (GEE(P0-P10)), which mimics ethanol consumption during th

31 ape heterogeneity and human-driven dynamics, GEE-MEGAN significantly improves BVOC emission estimates

32 e, 2,3-butanedione, and the reagent pair EDC/GEE, are used together to pinpoint the binding sites of

33 observation data on the Google Earth Engine (GEE) platform and machine learning-based analysis enable

34 a 1-m resolution on the Google Earth Engine (GEE) platform using NAIP imagery and LiDAR-derived canop

35 ping layers V1.4 on the Google Earth Engine (GEE) to map and monitor the effects of climate change on

36 ed approach integrating Google Earth Engine (GEE), remote sensing techniques using Sentinel-2 imagery

37 data processed through Google Earth Engine (GEE).

38 alyses, and generalized estimating equation (GEE) analyses were conducted to examine the relationship

39 models, and generalized estimating equation (GEE) analysis.

40 3) to build generalized estimating equation (GEE) and generalized linear mixed-effects (GLME) models

41 ession with generalized estimating equation (GEE) and interrupted time-series (ITS) models were used

42 Generalized estimating equation (GEE) and random-effects models were used to test for lin

43 mined using generalized estimating equation (GEE) and within-twin pair analyses, adjusting for potent

44 n using the Generalized Estimating Equation (GEE) approach.

45 The generalized estimating equation (GEE) logistic regression confirmed that clot size and st

46 Generalised Estimating Equation (GEE) logistic regression models investigated association

47 a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epide

48 A general estimating equation (GEE) model was used to calculate the odds ratio (OR) for

49 d model and generalized estimating equation (GEE) model with repeated measures.

50 ongitudinal Generalized Estimating Equation (GEE) model, each 10 mg increase in prednisone dose is as

51 he multiple generalized estimating equation (GEE) model, pseudophakia had a statistically significant

52 Generalized estimating equation (GEE) modeling with use of an unstructured binomial logit

53 Generalized estimating equation (GEE) models informed the mortality risk within 3 mo for

54 We used generalized estimating equation (GEE) models to analyze changes among sites implementing

55 ression and generalized estimating equation (GEE) models to evaluate the association between log10-tr

56 Generalized estimating equation (GEE) models were fitted to compare covariate-adjusted pr

57 models and generalised estimating equation (GEE) models were run unadjusted and then adjusted for so

58 Generalized estimating equation (GEE) models were used to assess the significance of the

59 ested using Generalized Estimating Equation (GEE) regression due to their correlated data.

60 We fitted Generalized Estimating Equation (GEE) regression models to analyse repeated measurements

61 Generalized estimating equation (GEE) regression models were used to identify patient and

62 cores and a generalized estimating equation (GEE) was used to analyze the binary indicator for a PHQ-

63 Generalized estimating equation (GEE) was used to examine the associations of family and

64 Generalized estimating equation (GEE) was used to examine the associations of lipid speci

65 regression, generalised estimating equation (GEE), and receiver operating characteristic curves were

66 In a Generalized Estimation Equation (GEE) logit model for mothers (n = 179) and children (n =

67 l eye using generalized estimation equation (GEE) models that can account for within-subject correlat

68 ance using generalized estimating equations (GEE) and extended Cox models.

69 Generalized estimating equations (GEE) and latent profile analysis (LPA) were conducted to

70 A generalized estimating equations (GEE) approach was used for both clinical examinations an

71 method of generalized estimating equations (GEE) for CAL changes from baseline to the 3-month visit,

72 method of generalized estimating equations (GEE) for correlated data was utilized to determine the r

73 lyses, and generalised estimating equations (GEE) for the global (ie, any) pathogen analyses, with ad

74 ffects and generalized estimating equations (GEE) logistic models showed that reinfection risk was si

75 mputation, generalized estimating equations (GEE) longitudinally modeled GAHT and moderate-to-severe

76 The generalized estimating equations (GEE) method is commonly used to estimate population-aver

77 ample, the Generalized Estimating Equations (GEE) method tends to overestimate the effect size due to

78 using the generalized estimating equations (GEE) method to test for associations between initial occ

79 t with the generalized estimating equations (GEE) method with an exchangeable correlation structure b

80 )-weighted generalized estimating equations (GEE) methods in the context of a study of Kenyan mothers

81 ltivariate generalized estimating equations (GEE) model with a binomial distribution was used to asse

82 lculated using general estimating equations (GEE) models to compute the overall odds ratios (OR) for

83 CH, database), General Estimating Equations (GEE) models were used to estimate population-averaged pr

84 t test and generalized estimating equations (GEE) RESULTS: The median age was 66.2 years [IQR = 18.3]

85 ing to the Generalized estimating equations (GEE) test, the changes in quality of life score between

86 Generalised estimating equations (GEE) tested the association between anti-CarP antibodies

87 We used generalized estimating equations (GEE) to examine associations of prenatal and childhood D

88 pplied the generalized estimating equations (GEE) to examine the association between baseline annual

89 cted using generalized estimating equations (GEE) to examine the association of SCT with HbA1c levels

90 ined using generalised estimating equations (GEE) to incorporate inter-eye correlations.

91 method of generalized estimating equations (GEE) to test for associations between increase or decrea

92 Generalized Estimating Equations (GEE) were applied to account for the correlation between

93 Generalized estimating equations (GEE) were employed to perform a multivariable multilevel

94 ervations, generalized estimating equations (GEE) were used for regression modeling.

95 Generalized Estimating Equations (GEE) were used to compare males with females in terms of

96 Generalized estimating equations (GEE) were used to estimate the impact of BMI and overwei

97 s based on generalized estimating equations (GEE), as a potential alternative to full maximum-likelih

98 sion using generalized estimating equations (GEE), from which odds ratios (OR) were estimated and tes

99 PCA), the generalizing estimating equations (GEE), the trait-based association test involving the ext

100 method of generalized estimating equations (GEE), with an exchangeable working correlation to accomm

101 yzed using generalized estimating equations (GEE).

102 HV-6 using generalized estimating equations (GEE).

103 y by using generalized estimating equations (GEE).

104 ated using generalized estimating equations (GEE).

105 e by using generalized estimating equations (GEE).

106 yses using generalised estimating equations (GEE).

107 well-known generalized estimating equations (GEEs) for longitudinal data analysis, we focus on the co

108 sion using Generalized Estimating Equations (GEEs) to account for inter-eye correlation within subjec

109 ment using generalized estimating equations (GEEs) using difference in differences (DiD) with patient

110 ssion with generalized estimating equations (GEEs) were performed to evaluate the association of insu

111 e binomial generalized estimating equations (GEEs) were used to calculate rate ratios to assess predi

112 s fit with generalized estimating equations (GEEs) were used to estimate the association between soci

113 Generalized estimating equations (GEEs) were used to estimate the predictive value of regi

114 Generalized estimating equations (GEEs) with a log link and exchangeable correlation matri

115 lyzed with generalized estimating equations (GEEs), a patient-based statistical approach.

116 mplemented generalized estimating equations (GEEs), an extension of the generalized linear model acco

117 d included generalized estimating equations (GEEs), latent class growth modeling (LCGM), linear mixed

118 ession and generalized estimating equations (GEEs).

119 gradient (generalized estimating equations [GEE] risk ratio 27.2, 95% CI 1.2 to 619.6, p = 0.0386) a

120 Glycine ethyl ester (GEE) and ammonium chloride served as replacements for ly

121 ing methods of FPOP and glycine ethyl ester (GEE) labeling.

122 s obtained from 20% v/v glycerin in ethanol (GEE) and 20% v/v eutectic mixture of sucrose and citric

123 uced carbon uptake gross ecosystem exchange (GEE).

124 mouse model of gestational ethanol exposure (GEE), we show increased instrumental lever-pressing and

125 ical models of gestational ethanol exposure (GEE).

126 Predictive habitat models using GAM-GEEs provided robust predictions in areas where telemetr

127 [6]-Gingerol, GEE and EMSCEE demonstrated significant and concentratio

128 In GEE models, adjusted odds ratios per calendar year were

129 Here we introduce GEE-MEGAN, a cloud-native extension of the widely used M

130 n index) indicated that water stress limited GEE and inhibited Reco .

131 telephone calls, were evaluated using logit GEEs that adjusted for patient characteristics and proba

132 cally increasing endocannabinoid tone mimics GEE effects on cognition and synaptic transmission.

133 In a multivariable GEE model, later year of observation was independently a

134 ot associated with DeltaIOP in multivariable GEE.

135 ndent predictor of DeltaIOP in multivariable GEE.

136 Predictors of CR in multivariate GEE analysis were age (odds ratio [OR] = 0.97, p = 0.011

137 y than those who were negative (multivariate GEE adjusted for age, sex, smoking status, ACPA, and yea

138 Both (15)NH4Cl and (15)N-GEE could be crosslinked to the three glutamines in alph

139 Non-GEE segment-based analysis revealed that for the two rev

140 ased excitability of striatal CINs in DLS of GEE(P0-P10) females, indicating striatal CIN dysfunction

141 levels in the dorsolateral striatum (DLS) of GEE(P0-P10) female, but not male, mice.

142 n learning and execution, yet the effects of GEE on acetylcholine (ACh) and striatal dopamine release

143 These results indicated the potential of GEE and EMSCEE to attenuate nausea and vomiting and migh

144 urons reduces the elevated lever pressing of GEE mice.

145 According to the analysis results of GEE model, greater power of astigmatism was found to be

146 Altogether, these data shed new light on GEE-induced striatal deficits and establish potential ph

147 Ordinal GEE analysis indicated significant improvements in fatty

148 oth the achromatic pulsed-pedestal paradigm (GEE: beta [SE] = 0.35 [0.06]; P < 0.001) and the chromat

149 analysis for individual SNPs using the PBAT-GEE program indicated that SNP rs921451 was significantl

150 vidual SNP analysis performed using the PBAT-GEE program indicated that two SNPs in the AAs and four

151 e 6-month postoperative measurement periods (GEE, P < 0.0001).

152 619.6, p = 0.0386) and aortic regurgitation (GEE risk ratio 2.4, 95% CI 1.3 to 4.3, p = 0.0029).

153 etween early-onset AD and allergic rhinitis; GEE OR = 1.56 [1.01; 2.41], p = .04 and severity; GEE OR

154 R = 1.56 [1.01; 2.41], p = .04 and severity; GEE OR = 1.09 [1.05; 1.13], p < .001, whereas late-onset

155 These findings show GEE induces long-lasting deficits in cognitive function

156 Since GEE models include outcome data at all timepoints, these

157 Use of a standard GEE model including both scheduled and unscheduled visit

158 Among all subjects, GEE modeling identified a significant change in angiopoi

159 d to have near normal distributions and that GEE be used for categorical or non-normally distributed

160 The GEE and the classical Fisher combination test, on the ot

161 The GEE identified the ICL size minus the anterior chamber w

162 The GEE model has greater performance than the GLME model, h

163 The GEE model revealed that the risk of leak decreased with

164 The GEE model using clinical examinations showed a significa

165 Results from the GEE model indicated the odds of hyperuricemia increased

166 statistically significant covariates in the GEE models were: 1) baseline age; 2) level of glycemic c

167 tic models, conditional logistic models, the GEE models, and random-effects models by analyzing a bin

168 Thirdly, the GEE model of four hours duration augmented with static a

169 re and after seaweed consumption through the GEE.

170 While the GEE model suggested a significant association between th

171 % corrected (95% CI 73.3% to 82.3%) with the GEE method, and the SVT positive predictivity was 100.0%

172 This GEE model identified 1 significant locus, GRM7, which pa

173 In unadjusted GEE analyses, for a given fasting glucose, HbA1c values

174 ehavioral characteristics was assessed using GEE logistic regression.

175 he estimate obtained using the IIRR-weighted GEE approach was compatible with estimates derived using

176 2.3%, 3.5%), while use of the IIRR-weighted GEE predicted a prevalence of 1.5% (95% confidence inter

177 dependent and additive predictive value when GEEs were used (P < .001, P = .02, P = .002, respectivel

178 While GEE analysis revealed year-to-year variability, overall