ライフサイエンスコーパス: confounding variable

1 y measures the effect of a third factor (the confounding variable).

2 nd 0.010, respectively, after adjustment for confounding variables).

3 sifier in a classification task with a known confounding variable.

4 ion (APACHE) IV score, was not a significant confounding variable.

5 (P < 0.001) after adjustment for potentially confounding variables.

6 nd second halves of follow-up, adjusting for confounding variables.

7 ions, procedural differences, and unmeasured confounding variables.

8 positives due to the effect of covariates or confounding variables.

9 nce interval, 0.08-0.6) after adjustment for confounding variables.

10 l as to assess the robustness to potentially confounding variables.

11 estimated IQ after adjustment for potential confounding variables.

12 ttle fed their infants after controlling for confounding variables.

13 tcome at day 7 after adjusting for potential confounding variables.

14 fter adjustment for each other and potential confounding variables.

15 adjusting for the degree of relatedness and confounding variables.

16 models were constructed that controlled for confounding variables.

17 d by center and stage was used to adjust for confounding variables.

18 etween cases and controls, and to adjust for confounding variables.

19 tudies were not systematically corrected for confounding variables.

20 in this population even after adjusting for confounding variables.

21 ital affects outcomes independently of other confounding variables.

22 effect on ADR after controlling for multiple confounding variables.

23 CI) for cancer incidence after adjusting for confounding variables.

24 linear regression and adjusted for important confounding variables.

25 r varying lengths of follow-up and potential confounding variables.

26 dicting progression over time, adjusting for confounding variables.

27 dB/y faster; P = .04), after adjustment for confounding variables.

28 sted after adjustment for multiple potential confounding variables.

29 en after adjustment for multiple potentially confounding variables.

30 ts persisting after adjustment for potential confounding variables.

31 nd comparisons were adjusted for potentially confounding variables.

32 tures to be assessed in isolation from other confounding variables.

33 simple regression analyses were adjusted for confounding variables.

34 and CIs, adjusted for the maximal number of confounding variables.

35 d treatment outcomes, adjusted for potential confounding variables.

36 er day) were examined in models adjusted for confounding variables.

37 tolic function after adjusting for potential confounding variables.

38 development and HIV prevalence as potential confounding variables.

39 ted, applying log-linear models adjusted for confounding variables.

40 g generalized linear models, controlling for confounding variables.

41 en after controlling for several potentially confounding variables.

42 s both the method's power and the effects of confounding variables.

43 eneralized estimating equations adjusted for confounding variables.

44 quate control groups and poor adjustment for confounding variables.

45 ed significant when controlling for multiple confounding variables.

46 ic HCT, but these conclusions are limited by confounding variables.

47 be provided that simplify tasks and diminish confounding variables.

48 surgery type, while adjusting for potential confounding variables.

49 els and HT status and adjusted for potential confounding variables.

50 udy, especially with its risk for unmeasured confounding variables.

51 y, and analyses were adjusted for effects of confounding variables.

52 pital mortality while adjusting for baseline confounding variables.

53 potential biases associated with unmeasured confounding variables.

54 nteresting cluster structure associated with confounding variables.

55 collect information pertaining to potential confounding variables.

56 in diastolic performance is not due to known confounding variables.

57 ed whether differences could be explained by confounding variables.

58 h cataract development after controlling for confounding variables.

59 ards models were used to adjust for possible confounding variables.

60 ogistic regression)], adjusted for potential confounding variables.

61 , independent of a wide range of potentially confounding variables.

62 crease of 1640% (p < .0001), controlling for confounding variables.

63 while adjusting for a large set of potential confounding variables.

64 ion techniques with adjustment for potential confounding variables.

65 n groups, even after control for potentially confounding variables.

66 fferent countries and cannot be explained by confounding variables.

67 s of optimal donor lungs after adjusting for confounding variables.

68 the year and flare of disease for potential confounding variables.

69 general linear models adjusted for potential confounding variables.

70 a linear regression analysis to control for confounding variables.

71 of the year, with adjustment for potentially confounding variables.

72 rbic acid categories, adjusting for possible confounding variables.

73 regression models controlling for potential confounding variables.

74 over the following six years, independent of confounding variables.

75 as no longer significant after adjusting for confounding variables.

76 lity to adjust for a wide range of potential confounding variables.

77 Hazards regressions, while also considering confounding variables.

78 oint was graft survival after adjustment for confounding variables.

79 t these approaches all introduce potentially confounding variables.

80 l folate concentrations after adjustment for confounding variables.

81 ctors after adjustment for other potentially confounding variables.

82 s (logistic) regression models, adjusted for confounding variables.

83 or recipients, while adjusting for potential confounding variables.

84 on fat mass in relation to other potentially confounding variables.

85 he study end points correcting for potential confounding variables.

86 ric refeeding after adjustment for potential confounding variables.

87 Mexican American women after adjustment for confounding variables.

88 at age 18 years and several other potential confounding variables.

89 gression analysis, adjusting for potentially confounding variables.

90 nutrient concentrations after adjustment for confounding variables.

91 confidence interval (CI) after adjusting for confounding variables.

92 dies, glucocorticoids and age were two major confounding variables.

93 Adjusted HRs (aHRs) controlled for potential confounding variables.

94 a integration that intrinsically adjusts for confounding variables.

95 ce persisted after controlling for potential confounding variables.

96 ion, suicide attempt, suicide, and potential confounding variables.

97 across populations and with respect to known confounding variables.

98 a multiple regression analysis adjusted for confounding variables.

99 months, robust to adjustment for potentially confounding variables.

100 treated eyes were adjusted for age and other confounding variables.

101 mpared with those without PA, independent of confounding variables.

102 were small and did not adjust for important confounding variables.

103 ns were robust to adjustment for potentially confounding variables.

104 hat formed the early basis for adjustment of confounding variables.

105 elationship was maintained once adjusted for confounding variables.

106 ith symptom control, adjusting for potential confounding variables.

107 years), in models controlling for potential confounding variables.

108 ith linear regression analysis, adjusted for confounding variables.

109 ical data limited by the presence of several confounding variables.

110 aine and periodontitis after adjustments for confounding variables.

111 rrent level of visual field damage and other confounding variables.

112 duced power in the presence of covariates or confounding variables.

113 tipsychotic medication, or other potentially confounding variables.

114 ching >50/muL CD34(+) HSCs, independent from confounding variables.

115 surgery other than cataract surgery to limit confounding variables.

116 Rate ratios were adjusted for potential confounding variables.

117 regression analysis was used to control for confounding variables.

118 dies have been unable to adjust for some key confounding variables.

119 gy intake, BMI, physical activity, and other confounding variables, 45 overlapping metabolites were i

120 gitudinally, after adjusting for potentially confounding variables, active asthma predicted subsequen

121 se differences remained after adjustment for confounding variables (adjusted odds ratio for mortality

122 After adjusting for confounding variables, age and higher education were pos

123 After adjustment for confounding variables-age, gender, systolic blood pressu

124 Groups were matched on a critical confounding variable, alcohol use, to a far greater degr

125 ntrol for multiple comparisons and effect of confounding variables allows the identification of clini

126 After adjustment for pertinent confounding variables, an association between insurance

127 hes and strengths of association between the confounding variable and the exposure to vary.

128 obiome data; it allows for the adjustment of confounding variables and accommodates excessive zero ob

129 lied a random intercept model to account for confounding variables and case-control paired design.

130 e outcomes while controlling for potentially confounding variables and center differences.

131 ose restrictions on the relation between the confounding variables and certain unidentified backgroun

132 After control for potential confounding variables and comparing gravidas with lower

133 ation results showed that the adjustment for confounding variables and meta-analysis improved detecti

134 lysis was performed to control for potential confounding variables and showed that patients undergoin

135 c regression modeling adjusted for potential confounding variables and tested interaction between Rep

136 lyses were performed to adjust for potential confounding variables and to identify independent variab

137 a Lansing effect produced so far, potential confounding variables, and how the underlying mechanisms

138 ural experiment research design controls for confounding variables, and our conceptual model and stat

139 HRT use, subtypes, and duration of use; confounding variables; and asthma onset were defined by

140 e actually quite stable in experiments where confounding variables are controlled.

141 -sectional study suggest that even when many confounding variables are removed the relationship betwe

142 These experiments also control for the confounding variables associated with field-based approa

143 nical samples, the complex, non-standardized confounding variables associated with human subjects and

144 access to tissues from human patients and by confounding variables associated with sample accessibili

145 anges in body-mass index and other potential confounding variables at 12 months.

146 t of visual field loss on SAP, adjusting for confounding variables (baseline age, mean IOP, corneal t

147 ting visual field development, adjusting for confounding variables (baseline age, race, and corneal t

148 re remained significant after adjustment for confounding variables (beta= -0.08 P=0.04).

149 tching was performed to adjust for potential confounding variables between patients cared for in free

150 tching was performed to adjust for potential confounding variables between patients who received at l

151 analysis was performed to address potential confounding variables by indication.

152 After controlling for confounding variables by multivariate analysis, interleu

153 ting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorb

154 Controlled for confounding variables, cocaine exposure had significant

155 Adjustment for confounding variables confirmed the independence of thes

156 gression analysis (after adjusting for other confounding variables) confirmed a lower patient surviva

157 on analysis, controlling for other potential confounding variables (demographic characteristics, clin

158 rsisted in analyses adjusted for potentially confounding variables (demographics, current socioeconom

159 Potential confounding variables did not affect the strength of the

160 Potential confounding variables did not have a meaningful effect o

161 e findings were robust to the effects of the confounding variables examined and differed from other i

162 roportional hazards models that included all confounding variables except exercise physiologic charac

163 c regression analysis accounting for several confounding variables failed to show an association betw

164 e in backcrosses implies that SWD could be a confounding variable for other behaviors.

165 variables, and adaptively selects potential confounding variables for each mediation test.

166 After propensity matching for confounding variables, frequent ventricular ectopy durin

167 Controlling for confounding variables had little effect on these results

168 ontrolling for waist circumference, BMI, and confounding variables (hazard ratios = 1.00, 0.92, 0.75,

169 Additionally, after adjusting for confounding variables, household income, education, and

170 riments showed that neuronal pigments were a confounding variable; however, by examining sections cod

171 When adjusted for potentially confounding variables, ICU admission in July was not ass

172 Logistic regression incorporating several confounding variables identified separate pretransplant

173 separate models, adjusting for time-varying confounding variables (ie, rainfall, temperature, and th

174 We hypothesized that after correction for confounding variables, immunosuppression with tacrolimus

175 After adjustment for confounding variables, important differences remained be

176 Consequently, leukoaraiosis is an important confounding variable in functional MR imaging studies of

177 g for clinicians and introduce a significant confounding variable in research situations.

178 al; P<0.02) when adjusted for 22 potentially confounding variables in a Cox proportional hazards anal

179 ine consumption and withdrawal are potential confounding variables in cerebral perfusion and function

180 After controlling for confounding variables in logistic regression analyses, f

181 After controlling for confounding variables in multivariable analyses, severe

182 provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

183 There is an inherent bias because of confounding variables in observational studies.

184 ith major dietary patterns after control for confounding variables in regression analyses.

185 on level and autoinhibition can be important confounding variables in studies of HIV-1 assembly and c

186 ssion outcome models are used to control for confounding variables in tests for sufficient cause inte

187 Because of unavoidable confounding variables in the direct study of human subje

188 Confounding variables included a lack of use of a standa

189 Confounding variables included sex and maternal educatio

190 ng multivariate Cox regression to adjust for confounding variables including contact HIV status, cont

191 egression models were used to adjust for the confounding variables including graft function during fi

192 After adjustment for possible confounding variables (including menstrual history), lum

193 After adjusting for confounding variables, including fetal weight, fetal gro

194 ion persisted after adjustment for potential confounding variables, including hypertension, body mass

195 , MAC, and AAC after adjustment for relevant confounding variables, including kidney function.

196 The effect was independent of potential confounding variables, including maternal socioeconomic

197 After accounting for confounding variables, including race/ethnicity, age, se

198 Adjustments for potential confounding variables, including smoking, other medicati

199 using statistical models that accounted for confounding variables, including the degree of HLA misma

200 In Cox multiple regression analysis, 3 of 24 confounding variables independently correlated with surv

201 After adjustments for confounding variables, individuals with PISA >490.56 mm(

202 nce, but it will not do so if the unmeasured confounding variable itself does not interact with the g

203 gh parallel changes in body weight and other confounding variables limit this interpretation.

204 Although limited by confounding variables, low-fat dairy products, ascorbic

205 After controlling for confounding variables, LVHR was independently associated

206 The confounding variables make it difficult to compare studi

207 ling for total intracranial volume and other confounding variables, matched cannabis users had smalle

208 Potential confounding variables; maternal age at conception, mater

209 ned to a particular treatment group, unknown confounding variables may be present.

210 ustment for only a small number of potential confounding variables, meaning there is a possibility of

211 e-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MM

212 We observed that after correction for confounding variables, most notably testing rates, there

213 After correction for confounding variables, no association was seen between b

214 ess observed in ALS pathogenesis without the confounding variable of disease onset.

215 ble models of SG assembly, which require the confounding variable of exogenous stressors.

216 in a model of chronic rejection without the confounding variable of immunosuppression.

217 indings, in a system without the potentially confounding variable of immunosuppressive drugs, are in

218 This avoids the confounding variable of potentially abrogating motility

219 egories of heart failure severity as well as confounding variables of left ventricular wall thickness

220 After adjusting for confounding variables of maternal age, parity, race, mar

221 p analyses were conducted to control for the confounding variables of prior thrombolysis, location of

222 that prior studies may have been limited by confounding variables or the technique of identifying ey

223 results were sustained after adjustments for confounding variables (OR 5.20, 95% CI 1.12-24.0).

224 mispheric ICH after adjustment for potential confounding variables (OR, 1.77 (95% CI 1.33 to 2.37)).

225 a small sample size, failure to control for confounding variables, or the use of a cross-sectional d

226 functional decline, adjusting for potential confounding variables over long-term follow-up.

227 line fibrosis after adjustment for potential confounding variables (P<.03, for all).

228 After adjustment for confounding variables, participants living in the most d

229 e of the US population, after adjustment for confounding variables, participants with glaucoma more f

230 After adjustment for confounding variables, patients in teaching ICUs had sli

231 After adjusting for confounding variables, periodontitis remained not associ

232 After adjusting for relevant confounding variables, PH was independently associated w

233 After adjustment for potential confounding variables, PMRT was not associated with a st

234 After adjustment for potentially confounding variables, previous administration of beta-l

235 after adjustment for age and other potential confounding variables, production of interferon- gamma b

236 for moderate-vigorous physical activity and confounding variables, prolonged sedentary time was asso

237 an diseases, matching cases and controls for confounding variables reduces observed differences in th

238 uch a bundle while controlling for potential confounding variables seen in similar studies.

239 work simultaneously considers correction for confounding variables, selection of effective confounder

240 proportional-hazards model with and without confounding variables showed no relation between State-A

241 ssion survival analysis, after adjusting for confounding variables, showed a lower 1-year, 2-year, an

242 After controlling for confounding variables, significant linear correlations w

243 Adjusting for confounding variables, STEMI patients were more likely t

244 After adjustment for potential confounding variables, study participants who self-repor

245 After adjustment for the impact of potential confounding variables, subjects with severe glaucomatous

246 ontrolling for waist circumference, BMI, and confounding variables, successive quintiles of hip circu

247 arying numbers of lesions among patients and confounding variables such as age and medication.

248 After controlling for confounding variables such as age and neurologic diagnos

249 s was used for controlling other potentially confounding variables such as age and sex.

250 are key investigative systems because major confounding variables such as diet, activity, and geneti

251 We also provide a method of controlling for confounding variables such as population stratification.

252 ignificantly smaller cohorts not matched for confounding variables such as T stage.

253 All Cox models were corrected for potential confounding variables, such as age, gender, race, HLA mi

254 Confounding variables, such as donor type and conditioni

255 of detection (i.e., a measurable lesion) and confounding variables, such as tumor microenvironment, a

256 covariate for progressive liver disease or a confounding variable that impacts cirrhosis because of p

257 After controlling for potential confounding variables that assessed behavioral and socio

258 ontinuous culture methods to avoid potential confounding variables that can be associated with experi

259 To assess the dynamics and confounding variables that influence transgene expressio

260 We describe a number of confounding variables that must be addressed when conduc

261 After exclusion of patients with confounding variables that would affect postoperative vi

262 based treatment cohort and explore potential confounding variables, the authors examined use of NSAID

263 After adjusting for potential confounding variables, the odds of gallstones (OR = 3.20

264 After adjustment for potential confounding variables, the odds ratio of CKD for the hig

265 After adjusting for potential confounding variables, the predicted probability of 1-ye

266 After adjustment for confounding variables, the presence of lymphopenia remai

267 riable analyses adjusting for five potential confounding variables, the presence of resilience was in

268 nce for the hypothesis, because of a weighty confounding variable: the historical geography of coloni

269 ation between the causes of interest and the confounding variables; these assumptions will often be m

270 I eliminated the contribution of the major confounding variable to understanding the antiinflammato

271 searchers have not rigorously controlled for confounding variables to assess the independent relation

272 there are important limitations and possible confounding variables to consider.

273 After adjusting for potential confounding variables, use of trimodality therapy remain

274 h daptomycin monotherapy after adjusting for confounding variables using inverse probability of treat

275 L by HIV-NRD status, adjusting for potential confounding variables, using multiple linear regression.

276 After adjustment for potentially confounding variables, vaccination with two complete dos

277 No other confounding variable was associated with reduction in re

278 trolling for sampling design and potentially confounding variables was 0.45 (95% CI, 0.25 to 0.78).

279 symptom mapping (VLSM) analysis adjusted for confounding variables was performed correlating cerebral

280 symptom mapping (VLSM) analysis adjusted for confounding variables was performed correlating sites of

281 bclinical changes in smokers) and Dlco (as a confounding variable) was formulated.

282 intensive care unit clustering and important confounding variables, was used to examine the impact of

283 at through clever design and manipulation of confounding variables, we can gain deep insight into num

284 away performance, travel direction, and team confounding variables, we observed that jet-lag effects

285 Potentially confounding variables were also assessed including demog

286 The effects of potentially confounding variables were assessed in human subjects, a

287 te occupational histories and information on confounding variables were available for 1,323 clinicall

288 between treatment response, D2R binding, and confounding variables were conducted.

289 After potential confounding variables were controlled for, low (adjusted

290 After potential confounding variables were controlled for, significant a

291 After confounding variables were controlled for, statistically

292 Confounding variables were included in multiple regressi

293 or to LOCF and AC analyses when only data on confounding variables were missing; AC analysis also per

294 orrelation coefficients, with adjustment for confounding variables when indicated.

295 irely in darkness, thereby reducing numerous confounding variables when testing path integration.

296 After adjustment for multiple potential confounding variables, when extreme quintiles were compa

297 distance-based tests cannot flexibly handle confounding variables, which can result in excessive fal

298 c regression models adjusted for potentially confounding variables, which generally had no effect on

299 After adjusting for baseline confounding variables with regard to the Unified Parkins

300 We controlled for potential confounding variables with the use of traditional multiv