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 ction, but maternal effects are an important confounding variable.

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

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

6 dicting progression over time, adjusting for confounding variables.

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

8 sted after adjustment for multiple potential confounding variables.

9 a multiple regression analysis adjusted for confounding variables.

10 en after adjustment for multiple potentially confounding variables.

11 ts persisting after adjustment for potential confounding variables.

12 nd comparisons were adjusted for potentially confounding variables.

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

14 simple regression analyses were adjusted for confounding variables.

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

16 d treatment outcomes, adjusted for potential confounding variables.

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

18 tolic function after adjusting for potential confounding variables.

19 development and HIV prevalence as potential confounding variables.

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

21 en after controlling for several potentially confounding variables.

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

23 eneralized estimating equations adjusted for confounding variables.

24 quate control groups and poor adjustment for confounding variables.

25 ed significant when controlling for multiple confounding variables.

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

27 be provided that simplify tasks and diminish confounding variables.

28 surgery type, while adjusting for potential confounding variables.

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

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

31 pital mortality while adjusting for baseline confounding variables.

32 potential biases associated with unmeasured confounding variables.

33 nteresting cluster structure associated with confounding variables.

34 months, robust to adjustment for potentially confounding variables.

35 collect information pertaining to potential confounding variables.

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

37 ed whether differences could be explained by confounding variables.

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

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

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

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

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

43 ion techniques with adjustment for potential confounding variables.

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

45 fferent countries and cannot be explained by confounding variables.

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

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

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

49 general linear models adjusted for potential confounding variables.

50 a linear regression analysis to control for confounding variables.

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

52 rbic acid categories, adjusting for possible confounding variables.

53 regression models controlling for potential confounding variables.

54 as no longer significant after adjusting for confounding variables.

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

56 oint was graft survival after adjustment for confounding variables.

57 t these approaches all introduce potentially confounding variables.

58 l folate concentrations after adjustment for confounding variables.

59 ctors after adjustment for other potentially confounding variables.

60 or recipients, while adjusting for potential confounding variables.

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

62 he study end points correcting for potential confounding variables.

63 ric refeeding after adjustment for potential confounding variables.

64 Mexican American women after adjustment for confounding variables.

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

66 gression analysis, adjusting for potentially confounding variables.

67 016), even after controlling for potentially confounding variables.

68 3) questionnaire data regarding potentially confounding variables.

69 erative events and to adjust for potentially confounding variables.

70 t persisted after adjustment for potentially confounding variables.

71 es after adjustment for potential nondietary confounding variables.

72 resis, even when controlling for potentially confounding variables.

73 e determined in this cohort without possible confounding variables.

74 ogistic regression to adjust for potentially confounding variables.

75 e, urbanicity, and/or parity are included as confounding variables.

76 proportionate rate (P=.001), controlling for confounding variables.

77 ns were robust to adjustment for potentially confounding variables.

78 ter adjustment for age and other potentially confounding variables.

79 ncorporating race, urbanicity, and parity as confounding variables.

80 5 percent confidence intervals, adjusted for confounding variables.

81 ce persisted after controlling for potential confounding variables.

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

83 elationship was maintained once adjusted for confounding variables.

84 ith symptom control, adjusting for potential confounding variables.

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

86 ith linear regression analysis, adjusted for confounding variables.

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

88 aine and periodontitis after adjustments for confounding variables.

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

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

91 tipsychotic medication, or other potentially confounding variables.

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

93 surgery other than cataract surgery to limit confounding variables.

94 Rate ratios were adjusted for potential confounding variables.

95 regression analysis was used to control for confounding variables.

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

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

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

99 ions, procedural differences, and unmeasured confounding variables.

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

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

102 estimated IQ after adjustment for potential confounding variables.

103 ttle fed their infants after controlling for confounding variables.

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

105 fter adjustment for each other and potential confounding variables.

106 adjusting for the degree of relatedness and confounding variables.

107 models were constructed that controlled for confounding variables.

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

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

110 across populations and with respect to known confounding variables.

111 in this population even after adjusting for confounding variables.

112 ital affects outcomes independently of other confounding variables.

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

114 linear regression and adjusted for important confounding variables.

115 measles (odds ratio, adjusted for potential confounding variables 0.36 [95 percent CI 0.17-0.78], p=

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

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

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

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

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

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

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

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

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

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

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

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

128 regression analyses adjusted for potentially confounding variables and clustering of results within s

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

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

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

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

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

134 ty dietary information, control for multiple confounding variables, and modern multivariate methods o

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

136 Physiologic changes, preanalytical factors, confounding variables, and treatment goals must be taken

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

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

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

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

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

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

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

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

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

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

147 After controlling for confounding variables by multivariate analysis, interleu

148 Controlled for confounding variables, cocaine exposure had significant

149 Adjustment for confounding variables confirmed the independence of thes

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

151 After adjustment for confounding variables, current hormone users had a lower

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

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

154 Potential confounding variables did not affect the strength of the

155 Potential confounding variables did not have a meaningful effect o

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

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

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

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

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

161 The minimal number of confounding variables, good reliability, and little intr

162 Controlling for confounding variables had little effect on these results

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

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

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

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

167 Logistic regression incorporating several confounding variables identified separate pretransplant

168 esence of family history and other potential confounding variables (ie, age, treatment modality, stag

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

170 After adjustment for confounding variables, important differences remained be

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

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

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

174 f 36% at 2 years), even after adjustment for confounding variables in a multivariable analysis.

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

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

177 After controlling for confounding variables in multivariable analyses, severe

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

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

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

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

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

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

184 ually results from the effects of unmeasured confounding variables, in particular smoking status and

185 Confounding variables included a lack of use of a standa

186 ge of drug pharmacology is needed because of confounding variables including concurrent patient illne

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

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

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

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

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

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

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

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

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

196 ards analysis, with adjustment for potential confounding variables, including the transplantation cen

197 sues after adjustment for multiple potential confounding variables, including tobacco exposure, was 9

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

199 However, a possible confounding variable is the concentration of circulating

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

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

202 After controlling for confounding variables, LVHR was independently associated

203 The confounding variables make it difficult to compare studi

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

205 ter controlling for the effects of important confounding variables, maternal asthma was associated wi

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

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

208 tivariable model that adjusted for potential confounding variables (odds ratio 1.21, P=0.002).

209 did not persist when data were adjusted for confounding variables (odds ratio = 1.11; 95% confidence

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

211 f individual and sex differences without the confounding variable of genetically determined gender.

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

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

214 This avoids the confounding variable of potentially abrogating motility

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

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

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

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

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

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

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

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

223 After adjusting for confounding variables, overweight increased fastest amon

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

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

226 After adjusting for confounding variables, periodontitis remained not associ

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

228 not control for the effects of all potential confounding variables, physicians risk drawing the wrong

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

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

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

232 After controlling for potential confounding variables, risk of very preterm delivery (<

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

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

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

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

237 After controlling for confounding variables, significant linear correlations w

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

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

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

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

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

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

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

245 odels, adjusting for some of the potentially confounding variables such as initial disease severity a

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

247 ssed, even after controlling for potentially confounding variables such as sex, marital status, antid

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

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

250 Confounding variables, such as donor type and conditioni

251 ces remained after controlling for potential confounding variables, such as estimated levels of premo

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

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

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

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

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

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

258 After adjustment for confounding variables the odds ratio for seeking immedia

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

260 After controlling for potentially confounding variables, the authors found that exposure t

261 After controlling for potential confounding variables, the average distance walked in 6

262 Independently of known confounding variables, the impact of AR on CAF has signi

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

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

268 mas; however, after adjustment for potential confounding variables, these trends were not statistical

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

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

276 No other confounding variable was associated with reduction in re

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

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

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

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

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

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

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

284 Potentially confounding variables were also assessed including demog

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

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

287 After potential confounding variables were controlled for, leptin at ent

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

289 After potential confounding variables were controlled for, significant a

290 After confounding variables were controlled for, statistically

291 Confounding variables were included in multiple regressi

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

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

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

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

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

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

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

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

300 stment for a history of PTSD and potentially confounding variables, women were 4.39 times more likely