1 r set of atmospheric inversions and biosphere models, which
were adjusted for a consistent flux definition, showed a high
2 Prevalences
were adjusted for age and CD4 cell count.
3 Common variants (MAF > 0.05)
were adjusted for age at cancer diagnosis, CED, and top princ
4 Our HRs
were adjusted for age, baseline educational level, marital st
5 Analyses
were adjusted for age, gender, education and social class, an
6 Multivariable models
were adjusted for age, gender, race, diagnosis, central corne
7 Analyses
were adjusted for age, race, breast density, baseline examina
8 Association analyses
were adjusted for age, sex, and principal components in a lin
9 Cox models for these outcomes
were adjusted for age, sex, body mass index, hypertension, di
10 All risk estimates
were adjusted for age, sex, comorbidity, type of antireflux s
11 Associations
were adjusted for age, sex, education, diabetes status, and c
12 HRs
were adjusted for age, sex, educational level, marital status
13 g as a covariate, whereas in the pharmacogenomic study, HRs
were adjusted for age, sex, history of myocardial infarction,
14 Seroprevalence 95% confidence intervals (CI)
were adjusted for assay sensitivity and specificity.
15 Regression models
were adjusted for baseline function and patient and tumor cha
16 Models
were adjusted for confounders, including other Healthy Eating
17 Analyses
were adjusted for confounding by time, cluster effects, and p
18 Analyses
were adjusted for confounding using inverse probability of tr
19 Analyses
were adjusted for covariates and multiple hypothesis testing.
20 relative risks (aRRs) and absolute risk differences (ARDs)
were adjusted for demographic characteristics and comorbiditi
21 All analyses
were adjusted for demographics and standard COPD risk factors
22 Logistic regression models
were adjusted for education, other early life characteristics
23 tients with SZ were studied cross-sectionally, and analyses
were adjusted for effects of confounding variables.
24 Models
were adjusted for estimated cell type proportions, age, sex,
25 Survival analyses
were adjusted for guarantee-time bias controlling for known p
26 Analyses
were adjusted for income, parental education, maternal skin c
27 Regression models
were adjusted for individual sociodemographic and clinical ch
28 All models
were adjusted for individual-level predictors including age,
29 All costs and benefits
were adjusted for inflation to 2019 United States dollars and
30 on of the amyloid precursor protein after the latter values
were adjusted for kinetic isotope effects.
31 Associations between FeNO and HIV status
were adjusted for known potential confounders.
32 acts, all associations became non-significant when analyses
were adjusted for multiple comparisons.
33 disease category was analyzed separately, and the P values
were adjusted for multiple comparisons.
34 cs were compared across tertiles; P values for significance
were adjusted for multiple comparisons.
35 Multivariable linear probability models
were adjusted for patient and hospital characteristics.
36 Linear mixed models
were adjusted for postpartum age and infant sex.
37 All models
were adjusted for potential confounders, including demographi
38 Outcomes
were adjusted for prognostic variables and analyzed using Cox
39 Models
were adjusted for sex, age, education, and income (total effe
40 Models
were adjusted for sex, age, education, baseline test score, B
41 Incidence rate ratios (IRRs) and absolute risk differences
were adjusted for sex, age, smoking status, obesity, socioeco
42 cognitive scores between participants with and without HIV
were adjusted for sex, education, age, country of birth, fath
43 Models
were adjusted for sociodemographics, cardiovascular disease r
44 Logistic regression analyses
were adjusted for surgical factors and patients' preoperative
45 Results
were adjusted for the effects of other common infections, ass
46 idual familial aggregation of breast and ovarian cancer and
were adjusted for the family-specific ascertainment schemes.
47 Models
were adjusted for traditional risk factors, low-density lipop
48 s healthcare access and quality and diet, but these factors
were adjusted for with use of county-specific random intercep
49 conomic status, gestational age, breast-feeding, and gender
were adjusted for within each multi-variable model.
50 Models
were adjusted for within-ICU correlation, patient- and ICU-le