1 Regression analyses revealed that this combination of factors
2 Regression analysis revealed the two strongest independent ra
3 Regression analysis, correlation coefficient analysis, and te
4 ss the impact of resection margin status on survival, and
a regression analysis to analyze positive resection margin rate
5 cluded simultaneously in a multilocus model and least
angle regression was used to select the most potentially associated
6 red using the independent t test, Wald chi(2), and
binomial regression analysis.
7 Multivariable
binomial regression models were used to evaluate the effects of oral h
8 in rates of antimicrobial resistance, and negative
binomial regression to examine trends in icidence of bloodstream infec
9 Cox regression analysis explored risk factors for interim death o
10 imated hazard ratios (HR) and 95% CIs with multivariate
Cox regression models fitting stromal TILs as a continuous variab
11 d albumin bound paclitaxel is effective in inducing
disease regression in treatment-refractory breast cancer chest wall m
12 Mixed-
effects regression models were used to compare PRO scores across proc
13 Furthermore,
regression analysis shows a positive association between esti
14 We used Cox proportional
hazards regression models to assess the association between later-gen
15 Cox proportional
hazards regression was performed in propensity score-matched cohorts
16 Cox proportional
hazards regression was used to estimate HRs and 95% CIs of diabetes r
17 Hierarchical regression analyses further show that variations in spatial p
18 In regression models, APOE-e4 dose and age both consistently inc
19 ing the 52 SNPs to all phenotypes using logistic and
linear regression models.
20 Results were compared using Cohen's kappa and
linear regression, respectively.
21 m was correlated with the quercetin concentration by
linear regression (molar extinction coefficient 23.2 (+/-0.3)x10(3)M
22 Multivariable Poisson log-
linear regression was used to estimate adjusted risk ratios (aRRs) a
23 e analysis and residual analysis based on a multiple
linear regression model.
24 y intima-media thickness (cCIMT) using multivariable
linear regression analysis among 1554 African Americans from MESA (M
25 Logistic regression analyses examined the association between prenatal
26 We conducted conditional
logistic regression analyses adjusted for body mass index, smoking, hy
27 We used published data to create
logistic regression models comparing annual trends in the representati
28 Univariate and mixed-effects
logistic regression analysis controlling for center effect were used.
29 A hierarchical
logistic regression model was used to identify predictors of delayed f
30 We performed multinomial
logistic regression analysis to assess the weighting of histologic fea
31 Multivariable
logistic regression was used to explore the association of disease sta
32 Multivariable
logistic regression with generalized estimating equations was used to
33 We used multivariate
logistic regression with PCR-confirmed influenza infection as the outc
34 On multivariate
logistic regression, lower baseline GDF-15 was associated with improve
35 within 14 days of LVAD were assessed with stepwise
logistic regression.
36 Longitudinal regression models were constructed to assess associations bet
37 This study was a systematic review and
meta-
regression analysis.
38 Potential moderators of efficacy were analyzed by
meta-
regression.
39 The use of
multiple regression analysis demonstrates that FAEE content can be inf
40 Weighted
multivariable regression was used to examine trends in rates of sudden deat
41 Linear
multivariate regression showed that successful agers (N = 789) reported 3.
42 On
multivariate regression controlling for injury severity and demographic va
43 Our simulation study compares methods under
parametric regression misspecification; our results highlight TMLE's pro
44 Poisson regression with robust variance estimation provided prevalenc
45 Cubic-restricted splines and multivariable log-
Poisson regression with empirical standard errors were used to estima
46 Associations were assessed using
Poisson regression with robust variance estimation.
47 Concordance between 4 antibodies
revealed regression for tumor tissue cores (R2 = 0.42-0.91) and cell l
48 a new multivariable linear model for GFR using
statistical regression analysis.
49 Eliminating PEPD causes cell death and
tumor regression due to p53 activation.
50 tumor bearing mice with an IKK inhibitor resulted in
tumor regression.