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.