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1                                                             Regression modelling was used for a statistical analysis.
2                                                             Regression models were fitted to assess association between r
3                                                 In adjusted regression analyses, we examined associations of brain insuli
4 ds for logarithmically scaled tumor volume are estimated as regression splines in a generalized additive mixed model.
5                                         Three complementary regression models were generated for number of patients seen,
6 ession-free survival (PFS; by RECIST) were evaluated by Cox regression and Kaplan-Meier statistics.
7                                 We fitted mixed-effects Cox regression models adjusting for multiple pregnancies per indi
8                                          A multivariate Cox regression analysis of the miR-21 expression in the TCGA glio
9 eatinine and cystatin C) and ACR with cancer risk using Cox regression models adjusted for potential confounders.
10                                                       A cox-regression analysis for post-liver transplant HCC recurrence
11  by intention to treat by means of multilevel random effect regression analyses adjusting for clustering in health centre
12 l was assessed using time-dependent Cox proportional hazard regression analysis and landmark analysis.
13  (i.e. LAZ < - 2) and persistence from 12 to 24 months into regression models and tested for the mediating effect of low
14                            In addition, we performed linear regression to identify clinical factors associated with myoca
15                                             Stepwise linear regression was applied to select the model best predicting th
16                                              We used linear regression to examine country-level associations between the
17                                                    Logistic regression models combining T2-weighted SI and T2-weighted he
18                             Adjusted path analysis logistic regression models were used to assess the role of pre-pregnan
19 lysis (descriptive, sequence pattern analyses, and logistic regression analyses) aimed to detect any combinations of even
20 d independently, (ROC analysis, followed by binary logistic regression) only Ultrasound depth is a significant predictor
21                                        Conditional logistic regression odds ratios (ORs) accounting for individual matchi
22 tratified case-crossover analysis with conditional logistic regression to estimate the association between hourly particl
23                      Univariable and multivariable logistic regression analyses were performed to identify parameters tha
24                                   In multivariable logistic regression analysis, risk factors for severe infection includ
25                                 In a multivariable logistic regression analysis, we investigated the risk of IE according
26 ital mortality, was analyzed using a multivariable logistic regression model.
27                                       Multivariate logistic regression analysis showed women with hydrosalpinx were 2.11
28                                       Multivariate logistic regression of the retrospective cohort demonstrated predictor
29      Predictive algorithms were developed based on logistic regression, random forests, gradient boosted trees and a stac
30 fects were estimated using mixed-effects linear or logistic regression, including a random effect to adjust for within-sc
31                                                The logistic regression coefficients were identical between the methods (a
32 ake frequency (%) was compared using unconditional logistic regression.
33 essed using locally-weighted scatterplot smoothing (LOWESS) regression and change-point analyses and Spearman correlation
34                                         Random-effects meta regression estimated whether sex differences in not enrolling
35                                                        Meta-regression revealed an increase in Anisakis spp. abundance (a
36 ly smaller than the number of markers, a penalized multiple regression method can be adopted by fitting all bins to a sin
37                                    We created multivariable regression models at the year, day, and visit level after adj
38                                          The average myopic regression was - 0.51 +/- 0.38 D.
39 t 78% of hepatocellular adenomas had long-term stability or regression.
40                         We used chi2 statistics and ordinal regression to assess the significance of associations and Bon
41 G1 = 8%) but was associated with a significant pathological regression (TRG1-2 = 44% vs 8%, P < 0.001) and a trend to tum
42  included cases around 90 minutes; however, local quadratic regression around the 90-minute cutoff did not reveal evidenc
43                                                      Random regression models were used to jointly analyse live body weig
44          We applied stratified linkage disequilibrium score regression and evaluated heritability enrichment in 64 genome
45 Our BGW-TWAS method is based on Bayesian variable selection regression, which not only accounts for cis- and trans-eQTL o
46 ensitivity~70-90% and specificity~90-93% through the sparse regression machine learning of patterns.
47  analytical curves were estimated by weighted least squares regression (WLS), confirming heteroscedasticity for all compo
48 e calibration models were built using Partial Least Squares regression to determine dry matter (DM), soluble solids (SS),
49 ncy for each participant was estimated by means of land-use regression models.
50 peaks of some parameters show strong correlations for which regression formulae are given.