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1 me after high-volume but not low-volume aSAH (multivariable logistic regression).
2 ation intake frequency (%) was compared using unconditional logistic regression.
3 ns with IOP using linear regression and with glaucoma using logistic regression.
4 nd compared these with results generated from multivariable logistic regression.
5 tive complications and FTR was evaluated with multivariable logistic regression.
6             Factors associated with PIR were assessed using logistic regression.
7 , and multivariable predictors of cPR were identified using logistic regression.
8 th linear kernel (0.780), and [Formula: see text] penalized logistic regression (0.780).
9 en of Disease (GBD) super-regions, with adjusted linear and logistic regression analyses examining associations with immu
10               Descriptive analyses and multivariable binary logistic regression analyses were conducted on weighted data.
11                               Univariable and multivariable logistic regression analyses were performed to identify param
12   Radiomics were obtained for the entire lung, and multiple logistic regression analyses with areas under the curve (AUCs
13 tical analysis (descriptive, sequence pattern analyses, and logistic regression analyses) aimed to detect any combination
14                                                    Multiple logistic regression analysis demonstrated that increased infe
15                                                Multivariate logistic regression analysis showed women with hydrosalpinx w
16                                                             Logistic regression analysis was undertaken to identify indep
17                                            In multivariable logistic regression analysis, higher baseline IOP predicted h
18                                            In multivariable logistic regression analysis, risk factors for severe infecti
19                                          In a multivariable logistic regression analysis, we investigated the risk of IE
20            Odds ratios (ORs) were calculated as part of the logistic regression analysis.
21 ing alcohol-related cirrhosis and HCC were determined using logistic regression analysis.
22 ared between late AMD patients and control individuals with logistic regression analysis.
23                                             We used ordinal logistic regression and applied generalized estimating equati
24  k-nearest neighbor, support vector machine, random forest, logistic regression and Naive Bayes.
25                Performance of the ANN was evaluated against logistic regression and the standard grading system by analys
26                                                         The logistic regression coefficients were identical between the m
27  common diseases, of which 38 loci would be missed within a logistic regression framework with a binary phenotype defined
28 ention effects were estimated using mixed-effects linear or logistic regression, including a random effect to adjust for
29                                                         The logistic regression model combining T2-weighted SI ratio with
30          100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholdin
31 , in-hospital mortality, was analyzed using a multivariable logistic regression model.
32                                                    Adjusted logistic regression models and meta-analyses were performed.
33                                                             Logistic regression models combining T2-weighted SI and T2-we
34                               Univariable and multivariable logistic regression models were used to assess predictors of
35                                      Adjusted path analysis logistic regression models were used to assess the role of pr
36                                               Unconditional logistic regression models were used to estimate odds ratios
37 iated transrepression and predicted response to ICS through logistic regression models.Measurements and Main Results: We
38                                                 Conditional logistic regression odds ratios (ORs) accounting for individu
39                                                Multivariate logistic regression of the retrospective cohort demonstrated
40 considered independently, (ROC analysis, followed by binary logistic regression) only Ultrasound depth is a significant p
41               Predictive algorithms were developed based on logistic regression, random forests, gradient boosted trees a
42                                                             Logistic regression showed increasing odds of respiratory fai
43  a time-stratified case-crossover analysis with conditional logistic regression to estimate the association between hourl
44    We analyzed time trends during the study period and used logistic regression to examine sociodemographic and clinical
45                               We used multivariable ordinal logistic regression to identify factors associated with indol
46                                                    Multiple logistic regression was performed on demographic and anatomic
47                                                    Stepwise logistic regression was performed to select the optimal combi
48                                                 Conditional logistic regression was used to create models of associations
49                         Backward selection and multivariate logistic regression were conducted to assess risk of GI adver
50 meters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross valida