Milestone articles have highlighted the frequency and types of statistical errors in research,1–5 yet fundamental errors ...

Table 2. Results of the multivariable logistic regression analysis for the entire study population, assessing associations between patient demographics, congenital diagnosis and complexity of cardiac ...

Three models were constructed a priori, based on: (1) history, (2) history+spirometry and (3) history+spirometry+Fe NO, using logistic regression analysis. For the history-only model, only those ...

python machine-learning model scikit-learn under classification logistic-regression unsupervised-learning decision-boundary feature-scaling scikitlearn-machine-learning multivariate-linear-regression ...

Categorical variables were compared using the chi-square test. Pearson's and Spearman's correlation analyses were undertaken to evaluate the relationship between the R-wave amplitude and strain ...

Performing multiple logistic regression analysis on airline and customer data to predict the satisfaction. 🔵R. r data-analysis multiple-logistic-regression missing-values-analysis ...

Multivariable logistic regression identified factors associated with drug indication withdrawal. Findings Among 167 accelerated approval indications for 113 anticancer drugs, by August 2024, 102 (61%) ...

Univariable analysis showed that caregiver concern for clinical deterioration was associated with ICU admission (OR 4·04 [95% CI 3·47–4·72]). Multiple logistic regression identified that caregiver ...

To identify factors associated with urgent/emergent AVR, we used multivariable‐adjusted logistic regression analyses to examine the association of sociodemographic and clinical characteristics ...

Background: The clinico-genomic factors influencing clinical trial participation and their impact on clinical outcomes remain unclear. We investigated which clinico-genomic characteristics predict ...