We define x i as the ith participant's row vector of ten covariates, in the order they appear in Tables 2 and 4. Since Y i and R i are both binary, we use conventional logistic regression modelling for both variables and we assume that (1) logit (P (Y i = 1 | x i ) ) = α 0 + α 1 x i and (2) logit (P (R i = 1 | Y i = y i, x i ) ) = β 0 + β 1 x i + β 2 y i.
As other authors have underlined, hierarchical regression models could result in different RAMR from that obtained using conventional logistic regression, even though only patient-level characteristics are used in both models [ 32].
Bayesian binomial logistic regression proved to be a flexible mapping tool but the accuracy gain compared to conventional logistic regression was marginal and may not outweigh the extra modelling and computing effort.
The super learner algorithm had better cross-validated performance than the 39 individual algorithms from which it was developed, including conventional logistic regression.
Donation channels, whether donated in public and whether the government has incentives for donations, are dichotomous variables, and we therefore used a conventional logistic regression model to perform hypothesis testing.
Additionally, the statistical analysis performed showed that the estimates values found by applying a generalised linear mixed model or the conventional logistic regression were grossly coincidental (footnote on Table 2).
[10] We used conventional logistic regression to generate predicted probabilities of TB, plotted the fraction of true positives versus the fraction of false positives at various thresholds of predicted probability as a receiver operating characteristic curve, and measured model accuracy using the concordance (C) statistic (area under the curve).
However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance.
Because similar results were obtained by the hierarchic and conventional logistic regression models, we performed sensitivity analysis by conventional multiple logistic regression analysis (no mutual adjustment).
Second, for predicting short-term cardiovascular mortality, ensemble-based methods did not offer a clear advantage over conventional logistic regression.
