Risk factors for contacts identified by a uni- and multivariable logistic regression approach were: distance between pigs enclosure and houses, proximity of a forest, electric fences, and fences ≤ 60 cm.
There are two common multivariable linear regression approaches to modelling changes in metric (interval level of measurement) outcomes like cognitive function [ 29- 33].
We used a multivariable unconditional logistic regression approach [ 27] for the comparisons of all case patients with controls, and ER+PR+ with ER- PR- case patients.
Moreover, since differential recall of detailed physical activity history between cases and controls might occur, we conducted case case comparisons for ER− versus ER+, PR− versus PR+, HER2− versus HER2+, and p53− versus p53+ patients using a multivariable unconditional logistic regression approach 48.
Using this approach, the multivariable regression results for each fat compartment could be more directly compared.
For multivariable regression, the multivariable fractional polynomial approach was used, which evaluates possible non-linear effects of continuous variables such as CD8+ cell density or Ki67 by a set of parsimonious transformations [ 26].
We then estimated the association between NPSGs and initiation of OAT among individuals with new onset AF using a difference-in-difference approach and multivariable regression equations.
The main objective of this work is to develop early cost estimation models for light rail transit and metro trackworks using the multivariable regression and artificial neural network approaches.
We found no evidence of an increased risk of fatal or non-fatal self harm or depression (as measured by antidepressant prescriptions) at three months in individuals prescribed varenicline or bupropion compared with those prescribed nicotine replacement therapy, using three different analytical approaches (Cox multivariable regression, propensity score methods and instrumental variable analyses).
