Drawing on the results of a representative survey of 2300 individuals, carried out in Chile's capital city, Santiago, at the behest of the country's Ministry of Justice, we apply multilevel logistical regression models.
Our study is using repeated measures multilevel logistical regression models that were gender stratified.
Repeated-measures multilevel logistical regression models were estimated using MLwiN V.2.27.
We repeated the key rejection rate analysis using multilevel logistical regression (applying the xtmelogit command in Stata 11.0; StataCorp, 2009).
To handle this dichotomous outcome variable, we used a series of non-linear (Bernoulli) multilevel models, often referred to as multilevel logistical regression.
To determine the effect of participation in the implementation programme and to correct for the clustering effect, we applied a multilevel logistical regression analysis with a two-level structure with patients nested within general practices.
