Sentence examples for using a mixed logistic from inspiring English sources

The data were analysed using a mixed logistic regression model.

These comparisons remained significant even after controlling for inter-center variability using a mixed logistic regression model for each outcome (liver fibrosis, harmful alcohol consumption, employment, severe depressive symptoms).

The link between these percentages and adherence was explored using a mixed logistic regression that considered the classes of adherence averages and the standardized variances as well as their interactions as fixed effects and the six-month period as random intercept.

60 The percentage of patients in whom a change (initiation/switch/intensification) in any DMARD (conventional or biological) was made during the 6-month study was analysed using a mixed logistic-regression model with a random effect for the centre before and after adjusting for corticosteroid intake and biological therapy.

Also, this paper shows how to use a mixed logistic model to test homogeneity of odds ratios in multicenter trials.

We used a mixed logistic model [ 14] with a random intercept [ 15, 16] to assess the association between physicians' characteristics and agreement for smoking status (the dependent variable).

We used a mixed logistic model to assess the association between physicians' characteristics and agreement for patients' smoking status and alcohol consumption.

We also tested separately for interaction between- and within-families genetic effect and age, sex and location (rural/urban) as effect modifiers in the models for quantitative traits.For association analysis with the discrete trait of type 2 diabetes, we used a mixed logistic regression model using the same Fulker's decomposition of genotypes on 561 sib pairs (see ESM Table  4).

Because the kinetic of biomarkers was more evaluated than their absolute values in the present study, we used a mixed logistic regression model taking into account both time (as repeated measures were performed and analyzed) and biomarkers in the comparison model.

Using a mixed effect logistic model for longitudinal data we compared the point prevalence abstinence rate.

The impact of the intervention was assessed using a mixed effects logistic regression model, accommodating for clustering at GP level.