Sentence examples for multivariate multilevel regression from inspiring English sources

Multivariate multilevel regression analyses will be used to adjust for the nested structure of data in schools.

Multivariate multilevel regression analysis revealed that survey time was significantly and negatively related to three of six patient-reported experience scales: doctor services (Beta = -0.424, p< 0.05), information about examinations (Beta = -0.566, p < 0.05) and organization (Beta = -0.528, p < 0.05).

Main effects and interactions that remained significant on a 0.05 level were included in the final multivariate multilevel regression introducing hospital ward and hospital as levels 2 and 3 variables.

Finally, multivariate multilevel regression analyses (i.e., linear mixed models, adjusted for gender, age, CIRS score, MMSE score, previous ECT, electrode placement, dynamic impedance, and succinylcholine dose) were performed to detect predictors of ST levels during the ECT course.

Multivariate, multilevel regression analysis will be performed to determine patient-level factors (e.g. age, co-morbidities, socio-economic status) and hospital-level factors associated with variability (e.g. inter-hospital transfer protocols).

After a descriptive analysis and bivariate tests of equality of means, we carried out multivariate multilevel regressions for the price differences between pensioners and non-pensioners for therapeutic group j in area i, controlling for the type of co-payment (FC vs. RC), with random effects for the therapeutic group.

Second, variables with an adjusted univariate p-value < 0.2 were entered into multivariate multilevel logistic regression.

Multivariate multilevel prediction regression models for long term complicated grief and depression were fitted.

*Adjusted ORs were estimated with multivariate multilevel logistic regression models using all the variables presented in the table.

Clinical relevant determinants that influenced quality indicator scores in a univariate setting were tested as a group using multivariate, multilevel logistic regression analyses (odds ratios).

To account for the multilevel nature of the data (patients clustered within countries) and to control simultaneously for the possible confounding effects of the different variables, we used multivariate multilevel logistic regression models.