Sentence examples for multivariate multilevel analysis from inspiring English sources

Table  2 shows the results of the multivariate multilevel analysis.

Variables that presented p ≤ 0.20 in bivariate analysis were considered for the multivariate multilevel analysis.

In multivariate multilevel analysis (Table  2), an area-level effect was found in the null model (level 2 variance of 0.2898 [0.1087], p = 0.008).

In multivariate multilevel analysis (Table  3), an area-level effect was found in the null model (area-level variance of 0.1864 [0.0698], p = 0.008).

Within all steps of the multivariate multilevel analysis, data were adjusted by a normalisation procedure for the overrepresentation of university hospitals and deceased patients.

Last, variables included in the final multivariate model for participant-based factors and those included in the multilevel model for farm-based factors were combined in a multivariate multilevel analysis to identify the independent risk determinants for seropositivity.

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).

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).

In the multivariate and multilevel analysis final model (Table  6), performed colonoscopies reached an odds ratio (OR) of qualifying as appropriate for CRC diagnosis of 9.9 (OR = 9.87; CI 95%% 1.16 84.08), 1.5 (OR = 1.49; CI 95%% 1.1 2.02) if the colonoscopy request was issued by a general practitioner, and 1.1 (OR = 1.09; CI 95%% 1.07 1.1) if the colonoscopy was performed on women.

To estimate the effect of school type multivariate multilevel mixed effect regression analysis using hierarchical models were used based on the intention to treat principle.

Multivariate multilevel binary logistic regression analysis revealed that the following factors were significantly associated with EBF after controlling for confounders: (a) decreased child age in months; (b) geopolitical region; (c) antenatal clinic visits; (d) household wealth, and (f) gender.