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Cox proportional hazards regression modelling for repeated events were performed using a counting process approach to assess hazards of bicycle crash injury associated with residing in Auckland.
Cox proportional hazards regression modelling for repeated events was performed using a counting process approach to assess hazards of crash involvement associated with patterns of using conspicuity aids (latent classes), amount of bunch riding and region of residence.
Cox regression modelling for repeated events was performed with multivariate adjustments.
General linear modelling for repeated measures was used to evaluate the effect of each independent variable including clinical and sociodemographic data.
We used mixed modelling for repeated measures to assess the overall changes in smoking rate between the prelaw and postlaw periods with time spent in the venue and type of site (beach or park) included as variables in the model.
The effect of each independent variable was analyzed separately for the WOMAC and KSS questionnaires, and the CES-D10 and VAS scores, in time (baseline, 6 weeks, 3, 6, 12 months) using general linear modelling for repeated measures and post-hoc tests with Bonferroni's correction.
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Femoral angle measurements were analysed using a mixed effects linear model for repeated measures to determine the levels of intra-observer agreement (repeatability) and inter-observer agreement (reproducibility).
mixed-model for repeated measures.
Mixed-effects Models for Repeated Measures.
This chapter provides models for repeated measures and multivariate data.
Univariate analyses and multivariate hierarchical model for repeated measures were performed.
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