Multilevel Modeling of Periodontal Data (IV)

GTH

The (published) picture above had been created based on fixed estimates of a multivariate multilevel time series model of gingival dimensions after the implantation of a bioresorbable membrane for surgical root coverage. One may intuitively compare the multilevel model with a microscope here since raw data or presentation of means and standard deviations would hardly give a similarly elegant impression of what is actually going on after implantation of a membrane for guided tissue regeneration.

The fourth chapter of my new MLwiN manual using own data has been proofread and those who are still interested in “happy multilevel modeling” are encouraged to click here.

 

4 Multivariate Response Models

In the previous chapter, increasingly complex time series models have been set up in order to model gingival thickness, its width, the position of the mucogingival border relative to the cemento-enamel junction, and gingival recession after surgical implantation of a bio-resorbable membrane for guided tissue regeneration for the treatment of gingival recession. While some of these variables, such as thickness and width of gingiva might be positively related, others are not, for example gingival thickness and recession. Mucosal thickness had been measured at three locations: at the gingival margin, as well as at and below the mucogingival border (Müller et al. 2000d). In order to create general predictions of alterations of gingival dimensions after surgery, one single model would be preferred which might include mucosal thickness as measured at different locations as three different responses.

Multivariate response data are most conveniently incorporated into a multilevel model by creating a lower level below the original level 1 units. This will define the multivariate structure. Here we want to set up a 4-level model with multivariate responses (level 1) measured at different occasions (level 2) nested in higher-level units, i.e. teeth (level 3) and patients (level 4).

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3 October 2014 @ 8:47 am.

Last modified October 3, 2014.

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