Continuous and dichotomous outcomes for the five AEDI domains and the aggregate AEDI measure will be modelled separately using
multilevel linear and logistic regression, respectively.
We will use two - level
multilevel linear and logistic regression models (mothers and babies nested within areas) to compare outcomes between individuals living in an AMIHS area compared with individuals who live in a propensity - matched comparison area, using an intention - to - treat approach.
To estimate the proportion of each racial disparity attributable to within - plan differences and to determine the correlation between the outcome measure results and racial disparities in the results, we fitted
multilevel linear regression models predicting the result of each HEDIS indicator.
Not exact matches
A comparison of hierarchical
linear and
multilevel structural equation growth models and their application in school effectiveness research
Control variables in the
multilevel modeling and multiple -
linear regression analyses included gender, race, and pretest scores on the outcome being predicted.
Analyses were implemented at the level of the individual using random effects (
multilevel)
linear regression models24 fitted using maximum - likelihood estimation to allow for the correlation (or clustering) between the responses of subjects from the same MCH unit.
The data was analyzed using generalized
linear models and generalized estimating equations, which are specifically used to address the
multilevel design of data in which schools with participating schoolchildren were randomized (rather than individual participants).
A
multilevel mixed - effects
linear regression model with an unstructured covariance matrix was used to test whether different patterns of financial difficulty were associated with subsequent changes in ADHD symptoms.
«The application of hierarchical
linear modeling to management research,» in
Multilevel Theory, Research, and Methods in Organizations: Foundations, Extensions, and New Directions, eds K. J. Klein, and S. W. J. Kozlowski (Hoboken, NJ: Jossey - Bass), 467 — 511.
For the
multilevel analyses we used the hierarchical
linear modeling (HLM) framework and performed our analyses with HLM 7 [39].
A
multilevel network approach was used in which peer groups were identified via social network analysis, and peer group influence was evaluated with hierarchical
linear modeling (HLM).