Sentence examples for multilevel models that from inspiring English sources

With the purpose of identifying the net associations of class-level factors with students' habitual enjoyment of lessons, we therefore estimate multilevel models that include academic self-efficacy as an independent variable at the student level.

Since there could be multiple passengers in the same vehicle, the SAS GLIMMIX procedure (SAS Institute Inc 2014) with random effects was used to generate odds ratios with 95%% confidence intervals using multilevel models that controlled for violation of the assumption of independence associated with multiple rear-seated occupants in the same vehicle.

We accounted for this degree of clustering by constructing multilevel models that included random effects at the practice level.

Table  4 provides summary results from random-effects multilevel models that examined the relative contribution of individual- and contextual-level variables of the municipality of residence to the individual's utilization of a PCEC.

Finally, multilevel models that contained both individual-level factors and a neighborhood-level factor were constructed to explore sex-specific associations between neighborhood-level factors and CA-MRSA hospitalizations, adjusting for individual-level covariates.

However, making relevant predictions of how molecular events affect cellular and tissue phenotypes will involve computational multilevel models that are much richer in biological knowledge and data than the model presented here.

A multilevel model that is appropriate when several subjects are available is integrated into the Bayesian procedure to provide a standardized effect size measure comparable to effect size measures in a between-subjects design.

Therefore, we applied a cross-classified multilevel model that considers multiple memberships (cf. Goldstein 1994; Heck et al. 2010; Hill and Goldstein 1998).

In order to explain the differences, we define a multilevel model that contains four contextual factors: the importance of upper secondary education; the importance of dual education; vacant jobs; and expenditures for active labour market policy.

We compare a typical least squares mixed model ANOVA ("mixed model ANOVA") with a maximum likelihood mixed-effects model ("mixed-effects model") that treats some variables as fixed and some as random [7], [8] and a hierarchical or multilevel model ("multilevel model") that calculates variance components for all variables [9].

To better accommodate this, instead of a standard ANOVA, groupwise and group-difference maps were calculated in AFNI using recently-developed software, 3dMEMA (http://afni.nimh.nih.gov/sscc/gangc/MEMA.html ), with a linear mixed-effects multilevel model that incorporates both within-subject and cross-subjects variability.