Sentence examples for mixed models containing from inspiring English sources

We then ran mixed models containing random subject effects using SAS (version 8.02; SAS Institute, Cary, NC) to examine the impact of various personal characteristics on FENO.

Generalized linear mixed models containing dependent variables length, weight (both Gaussian) and survival (binomial) with temperature and infection as fixed effects and density as a covariate.

Percent change in VEGF (dependent variable) was also related to Cmax and Tmax, (independent variables) using separate linear mixed models containing animal-specific intercepts and slopes and a power correlation structure for the residual errors to allow within animal correlations to differ with proximity of measurements.

Mixed models contain a fixed part, capturing the experimental factors, as in ordinary linear models, and a random part, allowing for possibly complex correlations between observations.

Data were analyzed with a polynomial mixed model containing linear, quadratic, and 2-factor interactions for Ile, Leu, Met, and Thr, and cow and residual as random factors.

Specifically, the number of microspheres in each tissue piece was modeled using a Poisson log-linear mixed model containing fixed effects for exposure and random effects for tissue piece and each dog.

Therefore, a linear mixed model containing both linear and second order time components as fixed effects (growth model) as well as random effects for intercepts and slopes for time was estimated first.

A linear mixed model contains fixed and random effects and is linear in these effects.

Historically, the Study effect has been considered a fixed effect not because of a strong argument that such effect is indeed fixed but because of our prior inability to efficiently solve even modest-sized mixed models (those containing both fixed and random effects).

Since we only had two to three time points, our mixed models only contained a random intercept but no random slope component.

Therefore, to evaluate the effects of these two factors, we analyzed a mixed-effects model containing a composite variable with three levels representing the combinations of domatia production and plant life history present in our dataset.