Sentence examples for by allowing random effects from inspiring English sources

This variant also attempts to reduce the impact of heterogeneity by allowing random effects in the pooling of literature associations.

Mixed-effects models deal with intra-subject correlation by allowing random effects in the models, these models focus on both population-average and individual profiles by taking the dependency between repeated measures into account.

To contain the required flexibility, the LCAR prior captures localized residual spatial autocorrelation by allowing random effects in geographically adjacent areas to be autocorrelated or conditionally independent, and we show that this prior distribution can have realizations at both spatial smoothing extremes, namely global smoothness and independence.

The current theory and implementation of GeneRaVE does not allow random effects to be included.

By allowing the random effects to be correlated, the model jointly determines the selection to returning to work (with the current employer in an accommodated job and with a new employer) and the selection out of employment after returning to work.

But in this case the data for each parameter were analyzed jointly, thereby allowing for random effects by cohort on intercept and covariate effects.

We analysed the association of patient characteristics with the number of chronic conditions by multilevel mixed-effects linear regression allowing for random effects at the study centre and GP practice-within-study centre level.

A random-effect analysis (allowing for random effects on models) yielded similar results (exceedance probability for model bFB+ = 0.965).

Z i is a design matrix for the random effects that allows random subject deviations from the population average response.

The Limit meta-analysis (Schwarzer et al., 2014) is an extended random effects model that takes account of possible small-study effects by allowing the treatment effect to depend on the standard error.

2. The Limit meta-analysis (Schwarzer et al., 2014 ) is an extended random effects model that takes account of possible small-study effects by allowing the treatment effect to depend on the standard error.