How to use the glmulti package for model selection?

How to use the glmulti package for model selection?

Please go here for the updated page: Model Selection using the glmulti and MuMIn Packages. This also covers how to use the MuMIn package for the same types of analyses.

How to use glmulti to handle rma.uni objects?

To get the glmulti package to handle rma.uni objects, we must register a getfit method for such objects. The necessary code for this comes with the metafor package, but it first needs to be evaluated with: Now we can carry out the computations for multimodel inference with: The output is not shown, because I don’t find it very intuitive.

Which is a fixed effect in a meta regression?

This means that between-study heterogeneity exists in our data, which is captured by the heterogeneity variance τ 2 τ 2. Since the equation above includes a fixed effect (the β β coefficient) as well as a random effect ( ζk ζ k ), the model used in meta-regression is often called a mixed-effects model.

How are information theoretic methods used in model selection?

Information-theoretic approaches provide methods for model selection and (multi)model inference that differ quite a bit from more traditional methods based on null hypothesis testing (e.g., Anderson, 2007; Burnham & Anderson, 2002). These methods can also be used in the meta-analytic context when model fitting is based on likelihood methods.

What should be included in the Sequential Intercept Model?

Identify local behavioral health services to support diversion from the justice system. Introduce community system leaders and staff to evidence-based practices and emerging best practices related to each intercept. Enhance relationships across systems and agencies. Create a customized, local map and action plan to address identified gaps.

How many rows are in the glmulti dataset?

We can look at the first 10 and the last 10 rows of the dataset with: Variable yi contains the effect size estimates (standardized mean differences) and vi the corresponding sampling variances. There are 48 rows of data in this dataset.

How are the coefficients of a METAFOR model different?

Both coefficients are significantly different from zero ( p = .0334 p = .0334 and p = .0025 p = .0025, respectively), so the average effect is significantly different (and in fact lower) when teachers had some or a high amount of contact with the students prior to the expectancy induction (instead of no contact).

How to use alternative models with multiple factors?

We can use an alternative model specification, where we leave out the model intercept: Note that the first three coefficients now directly correspond to the estimated average effects for levels none, some, and high of the weeks factor and level blind of the tester factor.

How is Akaike weight used in model selection?

From an information-theoretic perspective, the Akaike weight for a particular model can be regarded as the probability that the model is the best model (in a Kullback-Leibler sense of minimizing the loss of information when approximating full reality by a fitted model) out of all of the models considered/fitted.