Meta-Analysis Binary Effect Size: Trim-and-Fill

The Trim-and-Fill dialog provides settings for implementing the trim-and-fill analysis of publication bias for meta-analysis with binary outcomes when the pre-calculated effect size data are provided in the active data set.

Estimate number of missing studies
Controls the trim-and-fill analysis of publication bias. Selecting this setting enables the other dialog settings.
Side to Impute Studies
Provides options for specifying the side of the funnel plot on which the missing studies are imputed.
Determined by the slopes of Egger's test
The default setting determines the side based on the estimated slope of the Egger’s test.
Left
Imputes the left side of the funnel plot.
Right
Imputes the right side of the funnel plot.
Method
Specifies the method to estimate the number of missing studies.
Linear
The default setting calculates the linear estimator.
Run
Calculates the run estimator.
Quadratic
Calculates the quadratic estimator.
Iteration process
Provides settings for specifying the iteration estimator and standard error adjustment.
Fixed-effects model
When selected, a fixed-effects model is employed and the iteration estimation and standard error adjustment options are not available.
Random-effects model
When selected, a random effects model is employed and the following settings are available.
Estimator
Provides settings for specifying the iteration estimator
Restricted maximum likelihood (REML)
The default setting applies the iterative method and calculates the restricted maximum likelihood estimator.
Maximum likelihood (ML)
Applies the iterative method and calculates the maximum likelihood estimator.
Empirical Bayes
Applies the iterative method and calculates the empirical Bayes estimator.
Hedges
Applies the non-iterative method and calculate the Hedges estimator.
Hunter-Schmidt
Applies the non-iterative method and calculates the Hunter-Schmidt estimator.
DerSimonian-Laird
Applies the non-iterative method and calculates the DerSimonian-Laird estimator.
Sidik-Jonkman
Applies the non-iterative method and calculates the Sidik-Jonkman estimator.
Standard Error Adjustment
Provides settings for controlling whether to apply the Knapp-Hartung standard-error adjustment to the iterations of the trim-and-fill algorithm.
No adjustment
The default setting does not apply the adjustment.
Apply the Knapp-Hartung adjustment
Applies the Knapp-Hartung adjustment method.
Apply the truncated Knapp-Hartung adjustment
Applies the Knapp-Hartung adjustment method and truncates the value if less than 1 when estimating the variance-covariance matrix.

Defining Meta-Analysis Binary Effect Size trim-and-fill settings

  1. From the menus choose:

    Analyze > Meta Analysis > Binary Outcomes > Pre-Calculated Effect Size...

  2. In the Meta-Analysis Binary Effect Size dialog, click Trim-and-Fill.
  3. Select and define the appropriate trim-and-fill settings.
  4. Click Continue.