TRIMFILL Subcommand (META CONTINUOUS command)
The META CONTINUOUS command calls the meta-analysis procedure with continuous outcomes and raw effect size data. The optional TRIMFILL subcommand implements the trim-and-fill analysis of publication bias.
- SIDE
- The optional keyword specifies the side of the funnel plot on which the missing studies are to be imputed. EGGERSLOPE is the default setting, which determines the side based upon the estimated slope of the Egger’s test. LEFT and RIGHT impute the left and right side of the funnel plot, respectively.
- METHOD
- The optional keyword specifies the method to estimate the number of missing studies.
- MODEL
- The optional keyword specifies the model that is used in the iterations of the trim-and-fill algorithm.
- ESTIMATE
- The optional keyword specifies the estimator in the iterations. The process
is available when
/TRIMFILL METHOD = RANDOM, and is otherwise ignored.- REML
- The default setting that applies the iterative method and calculates the restricted maximum likelihood estimator.
- ML
- Applies the iterative method and calculate the maximum likelihood estimator.
- BAYES
- Applies the iterative method and calculate the empirical Bayes estimator.
- HEDGES
- Applies the non-iterative method and calculates 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.
- ADJUSTSE
- The optional keyword controls whether to apply the Knapp-Hartung standard
error adjustment to the iterations of the trim-and-fill algorithm. The process is available when
/TRIMFILL MODEL = RANDOM, and is otherwise ignored.- NONE
- The default setting that does not apply the adjustment.
- KNAPP_HARTUNG
- Applies the adjustment method.
- TRUNCATED_KNAPP_HARTUNG
- Applies the adjustment method and truncates the value if less than 1 when estimating the variance-covariance matrix.