# Meta-Analysis Binary: Bias

The Bias dialog provides settings for enabling the publication bias by conducting regression-based tests for meta-analysis with binary outcomes on raw data that are provided in the active dataset for the estimation of the effect size.

- Regression-based Tests
- Provides options for specifying the regression based tests. More than one
test can be selected.
- Egger's test
- When selected, conducts Egger's test.
- Harbord's test
- When selected, conducts Harbord's test. The test is available when the Effect Size is specified as Logs Odd Ratio or Log Risk Ratio.
- Peters' test
- When selected, conducts Peters' test. The test is available when the Effect Size is specified as Logs Odd Ratio.

- Variables
- The list provides all available dataset variables.
- Covariate(s)
- Variables selected from the Variables list are treated as covariates. Multiple covariates are allowed.
- Factor(s)
- Variables selected from the Variables list are treated as factors. Multiple factors are allowed.
- Include intercept in regression
- Controls the intercept term in the regression-based test.
- Include dispersion parameter in fixed-effects model
- Controls the multiplicative model setting and introduces the multiplicative dispersion parameter to the analysis. The setting is available only when a fixed-effects model is selected.
- Estimate statistics based on t-distribution
- Controls the distribution used in the regression-based tests. The setting is
enabled by default, which estimates the statistics based on the
*t*-distribution. When the setting is not selected, the statistics are estimated based on the normal distribution.

## Defining Meta-Analysis Binary bias settings

- From the menus choose:
- In the Meta-Analysis Binary dialog, click Bias.
- Select and define the appropriate bias settings.
- Click Continue.