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Related Experiment Video

Updated: Jun 2, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

Published on: April 19, 2024

Testing overall and moderator effects in random effects meta-regression.

Hilde M Huizenga¹, Ingmar Visser, Conor V Dolan

¹Department of Psychology, University of Amsterdam, The Netherlands. h.m.huizenga@uva.nl

The British Journal of Mathematical and Statistical Psychology

|April 22, 2011

Summary

This summary is machine-generated.

For random effects meta-regression, the resampling and Bartlett-corrected likelihood ratio (BcLR) tests offer accurate Type I error rates for moderator effects. The t test is a tolerable alternative when these are unavailable.

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Last Updated: Jun 2, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

Published on: April 19, 2024

Area of Science:

Statistical methodology
Biostatistics
Epidemiology

Background:

Random effects meta-regression synthesizes multiple study results.
It enables testing overall effects and moderator effects of study characteristics.

Purpose of the Study:

To compare the performance of various statistical tests for moderator effects in random effects meta-regression.
To identify reliable methods for assessing the impact of study characteristics on synthesized results.

Main Methods:

Evaluation of Type I error rates for z, t, likelihood ratio (LR), Bartlett-corrected LR (BcLR), and resampling tests.
Comparison of statistical power across the tested methods.

Main Results:

The z and LR tests exhibit poor Type I error control, often exceeding the chosen alpha.
Resampling and BcLR tests demonstrate accurate error rates.
The t test shows less accurate but acceptable error rates.
BcLR and t tests offer slightly superior statistical power compared to the resampling test.

Conclusions:

The resampling or BcLR tests are recommended for moderator effect testing due to their accurate Type I error rates.
The t test is a viable alternative if resampling or BcLR tests are not feasible.
The z test is not recommended due to its poor performance.