Implements the Andrews & Kasy (AK) method for publication bias correction in meta-analysis. The AK method categorizes estimated effects into groups with different probabilities of being published. AK1 uses symmetric selection grouping estimates into significant (|t| >= 1.96) and insignificant (|t| < 1.96) estimates. AK2 uses asymmetric selection with four groups based on both significance and sign: highly significant positive/negative effects and marginally significant positive/negative effects, each with different publication probabilities. See Andrews and Kasy (2019) for details.
Usage
# S3 method for class 'AK'
method(method_name, data, settings)Details
The following settings are implemented
"default"Uses AK1 estimator (symmetric selection)
"AK1"Symmetric selection model grouping estimates into significant (|t| >= 1.96) and insignificant (|t| < 1.96) categories with relative publication probabilities of 1 and p1 respectively.
"AK2"Asymmetric selection model with four groups based on t-statistics: (a) t >= 1.96, (b) t < -1.96, (c) -1.96 <= t < 0, and (d) 0 <= t < 1.96, with relative publication probabilities of 1, p1, p2, and p3 respectively.
References
Andrews I, Kasy M (2019). “Identification of and correction for publication bias.” American Economic Review, 109(8), 2766–2794. doi:10.1257/aer.20180310 .
Examples
# Generate some example data
data <- data.frame(
yi = c(0.2, 0.3, 0.1, 0.4, 0.25),
sei = c(0.1, 0.15, 0.08, 0.12, 0.09)
)
# Apply AK method
result <- run_method("AK", data, "default")
#> Warning: NaNs produced
print(result)
#> method estimate standard_error ci_lower ci_upper p_value BF
#> 1 AK 0.1239951 0.07280359 -0.1892534 0.4372437 0.09217477 NA
#> convergence note tau_estimate tau2_se bias_coefficient
#> 1 TRUE NA 0 1.084652e-10 0.0685673164403796
#> bias_coefficient_se version method_setting
#> 1 0.110251775402335 AK1 default