msset: Testing and correcting for small study effects of...

In xmeta: A Toolbox for Multivariate Meta-Analysis

Testing and correcting for small study effects of multivariate meta-analysis

Description

Testing and correcting for small study effects of multivariate meta-analysis

Usage

msset(data, nm.y1, nm.s1, nm.y2, nm.s2, method, type, k)

Arguments

data	dataset
nm.y1	column name for outcome 1
nm.s1	column name for standard error of outcome 1
nm.y2	column name for outcome 2
nm.s2	column name for standard error of outcome 2
method	"nn.cl" indicating the score test for detecting small study effects of MMA
type	either "continuous" or "binary" indicating the type of outcomes
k	integer indicating the number of outcomes

Details

This function returns the test statistics for testing small study effects of multivariate meta-analysis using regression method.

Value

msset.TS returns the test statistic and p value of the score test.

A score test for detecting small study effects in multivariate meta-analysis

Small study effects occur when smaller studies show different, often larger, treatment effects than large ones, which may threaten the validity of systematic reviews and meta-analyses. Detecting small study effects in a multivariate meta-analysis setting remains an untouched research area. Hong et al. (2019) propose a pseudolikelihood-based score test for detecting small study effects in multivariate random-effects meta-analysis. This is the first test for detecting small study effects in multivariate meta-analysis setting.

Author(s)

Chuan Hong

References

Hong, C., Salanti, G., Morton, S., Riley, R., Chu, H., Kimmel, S.E. and Chen Y. (2019). Testing small study effects in multivariate meta-analysis (Biometrics).

Examples

data(prostate)
fit.msset=msset(data=prostate, nm.y1="y1", nm.s1="s1", nm.y2="y2", nm.s2="s2", 
method = "nn.cl", type = "continuous", k=2)
summary(fit.msset)

xmeta documentation built on April 12, 2025, 2:19 a.m.