xmeta (version 1.3.2)

msset: 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)

Value

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

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

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

Chuan Hong

Details

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

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)