generate_data_re1: Simulate summary statistics according to random effects...
In dan11mcguire/mamba: MAMBA: Meta-analysis Model Based Assessment of Replicability

Description Usage Arguments Value Examples

Simulate summary statistics according to random effects model.

1 2	generate_data_re1(M = 50 * 10^3, p = 0.01, tau2 = 0.00025, resref = NULL, n = rep(50 * 10^3, 10), I2 = 0.3)

`M`	number of SNPs for which to simulate summary stats.
`p`	proportion of SNPs with real non-zero effects.
`tau2`	variance of real associated non-zero SNPs.
`resref`	an optional vector of residual variances to sample from (with replacement) when generating the standard errors for the summary stats. Default is NULL, in which case the residual variances calculated from a Cigarretes Per Day GWAS (Liu, Jiang 2019) are used.
`n`	vector of sample sizes from the contributing studies.
`I2`	the I2 heterogeneity statistic for each SNP. The variance of study-level effects around population level effect at each SNP is specified given I2 level (between 0,1) and the simulated standard errors.
`alpha`	variance inflation factor of outlier studies.

A list containing: An Mxk matrix of effect size estimates betajk, An Mxk matrix of effect size estimate variances sjk2, M-length vector inverse-variance weighted meta-analysis z-scores meta.z, an M-length binary vector indicating real / non-real effect at each SNP Rj, an M-length binary vector indicating true effect-size at each SNP muj. an Mxk matrix of the true study-level effects etajk an M-length vector of the variance of the study-level effects around the SNP's population level effect omega2j