Description Arguments Details References See Also Examples
Results for simulations used in Korthauer and Kimes et al. (2019) with 'unimodal' series of effect size distributions (Stephens, 2017) with standard Gaussian distributed test statistics, and ‘cubic’ informative and paired uninformative covariates stored as a list of SummarizedBenchmark objects from 100 replications. In each simulation, 25% of tests were non-null, i.e. had non-zero effect sizes. Simulations were performed with ‘bimodal’, ‘flat top’, ‘skew’ and ‘spiky’ effect size distributions (see corresponding reference for details).
In sims-uasettings
,
similar settings were considered, but with 10% of tests being non-null.
metadata |
logical whether to load metadata (TRUE) or full resource (FALSE). (default = FALSE) |
The object is a list of length 100 corresponding to the 100 replications. Each
entry in the list is a named list of two SummarizedBenchmark objects. The results
based on using an informative and uninformative covariate are stored as
"informative"
and "uninformative"
, respectively.
Stephens, M. (2017). False discovery rates: a new deal. Biostatistics, 18(2), 275-294.
1 2 3 4 5 6 7 8 9 10 11 12 13 | `uasettings-25-benchmark-bimodal`(metadata = TRUE)
## Not run:
`uasettings-25-benchmark-bimodal`()
`uasettings-25-benchmark-flattop`()
`uasettings-25-benchmark-skew`()
`uasettings-25-benchmark-spiky`()
res <- `uasettings-25-benchmark-spiky`()
res[[1]]$informative
res[[1]]$uninformative
## End(Not run)
|
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