Description Usage Arguments Value References Examples
Function to estimate sample size required to achieve a desired statistical power.
1 2 3 4 5 6 7 8 9 10 11 12 13 |
pilot |
A matrix containing pilot data, if available. |
n1 |
Sample group 1 minimum sample size to consider. |
n2 |
Sample group 2 minimum sample size to consider. |
p |
Number of bins in the data. |
prop |
Expected proportion of significant bins. |
covars |
Matrix of covariates, if available. Categorical covariates should be included as X-1 dummy variables for a covariate with X levels. |
ncovar |
The number of covariates present. For Z numeric covariates and Y categorical covariates with X total levels, this should be Z + X - Y. |
model |
The chosen model. |
plot.prop |
TRUE/FALSE should sample size be calculated for varying proportions of significant bins? |
target.fdr |
The desired false discovery rate. |
Targeted |
TRUE/FALSE is the experiment intended as targeted analysis? |
List containing the estimated sample size with the per-group sample size breakdown, results of FDR calculations for each sample size tested, results for varying the proportion of significant metabolites, the number of bins input, the number of covariates input, the model type used, the input minimum sample sizes for group 1 and group 2, and the desired FDR.
G. Nyamundanda, I. C. Gormley, Y. Fan, W. M. Gallagher and L. Brennan, BMC Bioinformatics, 2013, 14, 338.
1 2 3 4 5 6 | metsize(pilot = NULL, n1 = 4, n2 = 4, p = 200, prop = 0.2, covars = NULL,
ncovar = 0, model = "PPCA", plot.prop = FALSE, target.fdr = 0.10,
Targeted = FALSE)
metsize(pilot = NULL, n1 = 6, n2 = 4, p = 100, prop = 0.1, covars = NULL,
ncovar = 2, model = "PPCCA", plot.prop = FALSE, target.fdr = 0.05,
Targeted = TRUE)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.