normal_confects | R Documentation |
A general purpose confident effect size function for where a normal or t distribution of errors can be assumed. Calculates confident effect sizes based on an estimated effect and standard deviation (normal distribution), or mean and scale (t distribution).
normal_confects(
effect,
se,
df = Inf,
signed = TRUE,
fdr = 0.05,
step = 0.001,
full = FALSE
)
effect |
A vector of estimated effects. |
se |
A single number or vector of standard errors (or if t distribution, scales). |
df |
A single number or vector of degrees of freedom, for t-distribution. Inf for normal distribution. |
signed |
If TRUE effects are signed, use TREAT test. If FALSE effects are all positive, use one sided t-test. |
fdr |
False Discovery Rate to control for. |
step |
Granularity of effect sizes to test. |
full |
Include some further statistics used to calculate confects in the output, and also include FDR-adjusted p-values that effect size is non-zero (note that this is against the spirit of the topconfects approach). |
See nest_confects
for details of how to interpret the result.
# Find largest positive or negative z-scores in a collection,
# and place confidence bounds on them that maintain FDR 0.05.
z <- c(1,-2,3,-4,5)
normal_confects(z, se=1, fdr=0.05, full=TRUE)
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