| 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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