seq_aipe_cv: seq_aipe_cv

In yelleKneK/SMSD: Sequential Methods for Study Design

seq_aipe_cv

Description

Sequential approach to Accuracy in Parameter Estimation for Effect Sizes (AIPE): Coefficient of Variation

Usage

seq_aipe_cv(
  alpha = 0.05,
  omega,
  data = NULL,
  pilot = FALSE,
  m0 = 4,
  na.rm = TRUE
)

Arguments

alpha	The significance level., default is 0.05.
omega	omega
data	The dataset for which to calculate the coefficient of variation.
pilot	Shoulda pilot sample be generated.
m0	The initial sample size.
na.rm	This parameter controls whether NA values are removed from the data prior to calculation. Default is TRUE.

Value

The current sample size, the coefficient of variation, an indicator of if the criterion is satisfied, and the confidence interval.

Author(s)

Ken Kelley [e-mail], Francis Bilson Darku [e-mail], Bhargab Chattopadhyay [e-mail]

Examples

pilot_ss <- seq_aipe_cv(alpha=0.05, omega=0.2, pilot=TRUE)
SLS <- rexp(pilot_ss, rate=0.05)
seq_aipe_cv(alpha=0.05, omega=0.2,data = SLS)

yelleKneK/SMSD documentation built on Nov. 23, 2022, 6:40 p.m.