seq_aipe_smd: seq_aipe_smd
In yelleKneK/SMSD: Sequential Methods for Study Design

seq_aipe_smd

R Documentation

seq_aipe_smd

Description

Sequential approach to Accuracy in Parameter Estimation for Effect Sizes (AIPE): Standardized Mean Difference

Usage

seq_aipe_smd(
  alpha = 0.05,
  omega,
  data = NULL,
  Group.1 = NULL,
  Group.2 = NULL,
  pilot = FALSE,
  m0 = 4,
  na.rm = TRUE
)

Arguments

`alpha`	The significance level. default is 0.05.
`omega`	omega
`data`	The data set for which to calculate the standardized mean difference.
`Group.1`	The data vector for the first group.
`Group.2`	The data vector for the second group.
`pilot`	Should a 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 calculated standardized mean difference, and an indicator of if the criterion has been satisfied.

Author(s)

Ken Kelley KKelley@nd.edu, Francis Bilson Darku FBilsonD@nd.edu, Bhargab Chattopadhyay Bhargab@iiitvadodara.ac.in

References

Kelley, K., Darku, F. B., \& Chattopadhyay, B. (2018). Accuracy in parameter estimation for a general class of effect sizes: A sequential approach. Psychological Methods, 23, 226–243.

Examples

pilot_ss <- seq_aipe_smd(alpha=0.05, omega=0.2, pilot=TRUE)
SLS <- matrix( rnorm(pilot_ss[1],mean=0,sd=1),
rnorm(pilot_ss[1], mean = 0, sd = 1), nrow=20, ncol= 2)
seq_aipe_smd(alpha=0.05, omega=0.2,data = SLS)

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