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

seq_blci_dfr_mean

R Documentation

seq_blci_dfr_mean

Description

Purely Sequential approach to Get Bounded Length Confidence Interval for the median of distribution free random variables

Usage

seq_blci_dfr_mean(data, d, alpha, pilot = FALSE, verbose = FALSE, na.rm = TRUE)

Arguments

`data`	The data for which to calculate the confidence interval. A numeric vector.
`d`	Half of the confidence interval width, must be a non-zero positive value.
`alpha`	The significance level. A value between 0 and 1.
`pilot`	Should a pilot sample be generated. True/False value. default value is `FALSE`.
`verbose`	Should the criterion be printed. Default is `FALSE`.
`na.rm`	This parameter controls whether NA values are removed from the data prior to calculation. Default is `TRUE`.

Value

The calculated confidence interval, the sample size, data mean, and an indicator of if the confidence level was satisfied.

Author(s)

Bhargab Chattopadhyay Bhargab@iiitvadodara.ac.in, Neetu Shah 201451015@iiitvadodara.ac.in

References

Mukhopadhyay, N., \& de Silva, B. M. (2009). Sequential Methods and Their Applications. New York: CRC Press.

Examples

pilot_ss <- seq_blci_dfr_mean(alpha=0.05, d=1, pilot=TRUE)
SLS <- rnorm(pilot_ss, mean=0, sd=1)
seq_blci_dfr_mean(data=SLS, d=1, alpha=0.5, pilot=FALSE)

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