LR.twoT

a postive numeric (integer); number of samples from Group-1 for computing the BF.

a postive numeric (integer); number of samples from Group-2 for computing the BF.

numeric; the value of sufficient statistic based on <code>m1</code> samples from Group-1.
In this case, the sufficient statistic is the mean of these <code>m1</code> observations.

suff.stat1

numeric; the value of sufficient statistic based on <code>m2</code> samples from Group-2.
In this case, the sufficient statistic is the mean of these <code>m2</code> observations.

suff.stat2

a numeric; the hypothesized value under the simple alternative.

a positive numeric; pooled sample standard deviation using <code>m1</code> observations from Group-1 and <code>m2</code> observations from Group-2.

Given the simple null equals to 0 and a simple alternative hypothesis, this function calculates the bayes factor (BF) in favor of the alternative based on an observed data in two-sample T-tests.

A modified SPRT (MSPRT) can be designed and implemented with the help of this package. In a
MSPRT design, (i) the maximum sample size of an experiment is fixed prior to the start of an
experiment; (ii) the alternative hypothesis used to define the rejection region of the test is derived
from the size of the test (Type I error), the maximum available sample size (N), and (iii) the targeted Type 2
error (equals to 1 minus the power) is also prespecified. Given these values, the MSPRT is defined in a
manner very similar to Wald's initial proposal. This test can reduce the average sample size required to
perform statistical hypothesis tests at the specified level of significance and power. This package
implements one-sample proportion tests, one-sample Z-tests, one-sample T-tests, two-sample
Z-tests and two-sample T-tests. A user guidance for this package is provided here.
One can also refer to the supplemental information for the same.

LR.twoT: Bayes factor in two-sample T-tests

Description

Usage

Arguments

Value

References

Examples