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MSPRT (version 2.1)

A Modified Sequential Probability Ratio Test (MSPRT)

Description

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.

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Version

Install

install.packages('MSPRT')

Monthly Downloads

204

Version

2.1

License

GPL (>= 2)

Maintainer

Sandipan Pramanik

Last Published

August 19th, 2019

Functions in MSPRT (2.1)

OC.MSPRT

Operating characteristics for a MSPRT
LR.twoT

Bayes factor in two-sample T-tests
LR.oneProp

Likelihood ratio in one-sample proportion tests
design.MSPRT

Designing a MSPRT
LR.oneZ

Likelihood ratio in one-sample Z-tests
LR.oneT

Bayes factor in one-sample T-tests
LR.twoZ

Likelihood ratio in two-sample Z-tests
check

Sequential checking
compmerge.list

Merging two lists componentwise
MSPRT-package

MSPRT
objfunc.oneProp

Objective function for determining the UMPBT point alternative in one-sample proportion tests
overshoot.oneProp

Error summary of the truncated Wald's SPRT in one-sample proportion tests
find.threshold.oneProp

Optimizing the UMPBT objective function in fixed design one-sample proportion tests
ovr.repl.twoT

A particular replication step in overshoot.twoT()
ovr.repl.oneZ

A particular replication step in overshoot.oneZ()
implement.MSPRT

Implementing a MSPRT
type2.error.oneProp

Type 2 error function of one-sample proportion tests in a fixed design
effective.N

Determining the 'effective maximum sample size' in MSPRT for one-sample proportion tests
error.summary

Error probabilities of a MSPRT
type2.error.oneT

Type 2 error function of one-sample T-tests in a fixed design
overshoot.twoT

Error summary of the truncated Wald's SPRT in two-sample T-tests
find.alt

Finding the `fixed design alternative'
umpbt.oneProp

The UMPBT alternative used in the MSPRT in one-sample proportion tests
point.umpbt.oneProp

The UMPBT point alternative in one-sample proportion tests
ovr.repl.twoZ

A particular replication step in overshoot.twoZ()
type2.error.twoZ

Type 2 error function of two-sample Z-tests in a fixed design
find.samplesize

Sample size required to achieve a higher significance for one-sample tests in a fixed design
umpbt.oneZ

The UMPBT alternative in one-sample Z-tests
umpbt.twoT

The UMPBT alternative in two-sample T-tests
ump.match.oneProp

Finding the "evidence threshold (\(\delta\))" in one-sample proportion tests in a fixed design
overshoot.oneZ

Error summary of the truncated Wald's SPRT in one-sample Z-tests
overshoot.oneT

Error summary of the truncated Wald's SPRT in one-sample T-tests
ovr.repl.oneProp

A particular replication step in overshoot.oneProp()
overshoot.twoZ

Error summary of the truncated Wald's SPRT in two-sample Z-tests
umpbt.twoZ

The UMPBT alternative in two-sample Z-tests
ovr.repl.oneT

A particular replication step in overshoot.oneT()
umpbt.oneT

The UMPBT alternative in one-sample T-tests
type2.error.twoT

Type 2 error function of two-sample T-tests in a fixed design
type2.error.oneZ

Type 2 error function of one-sample Z-tests in a fixed design