TE Taylor Enterprises, Inc.
www.variation.com
Quality and Statistics
Books, Software, Training and Consulting


Search variation.com

Enter keywords: 

Exact Match Search

 

Site Map

Products (HOME)

Books

Software

Courses

Consulting


Expertise

Acceptance Sampling

Process Validation

CAPAs and Trending of Quality Data

FMEA

Measurement Systems Analysis

Spec Setting, Tolerance Analysis and Robust Design

General Statistics

Statistical Process Control

Design of Experiments

Six Sigma


Store  

What's New

Technical Library

FAQ


  Contact Info

Chairman
Dr. Wayne A. Taylor   linkedin
President
Ann Taylor
Telephone
1 (847) 367-1032
FAX
1 (847) 367-1037
Postal address
5510 Fairmont Rd.
Libertyville, IL 60048
USA
Electronic mail
info@variation.com
Web
www.variation.com

 

Subscribe to our Web Site

By entering your e-mail address and clicking the Subscribe button, you will automatically be added to our mailing list.  You will receive an e-mail when new versions of our software or books are available as well as other significant announcements.  (privacy policy).

E-mail address to send notifications to:

    

       Statistical Procedures for the Medical Device Industry    Statistical Procedures for the Medical Device Industry   

STAT-16: Statistical Techniques for Equivalence Testing

Purpose

This procedure provides statistical techniques for demonstrating equivalence of a new product or process to an existing product or process. This is an alternate approach to demonstrating the product or process meets established requirements per the following procedures:.

Appendices

  1. Confidence Limits for the Difference between Two Averages
  2. Equivalence Test for Two Averages
  3. Confidence Limits for the Difference between Two Averages—Paired Data
  4. Equivalence Test for Two Averages—Paired Data
  5. Confidence Limits for the Ratio of Two Standard Deviations
  6. Equivalence Test for Two Standard Deviations

Highlights

  •  Equivalence does not mean identical.  It means the difference is less than some predetermined difference Δ.

  •  Demonstrating equivalence requires defining a difference Δ that is considered significant and then demonstrating with high confidence the different is less than Δ..  Equivalence tests are based on confidence intervals.  The validated spreadsheet STAT-12 to 16 - Confidence Intervals and Equivalence Tests.xlsx  accompanying the book can be used for performing equivalence tests.  For example, suppose a difference of 2 or more is considered a significance difference.  As shown below, the 95 confidence interval for the difference is between -2 and 2 so one can claim equivalence.  

                    Equivalence Test

  •  Procedures for calculating sample size are provided.  However, a passing equivalence test is valid regardless of the sample size used.  For smaller sample sizes the confidence intervals will be wider, making it harder to pass.  The risk of too small a sample size is falsely failing the equivalence test.  The procedure for calculating sample size is too ensure a reasonable chance of passing equivalent groups.

  • Equivalence tests cannot be chained together.  B is equivalent to A and C is equivalent to B does not mean C is equivalent to A.  The difference could be 2 times Δ.  One must prove directly that C is equivalent to A.  An alternate approach is to use A to establish specification limits and then show B and C meet the specification limits.  Setting specification limits is described in STAT-11, Statistical Techniques for Setting Specifications.

  • A t-test by itself is not a valid approach for demonstrating equivalence.  If it is believed that equivalence testing requires fewer samples than demonstrating the specification limits are meet, equivalence testing is being done wrong.  Equivalence testing is generally used when there are not specification limits.

 


Copyright 1997-2017 Taylor Enterprises, Inc.
Last modified: September 08, 2017