# Compare pairs

Compare Pairs examines related samples and makes inferences about the differences between them.

Related samples occur when observations are made on the same set of items or subjects at different times, or when another form of matching has occurred. If the knowing the values in one sample could tell you something about the values in the other sample, then the samples are related.

There are a few different study designs that produce related data. A paired study design takes individual observations from a pair of related subjects. A repeat measures study design takes multiple observations on the same subject. A matched pair study design takes individual observations on multiple subjects that are matched on other covariates. The purpose of matching similar subjects is often to reduce or eliminate the effects of a confounding factor.

**Difference plot**

A difference plot shows the differences between two observations on the same sampling unit.**Equality of means/medians hypothesis test**

An equality hypothesis test formally tests if two or more population means/medians are different.**Equivalence of means hypothesis test**

An equivalence hypothesis test formally tests if two population means are equivalent, that is, practically the same.**Difference between means/medians effect size**

An effect size estimates the magnitude of the difference between two means/medians.

**Available in Analyse-it Editions**

Standard edition

Method Validation edition

Quality Control & Improvement edition

Ultimate edition

- What is Analyse-it?
- What's new?
- Administrator's Guide
- User's Guide
- Statistical Reference Guide
- Distribution
- Compare groups
- Compare pairs
- Difference plot
- Creating a Tukey mean-difference plot
- Equality of means/medians hypothesis test
- Equivalence of means hypothesis test
- Tests for means/medians
- Testing equality of means/medians
- Testing equivalence of means
- Difference between means/medians effect size
- Estimators for the difference in means/medians
- Estimating the difference between means/medians
- Study design
- Contingency tables
- Correlation and association
- Principal component analysis (PCA)
- Factor analysis (FA)
- Item reliability
- Fit model
- Method comparison
- Measurement systems analysis (MSA)
- Reference interval
- Diagnostic performance
- Control charts
- Process capability
- Pareto analysis
- Study Designs
- Bibliography

Version 5.65

Published 14-Aug-2020