## What is a matched pairs study?

A matched pairs design is a type of experimental design wherein study participants are matched based on key variables, or shared characteristics, relevant to the topic of the study. Then, one member of each pair is placed into the control group while the other is placed in the experimental group.

**What is a matched pairs experiment example?**

For example, Pair 1 might be two women, both age 21. Pair 2 might be two men, both age 21. Pair 3 might be two women, both age 22; and so on. For this hypothetical example, the matched pairs design is an improvement over a completely randomized design.

**What is matched pairs in psychology?**

3. Matched Pairs: A matched pairs design is an experimental design where pairs of participants are matched in terms of key variables, such as age or socioeconomic status. One member of each pair is then placed into the experimental group and the other member into the control group.

### What is the matched pairs technique?

A matched pairs design is an experimental design where participants having the same characteristics get grouped into pairs, then within each pair, 1 participant gets randomly assigned to either the treatment or the control group and the other is automatically assigned to the other group.

**What is the benefit of a matched pairs design?**

Now the two groups are matched in terms of both age and gender. Differences between the group means can no longer be explained by differences in age or gender of the participants. The primary advantage of the matched pairs design is to use experimental control to reduce one or more sources of error variability.

**What is a paired experiment?**

“A matched pairs design is a special case of a randomized block design. It can be used when the experiment has only two treatment conditions; and subjects can be grouped into pairs, based on some blocking variable. Then, within each pair, subjects are randomly assigned to different treatments.”

#### What is a paired data experiment?

Paired samples (also called dependent samples) are samples in which natural or matched couplings occur. This generates a data set in which each data point in one sample is uniquely paired to a data point in the second sample.

**What is the purpose of matching study participants?**

The goal of matching is to reduce bias for the estimated treatment effect in an observational-data study, by finding, for every treated unit, one (or more) non-treated unit(s) with similar observable characteristics against who the covariates are balanced out.

**What is the difference between a paired and unpaired t-test?**

A paired t-test is designed to compare the means of the same group or item under two separate scenarios. An unpaired t-test compares the means of two independent or unrelated groups. In an unpaired t-test, the variance between groups is assumed to be equal.

## How do you calculate DF for a paired t-test?

We can compute the p-value corresponding to the absolute value of the t-test statistics (|t|) for the degrees of freedom (df): df=n−1. If the p-value is inferior or equal to 0.05, we can conclude that the difference between the two paired samples are significantly different.

**How do I know if my data is unpaired?**

This data is described as unpaired or independent when the sets of data arise from separate individuals or paired when it arises from the same individual at different points in time.

**What is a matched pairs design in psychology?**

Matched Pairs Design: Definition + Examples A matched pairs design is an experimental design that is used when an experiment only has two treatment conditions. The subjects in the experiment are grouped together into pairs based on some variable they “match” on, such as age or gender.

### How many subjects are needed to perform a matched pairs design?

Since this experiment only has two treatment conditions (new diet and standard diet), they can use a matched pairs design. They recruit 100 subjects, then group the subjects into 50 pairs based on their age and gender. For example:

**When is a matched pairs design better than a randomized trial?**

A matched pairs design is better than a simple randomized trial when we want to enforce a balance between important participant characteristics that may influence the outcome. For example, a lot of outcomes are gender and age specific. Therefore, matching individuals on these 2 variables will help improve the validity of the study by reducing bias.

**What is a matched pair case-control study?**

The Matched Pair Case-Control Study calculates the statistical relationship between exposures and the likelihood of becoming ill in a given patient population. This study is used to investigate a cause of an illness by selecting a non-ill person as the control and matching the control to a case.