What are order effects and can you provide some examples?

Order effects refer to the influence that the order of presentation of items or tasks has on the outcome or response of an individual. This can occur in various settings, such as in research studies, decision-making processes, or everyday interactions. The order in which information is presented can impact the way it is perceived, interpreted, and remembered. For example, in a research study, the first question or task may prime the participant’s response to the following questions or tasks, leading to a biased outcome. In a sales pitch, the order in which products are presented can influence the customer’s purchasing decision. Overall, order effects highlight the importance of considering the sequence of information or tasks in any situation to minimize bias and ensure accurate results.

What Are Order Effects? (Explanation & Examples)


Often in experimental studies, researchers will have participants provide responses to several different treatments.

In these types of studies, order effects refer to differences in participant responses as a result of the order in which treatments are presented to them.

For example, suppose researchers measure the percentage of free throws made by basketball players in which each player is instructed to shoot 10 free throws using a certain technique – A, B, or C – when shooting.

Here are the various orders in which players could shoot the free throws:

  • ABC
  • ACB
  • BCA
  • BAC
  • CAB
  • CBA

Regardless of whether or not one technique is better, it’s likely that players will become slightly tired or fatigued by time they use the last technique which means they’ll likely perform worst using that technique.

This is an example of an order effect. The order in which players try each technique has an effect on the percentage of free throws they make.

Types of Order Effects

There are several different types of order effects that can occur in experiments, including:

Practice Effects: Participants may become better at a certain task as they become more familiar with the testing environment. For example, participants may become faster in the latter trials of experiments that measure response time simply because they’ve had practice in previous trials.

Fatigue Effects: Participants may perform worse near the end of an experiment simply because they’ve become fatigued from performing some task over and over again.

Boredom Effects: Participants may perform worse near the end of an experiment simply because they get bored if a task is overly repetitive or long. 

Participants may respond to treatments differently depending on the treatment they were exposed to previously. For example, in experiments in which participants have to estimate the weight of objects they are likely to be influenced by how heavy the previous object was that they esimated.

In any experiment involving repeated measurements of the same individuals, one or more of these order effects may appear which could skew the results.

How to Prevent Order Effects

Depending on the type of order effect expected to occur, researchers can take the following steps to prevent them:

Practice Effects: To prevent practice effects, researchers could give each participant some time to warm up with the task to prevent them from getting better at the task during the experiment.

Boredom Effects: To prevent boredom effects, researchers could make a task shorter or add more variation to prevent boredom. 

Carryover Effects: To prevent carryover effects, researchers could add more time in between tasks so participants aren’t influenced by their previous trial.

Order Effects

On Using Counterbalancing

In any experiment involving repeated measurements of the same individuals, researchers can implement counterbalancing – a technique in which every possible order of treatments is used the same number of times. 

For example, in the previous basketball experiment we could have 5 players shoot free throws using the order of ABC, another 5 players shoot using the order of ACB, another 5 players shoot using the order of BCA, and so on.

By using each order the same number of times, we can “counterbalance” any order effects. The downside of this method is that it can be too time-consuming or costly to actually implement every order an equal number of times. 

For example, if we have three different treatment conditions then the total number of unique orders would be 3! = 6. If we have four treatment conditions, this number jumps up to 4! = 24. If we have five treatment conditions, it becomes 5! = 120. This number can quickly become unreasonable to implement in a study.

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