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Understanding Test-Retest Reliability: What It Is and Why It Matters

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Updated on
Modified on September 28, 2023

Reliability of assessment is crucial in education. Test-retest reliability is one of the most commonly practiced types of reliability methods and can be done fairly easily. Test-retest reliability is a statistical measure commonly used to assess the consistency and reproducibility of results obtained from healthy controls in research studies. While time between the first test and the second test differs, the same group of people receive the same test both times. Then, test administrators can determine reliability estimates based on the observations and correlations drawn between the two assessments.

Anyone doing assessments, whether in the psychological, educational, medical, or any other discipline, has to understand test-retest reliability. Without an understanding of how the test works and how to measure the results, reliable and accurate measurements cannot be drawn from assessments to help make informed decisions for the future.

Once a test-retest reliability coefficient has been found, the scores can be used to officially determine the stability and consistency of an assessment. Scores will range from poor reliability to excellent reliability, and sometimes even unacceptable or unassessable. Overall, a good test-retest reliability speaks to the reproducibility of an assessment and the successful results it can produce. 

Understanding Test-Retest Reliability

The most basic purpose of test-retest reliability is to determine if the same person would do as well on the exam if they took it again under identical circumstances. A basic level of understanding this type of reliability and the factors that can affect it will greatly influence the results.

Understanding of reliability must occur before, during, and after the method. Before administering the test, one must know the purpose of the test and how it works. During the process, understanding the internal and external factors that may influence or corrupt the reliability measures will improve outcomes. After gathering results from the test, it is crucial to understand how to measure and interpret the results. If one of these elements is missing, then the reliability of the process itself can be lost.

How Test-Retest Reliability Works

Test-retest reliability operates through three basic steps. First, the same test must be administered to the same group of individuals at two different times. Next, the correlation coefficient between the scores of the two assessments must be calculated. The final step is to interpret the correlation coefficient.

Just as benchmark assessments are used to track and assess student progress over time, test-retest reliability is used to assess stability and consistency over time. Both tests work in similar ways, in that they evaluate the effectiveness of education programs, assess student learning, and make data-driven decisions.

Factors Affecting Test-Retest Reliability

It is important to be aware of what factors may affect test-retest reliability to avoid or control these factors as much as possible. Minimizing the effects of several factors is critical for achieving high test-retest reliability. Therefore, the two tests should be administered with the same conditions and the same instructions. This can be challenging, but not impossible. 

Another factor to consider, along with the environment, is the amount of time between the two tests. If the second test is given too quickly, then test participants may remember their responses from the first test. At the same time, if too much time passes, then there are bigger changes that could occur during that time period that could affect the construct being measured.

Measuring Test-Retest Reliability

Once data has been collected, the reliability results can be measured. This is done by calculating the correlation coefficient. To do this, statistical analysis methods, like the Pearson correlation coefficient or Cronbach’s alpha, can be used to find the correlation or relationship between the two sets of scores. 

For example, Cronbach’s alpha measures the internal consistency reliability of a test on a baseline scale of 0 to 1. A score of 0.7 or higher is usually considered a good or high degree of consistency. A score of 0.5 or below indicates a poor or low consistency.

Importance of Test-Retest Reliability

Educational Assessment

Educational assessments are commonplace in the classroom. For example, reading comprehension is a literacy skill assessed from kindergarten through secondary education. Students may be given the same reading test a few months apart but with the same factors or conditions. Based on the results, educators will be able to determine how reliable the assessment is and whether or not changes need to be made.

Test-retest reliability is important in an educational setting because it helps educators figure out how consistent an assessment is measuring a certain skill over time. The reliability results can then help educators not only evaluate students in the present but also help make more informed decisions about instructional practices and curriculum development, such as aligning assessment to meet schoolwide literacy needs.

Improving Test-Retest Reliability

There are always ways to improve the reliability of the test-retest assessment method. Test results from this reliability method are vital for helping different fields with their research. Improving the test-retest reliability can be done throughout the assessment process. Improved reliability may also result from the use of suitable tests and measurements with high levels of test-retest repeatability.

It is important to understand and put these standards into practice because they are essential for guaranteeing accurate findings that may be utilized to make judgments. Below are some strategies to implement throughout the process to improve test-retest reliability.

Strategies for Designing Reliable Tests

Before administering the assessment, there are some strategies for designing reliable tests. This is an important foundational step because a test that is unreliable produces inconsistent results, which can lead to incorrect conclusions and decisions.

  • Clearly define the construct being measured. The very first thing to do is determine what skill, knowledge, trait, or ability is involved in the assessment and being measured.

  • Create a blueprint. This involves outlining specific objectives, content, structure, and formatting of the test. A good blueprint will even identify elements such as types of questions or tasks, number of items or sections, and/or level of difficulty. 

  • Pilot-test it. A small test run of the assessment can allow time to fix any issues with instructions, test items, or administration.

Best Practices for Administering Tests

Well-designed assessments, well-prepared students, and well-informed test administrators are all good practices of education. During the actual test itself, there are several best practices for administering the test.

  • Choose the right tool. Choosing the right assessment tool is dependent upon the construct being measured and the setting of the test. Whereas classrooms may use more standardized test tools, medical fields may use more equipment-based tools instead. 

  • Calculate the time. Many scholars recommend a two-week to two-month time frame between administering the two tests. A test readministered too soon could allow for recall of remembered or memorized answers, but a test too late could allow additional external factors to enter. 

  • Consistency is key. Controlling as many factors as possible can improve reliability of a test. Consistency should be present in instructions, testing conditions, equipment, timing, and environment of the assessment. Changes in any of these may skew the reliability.

Techniques for Improving the Reliability of Your Results

The reliability of a study refers to the consistency and accuracy of its results, and to ensure the results are reliable, it is important to implement techniques that can improve their consistency and accuracy.

  • Increase the number of test administrations. The more times the test is administered, the more reliable the results will be. A balance, however, must still be in place to avoid test fatigue. With more tests, more results can be analyzed, but this can also be done by increasing the sample size.  

  • Increase the sample size. Increasing the sample size can help improve the reliability of the results by reducing the impact of random measurement error. It may not always be an option to increase size, but if available, doing so may have a positive effect on improvement.

  • Use a statistical method. Understanding and using the right statistical methods to analyze the reliability of test-retest results may include measurements such as the Pearson correlation coefficient, the intraclass correlation coefficient, or the coefficient of variation.

Bottom Line

Reliability is a highly valued concept in research settings, academic classrooms, and in life in general. Something as simple as administering the same test to the same group of people at two different times is just one way of many to practice the pursuit of reliability. Each step of the process is important, from the beginning of designing the test to the interpretation and application of the results.

Creating a systemwide support system to gather and analyze data is important for educators. Dr. Courtney Wheeler, research associate at the Center for Applied Research and Educational Improvement at the University of Minnesota, states:  “Systems are more likely to be effective when educators are able to utilize the data they are collecting to inform systemwide decision-making and support.” Test-retest reliability is just one way educators, and other settings as well, can increase reliability in their fields.

At Voyager Sopris Learning®, we strive to offer strategies to prepare students for testing as well as strategies to prepare teachers for assessing. We believe in reliability in the classroom, and we believe in supporting teachers as they design reliable tests and analyze the data.