Main Types of Reliability
You need to know that when you conduct an experiment and measure something within the same sample under the same conditions, you should get the same result. It is called reliability. If your results differ every time you apply the same method and techniques, this method is unreliable, as well as the results of your research.
Reliability can be of four different types. You can assess it by comparing the results from different sets of tasks done with the help of the same method. These types are the following:
- Test-retest. It measures the consistency of the same test applied several times in a row.
- Interrater. You can see the consistency of the same test applied to different people.
- Parallel forms. You have different versions of the same test and want to check their consistency because you believe that they are equivalent.
- Internal consistency. It shows the consistency of the separate items within the test.
It shows the consistency of the separate items within the test.
Test-Retest Reliability
The measure of this type of reliability is defined by the application of the same test under the same conditions but at different periods or points in time. You use this measure when you research something that you expect to remain constant within the same sample and want to test it.
For example, you need the highest reliability of the test about work-life balance satisfaction. You administer a group of college students a survey about their levels of satisfaction with the work-life balance. The test is given on Monday, then - on Friday, and then in two weeks. Since there are no sufficient changes in the schedule during this period, the level of satisfaction is almost the same.
Importance
When you want to measure something at different points in time, you can come across many influences on the subjects of measurement. For example, the respondents may be in different moods every time, or they may experience some emotions related to external conditions. You use test-retest reliability measures to ensure that these factors have not affected the subject too much and that it has stayed the same. You need to know how well your method can resist these external conditions. The smaller the difference is between the two or three sets of obtained results, the higher test-retest reliability you will get.
Measurements
To measure this type of reliability, you need to give the same test to the same sample under the same external conditions at different points in time. Then, you can calculate the results and find the correlation between these tests.
You have developed a questionnaire to measure the activity preferences in a group of teenagers. Such preferences are unlikely to change significantly during a month. You give them this test once and then in two weeks and a month. The results are entirely different every time. It means that the test-retest reliability of your questionnaire is low.
How to Improve Test-Retest Reliability
Here are several tips on how to improve test-retest reliability by making changes in your methods and techniques.
- ✔️ If it is a test or questionnaire, formulate all the questions or statements in a way that will not influence the emotional perception, mood, or concentration of the participants.
- ✔️ While choosing the method of data collection, minimize the effects of external factors and check whether all the participants are influenced by the same conditions.
- ✔️ Slight changes can occur in participants even within the shortest periods of time, so you need to take this into account.
Interrater Reliability
This type is also known as interobserver reliability. It measures the level of agreement among different observers or researchers on the criteria of result assessment for the same subject. You can use this type when you need to measure scores or rates related to one or more variables but the measurements are performed by different people.
Suppose several observers are researching the aggressive behavior of kids in primary school. They need to agree on categorizing and rating different types of behavior. Or they will produce different opinions on in what form aggression is displayed and what to consider aggression at all.
Importance
People are rather subjective in their assessment. They perceive the same situation or phenomenon in different ways. Reliability here means that you need to minimize the effect of subjectivity on the results of research. That is why it is so important to develop unique criteria and scales for data collection and analysis to be sure that different people rate the same data consistently and do not implement biased judgments. It is important when there are many researchers or observers.
Measurements
When different observers measure the same subject or do the same observation, they need to ensure interrater reliability. You can see different sets of results, of course, but the correlation between them should be high. If the ratings of the test are similar, the research has high interrater reliability.
The team of researchers explores the positive influence of taking vitamins B6 and B12 on patients with insomnia. They should record different stages of improvements in their sleep patterns by using the established set of criteria to assess different aspects in various individuals. The results of every researcher who has evaluated the improvements in the same set of people show a strong correlation for all the researchers, so the test provides high interrater reliability. If the correlation is weak, this reliability is low.
How to Improve Interrater Reliability
We believe that the following tips will help to improve interrater reliability:
- ✔️ Be consistent about the variables and methods for measuring them.
- ✔️ Agree with your team about the objective criteria of measuring, rating, and calculating.
- ✔️ Check whether all the observers have received the same instructions and explanations.
Parallel Forms Reliability
This type measures the correlation between two equal versions of the same test. You can measure the same object with two sets of questions or assessment tools that are equivalent.
Importance
You can use this criterion when you want to avoid respondents who repeat the preliminary learned answers. Check whether all the versions of the test provide reliable results. This type of reliability is important in education and psychology research.
For example, researchers and teachers create different variants of the test or quiz to check that all the students know the material and have not had any access to answers before the test or during it. It means that if the same student has completed different versions of the same biology quiz, the result should be the same. It will indicate the high parallel forms reliability.
Measurements
The most commonly used way to check parallel forms reliability is to develop a large set of questions for the same subject or topic and then divide them into two sets. This division is random, so when the same group of participants answers both sets and you calculate the correlation between the results, it should be almost the same. If you get it, your test is parallel forms reliable.
You want to check how well your finance students understand the topic of banking loans. You compose 20 questions and randomly divide them into two sets. Then, you randomly divide the students into two groups, too, and offer them these two variants of the test. Be sure that both groups do both variants. First, group A does variant A, and group B does variant B. Then, group A does test B, and group B does test A. If the results are nearly identical for both variants in both groups, your test has high parallel forms reliability.
How to Improve Parallel Forms Reliability
There is only one suggestion here - check whether all the questions and items of the test are based on measuring the same phenomenon and based on the same theory.
Internal Consistency
If you want to measure the correlation between different items within the same test that is intended to measure the sole construct, look for internal consistency. You do not need to repeat the test many times or involve several researchers. You only have a single data set here and want to see how reliable it is.
Importance
If you develop a set of questions or rates that should result in an overall score, you need to ensure that every item in it corresponds to the same concept. If the items produce different or even contradictory results, the test is unreliable.
For example, if you want to measure the students’ satisfaction with their work-life balance, you compose a questionnaire with statements that the respondents need to agree or disagree with. If you check internal consistency, you will see that all the statements are trustworthy indicators of students’ satisfaction.
Measurements
You can use two methods to measure internal consistency:
- Calculate the average correlation between all possible pairs of items within a set. This method is known as average inter-item correlation.
- Calculate the correlation between the two sub-divisions of items you have randomly split. It is called split-half reliability.
You have a group of respondents whose task is to react to the set of statements about the positive or negative reaction to the recent improvements in the municipal sewage system. They assess their agreement or disagreement on a scale rating from 1 to 5.
If the test is reliable, those who appreciate these improvements provide a rating of 5, and those who are disappointed assess them as 1, while many responses range between 2 and 4. If most responses tend to be either 5 or 1, they do not demonstrate actual correlation because the statements might have been formulated unclearly or too difficult to choose one exact response. Such a test shows low internal consistency.
How to Improve Internal Consistency
All the questions or statements that are meant to support or reject the same concept should be based on the same theory. The formulation of these questions should be clear, concise, and consistent to exclude any misinterpretations.
Final Thoughts: What Type of Reliability Is More Suitable for Your Research?
You can now decide what type of reliability you need for your research. When you are planning the research design, you will mean to collect and analyze the necessary data that will help you make reliable and valid conclusions. Therefore, the type of reliability will depend on the research format and chosen methodology. Let’s consider some options for the accurate choice:
- If you want to measure the characteristic that is likely to remain the same for a long time, test-retest reliability is your best choice.
- If you have multiple researchers or observators in your project related to one topic or criterion, choose interrater reliability.
- If you want to offer two different variations of the same test or two tests for the same object, opt for parallel forms.
- When you develop all the items for measuring the same variable within a multi-item test, check the internal consistency of every item.
You can calculate the reliability statistically and mention the results of such calculation in your work. If you get the high reliability of all your methods and techniques, your research paper will be successful and allow you to make substantial academic progress.