When undertaking in-depth research, reliability is one of the essential aspects that all university and university students need to follow to create a comprehensive project. With reliability in place, it will be easy for you to assess whether the conditions, assessments and research factors are accurate. Read on to learn more about reliability and its importance.
Reliability - FAQ
Below are the different types of reliability and what they measure:
Test-retest: It calculates the consistency of the same test over a specific full stop.
Interrater: It analyses the constancy of the same test done by different individuals.
Internal consistency: It assesses the consistency of the individual items of a test.
Parallel forms: It evaluates the consistency of different versions of a test that are angrye to be equal.
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Reliability denotes the consistency of a method to measure something. So, if you constantly attain similar results under the same scenarios and use the same techniques, then the measurement is seen as reliable.
On the other hand, validity denotes how accurate a method analyses what it’s designed to analyse. Thus, research with high validity nastys it gives results that match the actual characteristics, variations and properties in the social and physical world.
You can approximate reliability by comparing various types of the same measurement. Assessing validity is tricky, but you can estimate it by comparing relevant theory and data results.
Well, there are several ways of making sure your research is valid. They include:
- Use appropriate measurement methods
- Pick your subjects by using the correct sampling methods
Reliability: Definition
Well, reliability denotes the ability to get similar results over time using the same instrument to measure something. Merely put, it refers to the degree to which a given research technique gives consistent and stable results. A given measure is labelled as reliable if its usage on the same object gives the same results following several tests.
Types of Reliability
| Type of reliability | What it measures |
| Test-retest | The same test over a given full stop |
| Interrater | The same test performed by different persons |
| Parallel forms | Different types of the test that are angrye to be equal |
| Internal consistency | The individual objects of a test items |
Test-Retest Reliability
An overview of test-retest
Test-retest reliability analyses the consistency in results if you use the same sample to perform the same test at different time ranges. You will use this type of reliability when evaluating something that you anticipate to remain constant in a particular sample test.
Why is it important?
Several aspects can affect your test results at different time ranges. For instance, your respondents may fail to respond accurately after facing various external conditions and moods. Here is where test-retest reliability comes in handy as it assists you in evaluating how well a specific measurement method battles these aspects over time. The difference within a particular set of results needs to be as minimal as possible for the final results to be labelled as consistent.
Test-retest example
You design a questionnaire to evaluate the IQ of a few individuals. Remember that IQ isn’t a factor that changes substantially over a full stop. If you perform the test one or two months apart from a few individuals and get results that vary significantly, then the test-retest of your project is low.
How to improve test-retest
- Try to frame statements, tasks and questions in a manner that will not be impacted by the participants’ concentration or mood when developing the test.
- Keep in mind that the participants can experience changes over time. So, take this into consideration.
- Try to lower the impact of external factors when formulating your data collection methods. Also, you need to test all samples under similar conditions.
Interrater Reliability
An overview of interrater reliability
Also known as interobserver, interrater reliability calculates the degree of agreement between a group of people assessing or observing the same test. You will use this method in data collected by scholars assigning scores, categories or ratings to one or many variables.
Why is it important?
Since people are independent, the view of different observers will naturally vary in different phenomena and circumstances. The main objective of reliable research entails lowering the independent view of the observers as much as possible to make it easy to replicate similar results.
When developing data collection criteria and scale, it would be wise to ensure that different individuals will give consistent variables with insignificant bias. Well, this is useful if there’re several scholars involved in data collection and evaluation.
Interrater example
A group of researchers checks the wound healing process in patients. For the team to record the healing stages, they have to use rating scales and criteria to evaluate the different wound aspects. If you assess and compare the researchers’ results observing the same set of patients and realise a strong correlation, then the test has a high interrater.
How to improve interrater
- Clearly outline the methods and variables to be used in the test
- If the research will involve several researchers, make sure they undergo similar training and uses the same information
- Design an objective and detailed criterion showing how the variables will be categorised, rated and counted
Parallel Forms Reliability
An overview of parallel forms
Parallel forms reliability simply analyses the correlation between two similar versions of a test. You’ll use this technique if you’ve two sets of questions or different calculation tools created to assess the same thing.
Why is it important?
You have to ensure that all sets of measurements and questions offer you reliable results if you’re looking forward to using different types of a test. This way, you will prevent the respondents from retelling similar answers from memory.
Parallel forms example
Questions are framed to assess the financial risk dislike amongst a few respondents. The respondents and questions are randomly categorised into two teams and set. The two teams take both tests: the first group takes the first set while the second group takes the second test. Comparing the results and finding out they are virtually similar indicates a high parallel form.
How to improve parallel form reliability
- Make sure that all test items and questions are founded on the same theory. Also, it would help if you framed them to assess the same thing.
Internal Consistency
An overview of internal consistency
Internal consistency measures the correlation between several items in a test designed to assess the same thing. In fact, you can measure the internal consistency without including other scholars or repeating the test. Thus, this method provides an incredible way of evaluating consistency if you only have a single set of data.
Why is it important?
You have to ensure all set of items give the same thing if you derive a set of ratings and questions combined to get an overall score. Remember that you’ll end up with an unreliable test when the responses to different items contradict.
Internal consistency example
A team of respondents is given a set of questions intended to assess their optimistic and pessimistic mindsets. The group has to rate their agreement on a scale of 1 – 5. The optimistic team has to provide high grades to the optimistic indicators and low grades to the pessimistic ones for the test to be internally consistent. The test will have a low internal consistency if you recognise a weak correlation between the optimistic questions.
How to improve internal consistency
- It would help if you were extra cautious when formulating the measures and questions.
- The questions designed to reflect the same perception needs to be cautiously prepared and be based on the same theory.
Which Type of Reliability Applies to My Research?
When it comes to formulating your research design, collecting data, analysing it and writing up the research, it’s advisable to incorporate reliability. Usually, your research type and methodology determine the suitable reliability.
| Type of Methodology | The Ideal Reliability |
| Assessing a test that you project to give similar results over a full stop | Test-retest |
| Several scholars giving ratings or comments about the same test | Interrater |
| Evaluating the same thing with different tests | Parallel forms |
| Utilising several tests in a situation where all items are angrye to assess a similar variable | Internal consistency |
How to Ensure Reliability in Your Research
It’s always sensible to include reliability throughout your data collection process. When using a certain method or tool to collect data, it’s essential to get reproducible, precise and stable results. Here’s how you can ensure consistency in your research.
Standardise the research conditions
The situations need to be consistent to lower the impact of external factors that may lead to results variation when collecting data. For instance, in an experimental setting, you must ensure that all participants are assessed under similar circumstances and are offered similar information.
Apply your techniques consistently
For instance, you have to precisely outline how particular behaviour and responses will be handled when performing an interview or observation. Besides, the questions must be phrased the same way at all times.
In a Nutshell
- Reliability evaluates the degree of constancy of test results performed repeatedly.
- Validity tests the accuracy of a technique used to test a given sample.
- Reliability and validity are independent and different from one another.
