Reliability and Validity – Definitions, Types & Examples
Published by at August 16th, 2021 , Revised On October 26, 2023
A researcher must test the collected data before making any conclusion. Every research design needs to be concerned with reliability and validity to measure the quality of the research.
What is Reliability?
Reliability refers to the consistency of the measurement. Reliability shows how trustworthy is the score of the test. If the collected data shows the same results after being tested using various methods and sample groups, the information is reliable. If your method has reliability, the results will be valid.
Example: If you weigh yourself on a weighing scale throughout the day, you’ll get the same results. These are considered reliable results obtained through repeated measures.
Example: If a teacher conducts the same math test of students and repeats it next week with the same questions. If she gets the same score, then the reliability of the test is high.
What is the Validity?
Validity refers to the accuracy of the measurement. Validity shows how a specific test is suitable for a particular situation. If the results are accurate according to the researcher’s situation, explanation, and prediction, then the research is valid.
If the method of measuring is accurate, then it’ll produce accurate results. If a method is reliable, then it’s valid. In contrast, if a method is not reliable, it’s not valid.
Example: Your weighing scale shows different results each time you weigh yourself within a day even after handling it carefully, and weighing before and after meals. Your weighing machine might be malfunctioning. It means your method had low reliability. Hence you are getting inaccurate or inconsistent results that are not valid.
Example: Suppose a questionnaire is distributed among a group of people to check the quality of a skincare product and repeated the same questionnaire with many groups. If you get the same response from various participants, it means the validity of the questionnaire and product is high as it has high reliability.
Most of the time, validity is difficult to measure even though the process of measurement is reliable. It isn’t easy to interpret the real situation.
Example: If the weighing scale shows the same result, let’s say 70 kg each time, even if your actual weight is 55 kg, then it means the weighing scale is malfunctioning. However, it was showing consistent results, but it cannot be considered as reliable. It means the method has low reliability.
Internal Vs. External Validity
One of the key features of randomised designs is that they have significantly high internal and external validity.
Internal validity is the ability to draw a causal link between your treatment and the dependent variable of interest. It means the observed changes should be due to the experiment conducted, and any external factor should not influence the variables.
Example: age, level, height, and grade.
External validity is the ability to identify and generalise your study outcomes to the population at large. The relationship between the study’s situation and the situations outside the study is considered external validity.
Also, read about Inductive vs Deductive reasoning in this article.
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Threats to Interval Validity
| Threat | Definition | Example |
|---|---|---|
| Confounding factors | Unexpected events during the experiment that are not a part of treatment. | If you feel the increased weight of your experiment participants is due to lack of physical activity, but it was actually due to the consumption of coffee with sugar. |
| Maturation | The influence on the independent variable due to passage of time. | During a long-term experiment, subjects may feel tired, bored, and hungry. |
| Testing | The results of one test affect the results of another test. | Participants of the first experiment may react differently during the second experiment. |
| Instrumentation | Changes in the instrument’s collaboration | Change in the research question may give different results instead of the expected results. |
| Statistical regression | Groups selected depending on the extreme scores are not as extreme on subsequent testing. | Students who failed in the pre-final exam are likely to get passed in the final exams; they might be more confident and conscious than earlier. |
| Selection bias | Choosing comparison groups without randomisation. | A group of trained and efficient teachers is selected to teach children communication skills instead of randomly selecting them. |
| Experimental mortality | Due to the extension of the time of the experiment, participants may leave the experiment. | Due to multi-tasking and various competition levels, the participants may leave the competition because they are dissatisfied with the time-extension even if they were doing well. |
Threats of External Validity
| Threat | Definition | Example |
|---|---|---|
| Reactive/interactive effects of testing | The participants of the pre-test may get awareness about the next experiment. The treatment may not be effective without the pre-test. | Students who got failed in the pre-final exam are likely to get passed in the final exams; they might be more confident and conscious than earlier. |
| Selection of participants | A group of participants selected with specific characteristics and the treatment of the experiment may work only on the participants possessing those characteristics | If an experiment is conducted specifically on the health issues of pregnant women, the same treatment cannot be given to male participants. |
How to Assess Reliability and Validity?
Reliability can be measured by comparing the consistency of the procedure and its results. There are various methods to measure validity and reliability. Reliability can be measured through various statistical methods depending on the types of validity, as explained below:
Types of Reliability
| Type of reliability | What does it measure? | Example |
|---|---|---|
| Test-Retests | It measures the consistency of the results at different points of time. It identifies whether the results are the same after repeated measures. | Suppose a questionnaire is distributed among a group of people to check the quality of a skincare product and repeated the same questionnaire with many groups. If you get the same response from a various group of participants, it means the validity of the questionnaire and product is high as it has high test-retest reliability. |
| Inter-Rater | It measures the consistency of the results at the same time by different raters (researchers) | Suppose five researchers measure the academic performance of the same student by incorporating various questions from all the academic subjects and submit various results. It shows that the questionnaire has low inter-rater reliability. |
| Parallel Forms | It measures Equivalence. It includes different forms of the same test performed on the same participants. | Suppose the same researcher conducts the two different forms of tests on the same topic and the same students. The tests could be written and oral tests on the same topic. If results are the same, then the parallel-forms reliability of the test is high; otherwise, it’ll be low if the results are different. |
| Inter-Term | It measures the consistency of the measurement. | The results of the same tests are split into two halves and compared with each other. If there is a lot of difference in results, then the inter-term reliability of the test is low. |
Types of Validity
As we discussed above, the reliability of the measurement alone cannot determine its validity. Validity is difficult to be measured even if the method is reliable. The following type of tests is conducted for measuring validity.
| Type of reliability | What does it measure? | Example |
|---|---|---|
| Content validity | It shows whether all the aspects of the test/measurement are covered. | A language test is designed to measure the writing and reading skills, listening, and speaking skills. It indicates that a test has high content validity. |
| Face validity | It is about the validity of the appearance of a test or procedure of the test. | The type of questions included in the question paper, time, and marks allotted. The number of questions and their categories. Is it a good question paper to measure the academic performance of students? |
| Construct validity | It shows whether the test is measuring the correct construct (ability/attribute, trait, skill) | Is the test conducted to measure communication skills is actually measuring communication skills? |
| Criterion validity | It shows whether the test scores obtained are similar to other measures of the same concept. | The results obtained from a prefinal exam of graduate accurately predict the results of the later final exam. It shows that the test has high criterion validity. |
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How to Increase Reliability?
- Use an appropriate questionnaire to measure the competency level.
- Ensure a consistent environment for participants
- Make the participants familiar with the criteria of assessment.
- Train the participants appropriately.
- Analyse the research items regularly to avoid poor performance.
How to Increase Validity?
Ensuring Validity is also not an easy job. A proper functioning method to ensure validity is given below:
- The reactivity should be minimised at the first concern.
- The Hawthorne effect should be reduced.
- The respondents should be motivated.
- The intervals between the pre-test and post-test should not be lengthy.
- Dropout rates should be avoided.
- The inter-rater reliability should be ensured.
- Control and experimental groups should be matched with each other.
How to Implement Reliability and Validity in your Thesis?
According to the experts, it is helpful if to implement the concept of reliability and Validity. Especially, in the thesis and the dissertation, these concepts are adopted much. The method for implementation given below:
| Segments | Explanation | |
|---|---|---|
| Methodology | All the planning about reliability and validity will be discussed here, including the chosen samples and size and the techniques used to measure reliability and validity. | |
| Discussion | Please talk about the level of reliability and validity of your results and their influence on values. | |
| Literature Reviews |
|
|
| Conclusion | Talk about the issues you faced while ensuring reliability and validity here. | |
| Results | Include calculations of reliability and validity here. |
Frequently Asked Questions
Reliability in research refers to the consistency and stability of measurements or findings. Validity relates to the accuracy and truthfulness of results, measuring what the study intends to. Both are crucial for trustworthy and credible research outcomes.
Validity in research refers to the extent to which a study accurately measures what it intends to measure. It ensures that the results are truly representative of the phenomena under investigation. Without validity, research findings may be irrelevant, misleading, or incorrect, limiting their applicability and credibility.
Reliability in research refers to the consistency and stability of measurements over time. If a study is reliable, repeating the experiment or test under the same conditions should produce similar results. Without reliability, findings become unpredictable and lack dependability, potentially undermining the study’s credibility and generalisability.
In psychology, reliability refers to the consistency of a measurement tool or test. A reliable psychological assessment produces stable and consistent results across different times, situations, or raters. It ensures that an instrument’s scores are not due to random error, making the findings dependable and reproducible in similar conditions.
Test-retest reliability assesses the consistency of measurements taken by a test over time. It involves administering the same test to the same participants at two different points in time and comparing the results. A high correlation between the scores indicates that the test produces stable and consistent results over time.
- Standardise procedures and instructions.
- Use consistent and precise measurement tools.
- Train observers or raters to reduce subjective judgments.
- Increase sample size to reduce random errors.
- Conduct pilot studies to refine methods.
- Repeat measurements or use multiple methods.
- Address potential sources of variability.
Reliability refers to the consistency and repeatability of measurements, ensuring results are stable over time. Validity indicates how well an instrument measures what it’s intended to measure, ensuring accuracy and relevance. While a test can be reliable without being valid, a valid test must inherently be reliable. Both are essential for credible research.
Interviews can be both reliable and valid, but they are susceptible to biases. The reliability and validity depend on the design, structure, and execution of the interview. Structured interviews with standardised questions improve reliability. Validity is enhanced when questions accurately capture the intended construct and when interviewer biases are minimised.
IQ tests are generally considered reliable, producing consistent scores over time. Their validity, however, is a subject of debate. While they effectively measure certain cognitive skills, whether they capture the entirety of “intelligence” or predict success in all life areas is contested. Cultural bias and over-reliance on tests are also concerns.
Questionnaires can be both reliable and valid if well-designed. Reliability is achieved when they produce consistent results over time or across similar populations. Validity is ensured when questions accurately measure the intended construct. However, factors like poorly phrased questions, respondent bias, and lack of standardisation can compromise their reliability and validity.
