Good research does not rely on hunches; it rests on the measurement that the reader can trust. That’s why every research design must have these two characteristics in it, i.e, reliability (consistency) and validity (accuracy).
Reliability tells us whether a measure gives stable results, whereas validity refers to whether those results reflect what you intend to measure or not. Together, both of these factors determine the quality of your findings from planning to completion.
However, ignoring these factors can lead to misleading data and weak conclusions. So, to avoid these issues, add them to your design choices analysis and sampling.
| Reliability | Validity | |
|---|---|---|
| What it shows | Consistency of results when repeated under similar conditions | Accuracy in measuring the intended concept |
| How it’s checked | Consistency across time, raters, and test parts | Agreement with theory and other accepted measures |
| Relationship | A measure can be reliable but not valid | Valid measures are generally reliable |
What is Reliability?
Reliability refers to the consistency of the measurement. It shows how trustworthy the score of the test is. 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. → reliable results.
- Example: If a teacher conducts the same math test for students and repeats it next week with the same questions. If she gets the same score, then the reliability of the test is high.
Note: Reliability is not sufficient on its own; that’s why it is necessary for validity.
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How to Assess Reliability?
Reliability can be measured by comparing the consistency of the procedure and its results. It can be measured through various statistical methods depending on the types of validity, as explained below:
Types of Reliability
| Type | What it measures | Example |
|---|---|---|
| Test–retest | It focuses on consistency of score instead of time. | Suppose a questionnaire is distributed among a group of people to check the quality of a skincare product, and the same questionnaire with many groups. If you get the same response from a variety of groups of participants, it means the validity of the questionnaire and product is high, as it has high test-retest reliability. |
| Inter-rater | This deals with the agreement between graders and observers. | 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 | Equivalence that includes different forms of the same test. | 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. |
| Internal consistency (split-half) | Consistency of 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. |
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.
What is Validity?
Validity is the accuracy of a measurement. It 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: If a scale shows different types of results of weight with no real change, it shows that our method lacks reliability, and the result is not valid.
- Example: If a skincare product questionnaire receives a similar response from different groups, it shows that the real user experience is great and the validity is high.
Types of Validity
| Type | What it measures | Example |
|---|---|---|
| Content validity | It shows whether all the aspects of the test/measurement are covered. | It includes a language test, including speaking, listening, reading, and writing |
| Face validity | It is about the validity of a test or procedure. | The type of questions included in the question paper, the time, and the 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) | A communication skills test actually does not capture memory but communication |
| Criterion validity | It shows whether the test scores obtained are similar to other measures of the same concept. | The results obtained from a pre-final exam of graduates accurately predict the results of the final exam. It shows that the test has high criterion validity. |
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.
- Example: Findings from research on pregnant women may not generalize to other normal women or men.
Threats to Internal Validity
| Threat | Definition | Example |
|---|---|---|
| Confounding factors | Unexpected events during the experiment that are not a part of the treatment. | If you gain weight due to sugar or coffee instead of a lack of exercise. |
| Maturation | The influence on the independent variable due to the passage of time. | Participants get tired of long studies |
| Testing | The results of one test affect the results of another test. | Participants of the first experiment may act differently during the second experiment. |
| Instrumentation | Changes in the instrument’s collaboration | A 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 pass 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. |
How to Assess Validity?
Validity is assessed by comparing the results with theory and other measures by gathering the evidence given by the test to construct relevant facets.
Threats of External Validity
| Threat | Definition | Example |
|---|---|---|
| Reactive/interactive effects of testing | The participants of the pre-test may gain awareness about the next experiment. The treatment may not be effective without the pre-test. | Students who failed in the pre-final exam are likely to pass 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 Increase Validity?
- 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.
- Inter-rater reliability should be ensured.
- The control and experimental groups should be matched with each other.
How to Implement Reliability and Validity in a Thesis?
| Section | How to include reliability and validity |
|---|---|
| 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. |
| Literature Review | Discuss the contribution of other researchers to improve reliability and validity. |
| Results | Include calculations of reliability and validity here. |
| Discussion | Please talk about the level of reliability and validity of your results and their influence on values. |
| Conclusion | Talk about the issues you faced while ensuring reliability and validity here. |
Frequently Asked Questions
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.
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.
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.
