Reliability or Validity
The quality of research depends on many factors, including the qualifications of a researcher and the layout of the study. The research quality is accessed with the help of such criteria as reliability and validity. They show how correctly testing measures, techniques, and methods are picked out. However, these notions mean different things. While reliability is about the consistency of measurements, validity means measurement accuracy.
Reliability and validity are essential to consider when you make up a research design. Its correctness is essential, especially in quantitative research.
Reliability is always about the ability to reproduce the results of the research when the design is repeated in similar conditions. Validity can tell us how well the results reflect the measurements for the planned objects.
You can assess reliability by checking the result consistency under such conditions as the extent of time, observers who participate in the research, and settings within the process of research. Validity is assessed by checking how properly the results meet the established theories and previous measurements made for the same object.
Reliability and validity do not always relate. When the measurement is reliable, it does not mean that it is valid. The only requirement for the results is that they need to be reproducible, but they should not necessarily be correct. If we say that the measurements are valid, they are always reliable. Accurate results are usually reproducible.
The Concepts of Reliability and Validity and Their Meanings
These concepts are closely related. Though, you need to know what they exactly mean
Reliability and Its Characteristics
If you continuously get the same result with the help of the same methods under similar conditions, you can say that these results are reliable.
You can measure the air temperature in the greenhouse several times in similar conditions (the time of day or the present capacity of a heater). The temperature is the same with all the next measurements, so these results are reliable.
If a doctor uses the questionnaire to examine the patient’s chronic conditions and receives the same answer and gives the same diagnosis. However, when two other doctors use the same set of questions for the same patient and give different diagnoses, it means that this questionnaire is not reliable enough.
What Stands Behind Validity?
Validity is about the accuracy of measurements. Research with high validity can produce outcomes that exactly correspond to the actual characteristics or their variations related to social or physical phenomena.
If the measurement has high reliability, it is likely to be valid. If it is not reliable, it cannot be valid. If the thermometer shows a different temperature in the greenhouse every time you measure it under similar controlled conditions, it means that it is broken, and such measurements cannot be considered valid. If the patient’s diagnosis is the same due to the symptom questionnaire employed by different therapists at different times, it means that this questionnaire is entirely valid as a means for detecting a specific medical condition.
Reliability, though, cannot be the sole indicator of validity. Even if the results are reliable, they may not reflect real-life situations. As in the example with a thermometer in the greenhouse, every measurement taken shows the same results, but the temperature is 3 degrees higher than it shows because the tool has not been properly calibrated. Thus, this measurement is not valid, though it is reliable.
Suppose a group of participants is given a test to measure their speed of reactions to certain visual aids. The results are reliable because all of them reacted to the visuals appropriately. However, it is not valid because the speed of reaction depended a lot on the visual acuity - people with poorer sight reacted more slowly than those whose sight was good. The outcomes have actually shown that you were measuring the participants’ eyesight but not their speed of reaction to visuals.
All these factors add more difficulty to assessing validity. To get valid results, you need to pick the proper and entirely valid methods, and the purpose of the research must be clear - you need to measure exactly what you want to measure. As a result, the discussion of the obtained results and the follow-up conclusions are also fully valid.
How to Assess Reliability and Validity
One more question is how you can assess reliability and validity. To estimate reliability, you need to compare the different variants of several measurements in a row. As for validity, you need to compare the obtained results to other existing theories or measurements of the same phenomenon. You can use various methods to assess reliability and validity.
Reliability Types
| Test-retest. You should get the same results when you repeat the test. For example, if you ask a group of participants to complete a questionnaire about their food preferences and then repeat the task in a week or month and receive the same answers, the test-retest reliability is pretty high. |
| Interrater. You should get the same results when different people or objects produce the same measurements. For example, if the five different doctors give different diagnoses based on the same criteria for one patient within the time of two weeks, it means that the list of these criteria has low inter-rated reliability or the criteria assessments are too subjective. |
| Internal consistency. All the measurements should be consistent in themselves. You cannot get the same results from different steps of the test developed to measure the same object. For example, you have designed a questionnaire to measure work-life balance satisfaction. Even if you randomly divide the results into parts, they will have clear correlations between these parts. However, if some of the results are pretty different, the internal consistency of the questionnaire is low. |
Validity Types
Validity is estimated on the basis of three main types of evidence. You can utilize well-known statistical methods or expert opinions to evaluate each of these types.
| Construct. It assesses the correspondence of the measurement to the theory or widely spread knowledge of the subject that has already been measured. For example, the work-life satisfaction questionnaire can lead to the assessment based on other characteristics that are believed to be related to this question (for example, optimistic life views or high self-esteem). If the correlation between the scores of work-life balance and other features associated with it is strong, you get high construct validity. |
| Content. The measurement should cover all the aspects of the concept under research or a bigger part of them. When you research work-life balance satisfaction, your test can measure the times for work, taking food, sleep, and rest. However, experts believe that communication plays an important role in the work-life balance of most people, and this aspect is not involved here. That is why we can say that the test is not complete and lacks content validity for measuring the entire work-life balance satisfaction. |
| Criterion. The results of one measurement should correspond to the results of other measurements for the same concept. If you conduct a survey about the social problems in the region, and the mayor’s election results prove the victory of the candidate who promised to deal with those problems, you can say that your survey had high criterion validity. |
If you want to assess the validity of a cause-and-effect correlation between the two subjects (or variables), you should consider the experiment design as an internal validity and the generalizability of the results as its external validity.
Ensuring Reliability and Validity of Scientific Research
A straightforward and accurate research design is the main factor that can ensure the reliability and validity of any research. You should pick the proper methods and techniques, choose samples correctly, and follow consistent approaches in your study.
How to Ensure Validity
Try to utilize scores or ratings that can reflect the variations as strictly and accurately as possible. Think about research validity at the first stages of your study, no matter whether it concerns physical or mental aspects and characteristics. You should decide how you are going to collect data and later analyze them. You can take these steps to ensure validity:
| 1. Choosing an appropriate measurement method and techniques. They have to be high-quality and targeted. In addition, they should be based on existing theories or something that has already been measured during previous research. For example, if you collect data about some psychological reaction to stress, utilize a standardized questionnaire that has proven its reliability and validity. If you prefer to develop the questionnaires of your own, consider the existing knowledge and the results of the previous studies. Remember that all the questions should be clear and properly worded. |
| 2. Using the correct sampling methods for research subject selection. If you want the result of your research to be valid, determine the characteristics of the population you want to research (e.g., whether the people need to be the same or different age, have the same or different social status, be from one or different geographical locations, etc.). Consider whether you have enough participants for your type of research and whether they are actually representative of the entire population. |
How to Ensure Reliability
You need to start ensuring reliability from the beginning of the research process. Pick the tools or techniques for data collection that can provide accurate and reproducible results. Use the following principles:
| 1. Consistent application of all the chosen methods. Do the same steps for every measurement, especially if there are other researchers in the process apart from you. For example, if you need to conduct multiple interviews, provide clear instructions on the interviewer’s behavior and what kind of answer to count. It will help to phrase all the questions in the same way. |
| 2. Standardized conditions for all the circumstances and stages of research. All the circumstances should always be kept consistent to eliminate the impact of external factors. If you allow such factors to intrude on the process, you may obtain variations in results that will be difficult to analyze. If you conduct an experiment, ensure that all the participants have the same instructions and equally understand them all. The testing conditions should also be kept the same for all the groups and participants. |
Where to Report Validity and Reliability in Your Thesis Paper
You need to speak about the reliability and validity of your research in the paper. You can do this in different sections. You have to demonstrate that you have taken them into account while making conclusions. It will make your work more trustworthy. Therefore, you can discuss these aspects in:
- Literature review. Explain the achievements of other researchers in devising and improving validity and reliability.
- Methodology. Explain your plan of research meant to increase the validity and reliability of all measurements. It can be the choice of a sample and its size, preparations, external factors, and used techniques.
- Results. You can calculate validity and reliability in many cases. Indicate these values together with the main results.
- Discussion. Speak about how reliable and valid your research is and provide proof of this. If you see that the results do not reflect real-life values, explain why.
- Conclusion. You can mention the research reliability and validity here, especially if you had some problems with the findings.
Final Thoughts
As you see, reliability and validity are essential aspects of your research and its results. So, you need to know how to use these concepts properly, how to increase their importance, and how to explain why your measurements are reliable and valid. The consistent and straightforward conclusions will add overall value to your entire research work, so you will be highly appreciated.