When conducting quantitative research, you will want to know how valid your methods and research outcomes are. Most college students have a hard time differentiating the different types of validity. That is why in this article, we have set out to explain what validity is and the different forms of validity to help college students avoid confusion.
Validity - FAQ
These are two broad types of validity, and they are based on a cause-and-effect relationship. Internal validity is how trustworthy the results of an experiment are and if they can withstand influence from other factors. External validity is the extent of applicability of results to different settings and situations.
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There are four main types, and they are construct, content, face, and criterion. The difference between the four types depends on the perspective of view and the relationships between the measurements under consideration.
Many people confuse the two and sometimes use them interchangeably. However, they are quite different from each other. Reliability is the consistency of results or measurements obtained after conducting the same experiment multiple times under similar conditions. On the other hand, validity is when results or measurements obtained from an experiment fall in the middle of the construct of interest. If a test is valid, it is definitely reliable, but if a test is reliable, it does not necessarily mean it is valid.
It is a condition used to determine if the results obtained after an experiment or research closely relate to real-world values. It helps researchers know if they obtained results or measurements that can be used to answer research questions. It helps eliminate the factor of untrustworthiness on work done and results obtained.
These threats include history, attrition, social interaction, participant selection, maturation, regression towards the mean, size of the population under test, instrument/task sensitivity, testing, and instrumentation.
It can be defined as the accuracy of the results or measurements gathered using a particular method during quantitative research. It is the extent to which we can trust our conclusions will be correct based on the data that will be collected and the instrument used to collect them. It is a condition that researchers use to measure the quantity of real phenomenon captured during an experiment versus the amount of unrelated information in research results.
Types of Validity
|What it measures||Type|
|If the concept under study adheres to the theory and knowledge that is already in existence.||Construct|
|If the measurements cover all the aspects of the concept under study.||Content|
|The accuracy that a method measures what it purports to measure based on face value.||Face|
|The extent of correspondence of a measure to other valid measures of the same criteria.||Criterion|
This is concerned with how adequately an instrument measures the concept under study as theorised. A construct is a concept that expresses ideas, events, people, and/or objects and can be directly observed. Also, if there are indicators related to the concept, they can be monitored and analysed to obtain research results. Examples of constructs in quantitative research are age, height, gender, financial performance, sun, trees, ageism, poverty, disability e.t.c.
Construct validity, therefore, seeks to find out if a tool measures the concept as theoretically stated. For example, when a researcher sets out to diagnose depression among people, he/she needs to construct a questionnaire that helps measure indicators and symptoms of depression. This is because depression is not an observable entity hence cannot be measured. Therefore, the researcher needs to ensure the questions in the questionnaire can capture the indicators of depression and mood of participants.
It is concerned with how adequately an instrument or method measures the concept under research. In this category, for the results of a test to be valid, the test must include all the necessary aspects of the concept being measured. The test results will be regarded invalid if an essential aspect of the concept being measured is left out. For example, if a teacher wants to determine the language ability of his students, he should test all the necessary aspects of the concept being measured.
These are writing, learning, reading, and speaking aspects. Experts agree that all these components are essential when determining the language ability of students. However, if the teacher leaves out a particular component such as listening comprehension, the test outcomes would be invalid because it does not measure all the aspects of the concept.
It is subjective because it measures the extent to which a test covers a concept it claims to measure from a layperson’s view. It is very weak; hence it is not reliable and cannot be used on its own unless other measures support it. A good example is when a researcher sets out to determine the IQ of people using pictures with missing items like a missing mouse in a desktop setup and missing cassette tape in a cassette. The test may appear to be valid at face value, but it is biased against the poor who cannot afford or have never seen a desktop before. The test is also biased against the latest generation of kids who came after cassettes became obsolete and outdated.
It identifies if research outcomes relate to other measurements of the same concept. Criterion is a measurement or standard that is used as a basis when judging something. Criterion validity measures the correspondence of research outcomes to other results obtained from tests performed on a similar concept. An example is when a market research firm conducts a survey to determine which product customers would prefer between two products about to be launched by a company. The company then launches the products to the market simultaneously, and the product that customers preferred gets sold out after launch. The survey can then be regarded to be valid.
How to Ensure Validity in Your Research
As a researcher, you can achieve this by selecting a research method that can answer your questions as accurately as possible, setting straightforward questions that mean the same thing regardless of the person reading it, eliminate any biasedness, for example, by avoiding leading participants, and using sample size and sample type that is appropriate for the research.
In a Nutshell
- From the above, we can conclude that validity is an essential factor in quantitative research. It helps researchers know the accuracy of the methods they are about to use or are using in measuring something.
- Among the four types of validity discussed above, the weakest is face validity because it is subjective and informal.