Construct validity assesses how well a test reflects the phenomenon it’s supposed to measure. Construct validity cannot be directly measured; instead, you must gather evidence in favor of it.
This evidence comes in the form of other types of validity, including face validity, content validity, criterion validity, convergent validity, and divergent validity. The stronger the evidence across these measures, the more confident you can be that you are measuring what you intended to.
Continue reading: How do you measure construct validity?
Concurrent validity and predictive validity are both types of criterion validity. Both assess how well one test corresponds to another, theoretically related, test or outcome. However, the key difference is when each test is conducted:
- Concurrent validity compares one measure to a second, well-established measure that acts as a gold-standard. Both measures should be obtained at the same time, or concurrently.
- Predictive validity instead captures how well a measure corresponds to a measure taken later in time (i.e., how well one measure predicts a future measure).
Continue reading: What is the difference between concurrent and predictive validity?
A construct is a phenomenon that cannot be directly measured, such as intelligence, anxiety, or happiness. Researchers must instead approximate constructs using related, measurable variables.
The process of defining how a construct will be measured is called operationalization. Constructs are common in psychology and other social sciences.
To evaluate how well a construct measures what it’s supposed to, researchers determine construct validity. Face validity, content validity, criterion validity, convergent validity, and discriminant validity all provide evidence of construct validity.
Continue reading: What is a construct?
Convergent and concurrent validity both indicate how well a test score and another variable compare to one another.
However, convergent validity indicates how well one measure corresponds to other measures of the same or similar constructs. These measures do not have to be obtained at the same time.
Concurrent validity instead assesses how well a measure aligns with a benchmark or “gold-standard,” which can be a ground truth or another validated measure. Both measurements should be taken at the same time.
Continue reading: What is the difference between convergent and concurrent validity?
Criterion validity measures how well a test corresponds to another measure, or criterion. The two types of criterion validity are concurrent and predictive validity.
Continue reading: What are the two types of criterion validity?
Construct validity assesses how well a test measures the concept it was meant to measure, whereas predictive validity evaluates to what degree a test can predict a future outcome or behavior.
Continue reading: What is the difference between construct validity and predictive validity?
The interview type with the highest predictive validity differs based on the goal of the interview.
- Generally speaking, a structured interview has the highest predictive validity.
- Unstructured interviews have the lowest predictive validity, especially in recruitment or job performance settings.
- Semi-structured interviews have adequate predictive validity but not as high as structured interviews.
Situational questions, work sample requests, and interview questions about past behavior are the best question types in the case of job interviews.
When designing job interview questions, make sure to minimize bias and to also account for other types of validity, such as construct validity and content validity.
You can use QuillBot’s Grammar Checker to make sure your interview questions are error-free.
Continue reading: Which type of interview has been shown to have the highest predictive validity?
To ensure high external validity, it’s important to draw a sample that’s representative of the population you want to generalize to. It’s always best to choose a probability sampling (also known as random sampling) method for this.
The most popular sampling methods are stratified sampling, systematic sampling, simple random sampling, and cluster sampling.
A probability sampling method also increases other types of validity, such as internal validity, and it reduces bias.
Continue reading: What kind of sample is best for external validity?
Random assignment can increase external validity, but it has a bigger impact on internal validity.
Random assignment helps to reduce confounding variables and ensures that the treatment and control groups are comparable in all aspects except for the independent variable.
This increases the confidence that any observed differences between the groups can be attributed to the treatment rather than other factors, which means an increase in internal validity.
It can also improve external validity because random assignment of participants prevents researchers from inadvertently selecting participants who may be more or less likely to respond to the treatment.
However, the external validity may still be limited by sampling bias if the participants are not representative of the target population, which is why choosing the appropriate sampling method is also important to ensure external validity.
A probability sampling method, such as simple random sampling, stratified sampling, cluster sampling, or systematic sampling, is always the best choice.
Continue reading: Does random assignment increase external validity?
Content validity and criterion validity are two types of validity in research:
- Content validity ensures that an instrument measures all elements of the construct it intends to measure.
- A survey to investigate depression has high content validity if its questions cover all relevant aspects of the construct “depression.”
- Criterion validity ensures that an instrument corresponds with other “gold standard” measures of the same construct.
- A shortened version of an established anxiety assessment instrument has high criterion validity if the outcomes of the new version are similar to those of the original version.
Continue reading: What is the difference between content and criterion validity?
