Validity is described as the degree to which a research study measures what it intends to measure. There are two main types of validity, internal and external. Internal validity refers to the validity of the measurement and test itself, whereas external validity refers to the ability to generalise the findings to the target population. Both are very important in analysing the appropriateness, meaningfulness and usefulness of a research study. However, here I will focus on the validity of the measurement technique (i.e. internal validity).
The 4 main types of validity
There are 4 main types of validity used when assessing internal validity. Each type views validity from a different perspective and evaluates different relationships between measurements.
Face validity-This refers to whether a technique looks as if it should measure the variable it intends to measure. For example, a method where a participant is required to click a button as soon as a stimulus appears and this time is measured appears to have face validity for measuring reaction time. An example of analysing research for face validity by Hardesty and Bearden (2004) can be found here.
Concurrent validity-This compares the results from a new measurement technique to those of a more established technique that claims to measure the same variable to see if they are related. Often two measurements will behave in the same way, but are not necessarily measuring the same variable, therefore this kind of validity must be examined thoroughly. An example and some weakness associated with this type of validity can be found here (Shuttleworth, 2009).
Predictive validity-This is when the results obtained from measuring a construct can be accurately used to predict behaviour. There are obvious limitations to this as behaviour cannot be fully predicted to great depths, but this validity helps predict basic trends to a certain degree. A meta-analysis by van IJzendoorn (1995) examines the predictive validity of the Adult Attachment Interview.
Construct validity-This is whether the measurements of a variable in a study behave in exactly the same way as the variable itself. This involves examining past research regarding different aspects of the same variable. The use of construct validity in psychology is examined by Cronbach and Meehl (1955) here.
*Definitions taken from Research Methods for the Behavioural Sciences by Gravetter and Forzano (2009)*
A research study will often have one or more types of these validities but maybe not them all so caution should be taken. For example, using measurements of weight to measure the variable height has concurrent validity as weight generally increases as height increases, however it lacks construct validity as weight fluctuates based on food deprivation whereas height does not.
What are the threats to Internal Validity?
Factors that can effect internal validity can come in many forms, and it is important that these are controlled for as much as possible during research to reduce their impact on validity. The term history refers to effects that are not related to the treatment that may result in a change of performance over time. This could refer to events in the participant’s life that have led to a change in their mood etc. Instrumental bias refers to a change in the measuring instrument over time which may change the results. This is often evident in behavioural observations where the practice and experience of the experimenter influences their ability to notice certain things and changes their standards. A main threat to internal validity is testing effects. Often participants can become tired or bored during an experiment, and previous tests may influence their performance. This is often counterbalanced in experimental studies so that participants receive the tasks in a different order to reduce their impact on validity.
So why is validity important?
If the results of a study are not deemed to be valid then they are meaningless to our study. If it does not measure what we want it to measure then the results cannot be used to answer the research question, which is the main aim of the study. These results cannot then be used to generalise any findings and become a waste of time and effort. It is important to remember that just because a study is valid in one instance it does not mean that it is valid for measuring something else.
Validity’s relationship to Reliability
It is important to ensure that validity and reliability do not get confused. Reliability is the consistency of results when the experiment is replicated under the same conditions, which is very different to validity. These two evaluations of research studies are independent factors, therefore a study can be reliable without being valid, and vice versa, as demonstrated here (this resource also provides more information on types of validity and threats). However, a good study will be both reliable and valid.
So to conclude, validity is very important in a research study to ensure that our results can be used effectively, and variables that may threaten validity should be controlled as much as possible.