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 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. 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 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. 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.
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.
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. It is important to ensure that validity and reliability do not get confused.
The principles of validity and reliability are fundamental cornerstones of the scientific method. Together, they are at the core of what is accepted as scientific proof, by scientist and philosopher alike.
By following a few basic principles, any experimental design will stand up to rigorous questioning and skepticism. The idea behind reliability is that any significant results must be more than a one-off finding and be inherently repeatable. Other researchers must be able to perform exactly the same experiment , under the same conditions and generate the same results. This will reinforce the findings and ensure that the wider scientific community will accept the hypothesis.
Without this replication of statistically significant results , the experiment and research have not fulfilled all of the requirements of testability. This prerequisite is essential to a hypothesis establishing itself as an accepted scientific truth.
For example, if you are performing a time critical experiment, you will be using some type of stopwatch. Generally, it is reasonable to assume that the instruments are reliable and will keep true and accurate time.
However, diligent scientists take measurements many times, to minimize the chances of malfunction and maintain validity and reliability. At the other extreme, any experiment that uses human judgment is always going to come under question. Human judgment can vary wildly between observers , and the same individual may rate things differently depending upon time of day and current mood. This means that such experiments are more difficult to repeat and are inherently less reliable.
Reliability is a necessary ingredient for determining the overall validity of a scientific experiment and enhancing the strength of the results.
Debate between social and pure scientists, concerning reliability, is robust and ongoing. Validity encompasses the entire experimental concept and establishes whether the results obtained meet all of the requirements of the scientific research method. Construct validity entails demonstrating the power of such a construct to explain a network of research findings and to predict further relationships. The more evidence a researcher can demonstrate for a test's construct validity the better.
However, there is no single method of determining the construct validity of a test. Instead, different methods and approaches are combined to present the overall construct validity of a test.
For example, factor analysis and correlational methods can be used. This is the degree to which a test corresponds to an external criterion that is known concurrently i. If the new test is validated by a comparison with a currently existing criterion, we have concurrent validity. Very often, a new IQ or personality test might be compared with an older but similar test known to have good validity already. This is the degree to which a test accurately predicts a criterion that will occur in the future.
For example, a prediction may be made on the basis of a new intelligence test, that high scorers at age 12 will be more likely to obtain university degrees several years later. If the prediction is born out then the test has predictive validity. Psychological Bulletin , 52, Manual for the Minnesota Multiphasic Personality Inventory. Journal of Educational Measurement , 22 4 , Saul McLeod , published The concept of validity was formulated by Kelly , p.
Internal and External Validity A distinction can be made between internal and external validity. Assessing the validity of test There there are two main categories of validity used to assess the validity of test i. Face Validity This is the least sophisticated measure of validity.
Reliability and Validity. In order for research data to be of value and of use, they must be both reliable and valid.. Reliability.
Internal consistency reliability is a measure of reliability used to evaluate the degree to which different test items that probe the same construct produce similar results. Average inter-item correlation is a subtype of internal consistency reliability.
In research, internal validity is the extent to which you are able to say that no other variables except the one you're studying caused the result. For example, if we are studying the variable of. External Validity. Sarah is a psychologist who teaches and does research at an expensive, private college. She's interested in studying whether offering specific praise after a task will boost.
In its purest sense, this refers to how well a scientific test or piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent. Validity encompasses the entire experimental concept and establishes whether the results obtained meet all of the requirements of the scientific research method. For example, there must have been randomization of the sample groups and appropriate care and diligence shown in .