And, whenever we measure or observe we are concerned with whether we are measuring what we intend to measure or with how our observations are influenced by the circumstances in which they are made. We reach conclusions about the quality of our measures -- conclusions that will play an important role in addressing the broader substantive issues of our study.
When we talk about the validity of research, we are often referring to these to the many conclusions we reach about the quality of different parts of our research methodology.
We subdivide validity into four types. Each type addresses a specific methodological question. In order to understand the types of validity, you have to know something about how we investigate a research question. Because all four validity types are really only operative when studying causal questions, we will use a causal study to set the context. The figure shows that there are really two realms that are involved in research. The first, on the top, is the land of theory.
It is what goes on inside our heads as researchers. It is where we keep our theories about how the world operates. The second, on the bottom, is the land of observations. It is the real world into which we translate our ideas -- our programs, treatments, measures and observations. When we conduct research, we are continually flitting back and forth between these two realms, between what we think about the world and what is going on in it.
When we are investigating a cause-effect relationship, we have a theory implicit or otherwise of what the cause is the cause construct. For instance, if we are testing a new educational program, we have an idea of what it would look like ideally. Similarly, on the effect side, we have an idea of what we are ideally trying to affect and measure the effect construct.
But each of these, the cause and the effect, has to be translated into real things, into a program or treatment and a measure or observational method. We use the term operationalization to describe the act of translating a construct into its manifestation. In effect, we take our idea and describe it as a series of operations or procedures. Now, instead of it only being an idea in our minds, it becomes a public entity that anyone can look at and examine for themselves.
It is one thing, for instance, for you to say that you would like to measure self-esteem a construct. But when you show a ten-item paper-and-pencil self-esteem measure that you developed for that purpose, others can look at it and understand more clearly what you intend by the term self-esteem. Now, back to explaining the four validity types. They build on one another, with two of them conclusion and internal referring to the land of observation on the bottom of the figure, one of them construct emphasizing the linkages between the bottom and the top, and the last external being primarily concerned about the range of our theory on the top.
Assume that we took these two constructs, the cause construct the WWW site and the effect understanding , and operationalized them -- turned them into realities by constructing the WWW site and a measure of knowledge of the course material.
Here are the four validity types and the question each addresses:. In this study, is there a relationship between the two variables? In the context of the example we're considering, the question might be worded: There are several conclusions or inferences we might draw to answer such a question.
We could, for example, conclude that there is a relationship. We might conclude that there is a positive relationship.
We might infer that there is no relationship. We can assess the conclusion validity of each of these conclusions or inferences. Assuming that there is a relationship in this study, is the relationship a causal one? Just because we find that use of the WWW site and knowledge are correlated, we can't necessarily assume that WWW site use causes the knowledge.
Both could, for example, be caused by the same factor. If more than one person is observing behavior or some event, all observers should agree on what is being recorded in order to claim that the data are reliable. Reliability also applies to individual measures. When people take a vocabulary test two times, their scores on the two occasions should be very similar.
If so, the test can then be described as reliable. To be reliable, an inventory measuring self-esteem should give the same result if given twice to the same person within a short period of time. IQ tests should not give different results over time as intelligence is assumed to be a stable characteristic.
Validity refers to the credibility or believability of the research. Are the findings genuine? Is hand strength a valid measure of intelligence? Almost certainly the answer is "No, it is not. The answer depends on the amount of research support for such a relationship. Internal validity - the instruments or procedures used in the research measured what they were supposed to measure.
As part of a stress experiment, people are shown photos of war atrocities. After the study, they are asked how the pictures made them feel, and they respond that the pictures were very upsetting. In this study, the photos have good internal validity as stress producers. External validity - the results can be generalized beyond the immediate study. In order to have external validity, the claim that spaced study studying in several sessions ahead of time is better than cramming for exams should apply to more than one subject e.
It should also apply to people beyond the sample in the study.
Internal validity dictates how an experimental design is structured and encompasses all of the steps of the scientific research method. Even if your results are great, sloppy and inconsistent design will compromise your integrity in the eyes of the scientific community.
Sampling Validity (similar to content validity) ensures that the area of coverage of the measure within the research area is vast. No measure is able to cover all items and elements within the phenomenon, therefore, important items and elements are selected using a specific pattern of sampling method depending on aims and objectives of the .
INTERNAL VALIDITY is affected by flaws within the study itself such as not controlling some of the major variables (a design problem), or problems with the research instrument (a data collection problem). Here we consider three basic kinds: face validity, content validity, and criterion validity. Face Validity Face validity is the extent to which a measurement method appears “on its face” to measure the construct of interest.
Validity: the best available approximation to the truth of a given proposition, inference, or conclusion. The first thing we have to ask is: "validity of what?"When we think about validity in research, most of us think about research components. Validity of research can be explained as an extent at which requirements of scientific research method have been followed during the process of generating research findings. Oliver () considers validity to be a compulsory requirement for .