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.
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.
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.
For example, there must have been randomization of the sample groups and appropriate care and diligence shown in the allocation of controls. 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.
Internal validity and reliability are at the core of any experimental design. External validity is the process of examining the results and questioning whether there are any other possible causal relationships.
Control groups and randomization will lessen external validity problems but no method can be completely successful. This is why the statistical proofs of a hypothesis called significant , not absolute truth. Any scientific research design only puts forward a possible cause for the studied effect. There is always the chance that another unknown factor contributed to the results and findings.
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 study.
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.
In general, VALIDITY is an indication of how sound your research is. More specifically, validity applies to both the design and the methods of your research. Validity in data collection means that your findings truly represent the phenomenon you are claiming to measure. Start studying Research Methods - Validity. Learn vocabulary, terms, and more with flashcards, games, and other study tools.
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 . Reliability and Validity. In order for research data to be of value and of use The answer depends on the amount of research support for such a relationship. Different methods vary with regard to these two aspects of validity. Experiments, because they tend to be structured and controlled, are often high on internal validity.