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Introduction to Validity

Translation Validity

❶This extraneous causal relationship may become more apparent, as techniques are refined and honed.

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Construct validity
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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. For instance, it may be that wealthier students who have greater resources would be more likely to use have access to a WWW site and would excel on objective tests. When we want to make a claim that our program or treatment caused the outcomes in our study, we can consider the internal validity of our causal claim.

Assuming that there is a causal relationship in this study , can we claim that the program reflected well our construct of the program and that our measure reflected well our idea of the construct of the measure? In simpler terms, did we implement the program we intended to implement and did we measure the outcome we wanted to measure?

In yet other terms, did we operationalize well the ideas of the cause and the effect? When our research is over, we would like to be able to conclude that we did a credible job of operationalizing our constructs -- we can assess the construct validity of this conclusion.

Assuming that there is a causal relationship in this study between the constructs of the cause and the effect , can we generalize this effect to other persons, places or times?

We are likely to make some claims that our research findings have implications for other groups and individuals in other settings and at other times. When we do, we can examine the external validity of these claims. Notice how the question that each validity type addresses presupposes an affirmative answer to the previous one.

This is what we mean when we say that the validity types build on one another. The figure shows the idea of cumulativeness as a staircase, along with the key question for each validity type. For any inference or conclusion, there are always possible threats to validity -- reasons the conclusion or inference might be wrong.

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. 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. However, their strength with regard to structure and control, may result in low external validity. The results may be so limited as to prevent generalizing to other situations. 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.


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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.

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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.

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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.

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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.