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Research Methodology

What is Reliability?

❶In research, a hypothesis is a suggested explanation of a phenomenon.

Confounding Variables

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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. 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. Ideally, one tries to reduce the plausibility of the most likely threats to validity, thereby leaving as most plausible the conclusion reached in the study.

For instance, imagine a study examining whether there is a relationship between the amount of training in a specific technology and subsequent rates of use of that technology. Because the interest is in a relationship, it is considered an issue of conclusion validity. Assume that the study is completed and no significant correlation between amount of training and adoption rates is found. On this basis it is concluded that there is no relationship between the two.

How could this conclusion be wrong -- that is, what are the "threats to validity"? For one, it's possible that there isn't sufficient statistical power to detect a relationship even if it exists. Perhaps the sample size is too small or the measure of amount of training is unreliable.

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. 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.


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Research validity in surveys relates to the extent at which the survey measures right elements that need to be measured. In simple terms, validity refers to how well an instrument as measures what it .

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Issues of research reliability and validity need to be addressed in methodology chapter in a concise manner. Reliability refers to the extent to which the same answers can be obtained using the same instruments more than one time.

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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. More specifically, validity applies to both the design and the methods of your research. 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 .

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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. Research Methods in Psychology. Chapter 5: Psychological Measurement. Reliability and Validity of Measurement Learning Objectives. Define reliability, including the different types and how they are assessed. Define validity, including the different types and how they are assessed.