It is important to ensure that validity and reliability do not get confused. Reliability is the consistency of results when the experiment is replicated under the same conditions, which is very different to validity.
These two evaluations of research studies are independent factors, therefore a study can be reliable without being valid, and vice versa, as demonstrated here this resource also provides more information on types of validity and threats. However, a good study will be both reliable and valid.
So to conclude, validity is very important in a research study to ensure that our results can be used effectively, and variables that may threaten validity should be controlled as much as possible.
Validity is possibly the most important aspect of research and if anything is to be achieved it should be relibiltiy and validity or findings are in sense worthless.
This is when subject may choose not to remain in there group and as a result differences between a control group and a treatment group may be a result of who remained in each group opposed to the variables. Subject attrition shows that validity isnt just a concern when arranging a research design but as the experiment progress there are still threats to internal validity that can be overcome during data analysis.
Attrition is manly an issue in longitudinal research reference below in which validity is incredibly difficult to control. The overall message of this comment is that validity issues are an ongoing process with a single research process and can be effected at any point and needs many measures to control. I agree with the above comment!
There are many threats to both reliability and validity. If you add in more information on when each of these situations could be used it would bulk and add to the argument. There needs to be more examples to back up your points also and they seem very bare.
As well, try to add a bit more information on reliability into the argument. The information on the two will help make a very valid point through out your blog instead of just trying to justify validity. Very informative blog, however how can we prevent these threats to validity? A single blind being the participant being unaware of which condition or group they are in and a double blind being when neither participant or researcher being aware of this fact.
Both lessen the expectancy effects of the experimental setting or group. Even things as simple as experimenter bias can become major issues. Really detailed informative blog, well done!
You could have maybe included how you would try and stop their being threats to the validity, for example a double experimenter and participant or single just participant blind experiment, where they do not know what condition they are in in the experiment.
Homework for my TA simon: Permission from the authors were already requested and granted. Thanks hope somebody could help me. Thus splendid to find such a piece of writing which is worthy for the progressing of the education of the young age, keep up hey. What is validity and why is it important in research? Reliability, if a person take a test multiple times the results should be same? You are commenting using your WordPress.
You are commenting using your Twitter account. You are commenting using your Facebook account. Notify me of new comments via email. Notify me of new posts via email. The 4 main types of validity There are 4 main types of validity used when assessing internal validity.
So why is validity important? Hi there, I enjoy reading through yohr post. I like to write a little comment too support you. The third scenario shows a case where your hits are spread across the target and you are consistently missing the center. Your measure in this case is neither reliable nor valid. Finally, we see the "Robin Hood" scenario -- you consistently hit the center of the target.
Your measure is both reliable and valid I bet you never thought of Robin Hood in those terms before. Another way we can think about the relationship between reliability and validity is shown in the figure below.
Here, we set up a 2x2 table. The columns of the table indicate whether you are trying to measure the same or different concepts. The rows show whether you are using the same or different methods of measurement.
Imagine that we have two concepts we would like to measure, student verbal and math ability. Furthermore, imagine that we can measure each of these in two ways. Second, we can ask the student's classroom teacher to give us a rating of the student's ability based on their own classroom observation. The first cell on the upper left shows the comparison of the verbal written test score with the verbal written test score.
But how can we compare the same measure with itself? We could do this by estimating the reliability of the written test through a test-retest correlation, parallel forms, or an internal consistency measure See Types of Reliability. What we are estimating in this cell is the reliability of the measure. The cell on the lower left shows a comparison of the verbal written measure with the verbal teacher observation rating.
Because we are trying to measure the same concept, we are looking at convergent validity See Measurement Validity Types. The cell on the upper right shows the comparison of the verbal written exam with the math written exam.
Here, we are comparing two different concepts verbal versus math and so we would expect the relationship to be lower tha n a comparison of the same concept with itself e. Thus, we are trying to discriminate between two concepts and we would consider this discriminant validity. Finally, we have the cell on the lower right. Here, we are comparing the verbal written exam with the math teacher observation rating.
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.
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 use of reliability and validity are common in quantitative research and now it is reconsidered in the qualitative research paradigm. Since reliability and validity are rooted in positivist perspective then they should be redefined for their use in a naturalistic approach. Like reliability and validity as used in quantitative research are providing . Reliability and Validity. In order for research data to be of value and of use, they must be both reliable and valid.. Reliability.
Test-retest reliability is a measure of reliability obtained by administering the same test twice over a period of time to a group of individuals. The scores from Time 1 and Time 2 can then be correlated in order to evaluate the test for stability over time. When we look at reliability and validity in this way, we see that, rather than being distinct, they actually form a continuum. On one end is the situation where the concepts and methods of measurement are the same (reliability) and on the other is the situation where concepts and methods of measurement are different (very discriminant validity).