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What is the difference between slection crieteria and validity and reliability?
Wiki User
∙ 14y ago
Social and Medical sciences uses these statistical concepts.
ideally, we have to measure the same way each time, but intrasubject, interobserver and intraobserver variance occur, so we have to anticipate and evaluate them. In short, it is the repeatability of a measurement, by you, myself and everybody person or instrument.
Validity is how much the mean measure that we got is near of the true answer or value.
So, an instrument can be reliable but not valid, valid but not reliable, both valid and reliable, nor valid neither reliable.
I suggest that you imagine a target:
you can aim and
1) always get the center (both valid and reliable)
2) always get the same distant point (reliable but not valid)
3) err much around the true center (valid but not reliable - the mean and median of your arrow's shot will get the center)
4) err much around the another center, false one (nor valid neither reliable)
I did not understood exactly what selection criteria have to do with the rest of question, so, left in blank ;-)
Wiki User
∙ 14y ago
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When IQ tests were first developed in the early 1900s they had a tendency to measure cultural traits more than intellectual capability?
They lacked validity, which made their reliability insignificant.
What is the relationship between reliability and validity?
For every dimension of interest and specific question or set of questions, there are a vast number of ways to make questions. Although the guiding principle should be the specific purposes of the research, there are better and worse questions for any particular operationalization. How to evaluate the measures? Two of the primary criteria of evaluation in any measurement or observation are: # Whether we are measuring what we intend to measure. # Whether the same measurement process yields the same results. These two concepts are validity and reliability. Reliability is concerned with questions of stability and consistency - does the same measurement tool yield stable and consistent results when repeated over time. Think about measurement processes in other contexts - in construction or woodworking, a tape measure is a highly reliable measuring instrument. Say you have a piece of wood that is 2 1/2 feet long. You measure it once with the tape measure - you get a measurement of 2 1/2 feet. Measure it again and you get 2 1/2 feet. Measure it repeatedly and you consistently get a measurement of 2 1/2 feet. The tape measure yields reliable results. Validity refers to the extent we are measuring what we hope to measure (and what we think we are measuring). To continue with the example of measuring the piece of wood, a tape measure that has been created with accurate spacing for inches, feet, etc. should yield valid results as well. Measuring this piece of wood with a "good" tape measure should produce a correct measurement of the wood's length. To apply these concepts to social research, we want to use measurement tools that are both reliable and valid. We want questions that yield consistent responses when asked multiple times - this is reliability. Similarly, we want questions that get accurate responses from respondents - this is validity. Reliability refers to a condition where a measurement process yields consistent scores (given an unchanged measured phenomenon) over repeat measurements. Perhaps the most straightforward way to assess reliability is to ensure that they meet the following three criteria of reliability. Measures that are high in reliability should exhibit all three. == When a researcher administers the same measurement tool multiple times - asks the same question, follows the same research procedures, etc. - does he/she obtain consistent results, assuming that there has been no change in whatever he/she is measuring? This is really the simplest method for assessing reliability - when a researcher asks the same person the same question twice ("What's your name?"), does he/she get back the same results both times. If so, the measure has test-retest reliability. Measurement of the piece of wood talked about earlier has high test-retest reliability. == This is a dimension that applies to cases where multiple items are used to measure a single concept. In such cases, answers to a set of questions designed to measure some single concept (e.g., altruism) should be associated with each other. == Interobserver reliability concerns the extent to which different interviewers or observers using the same measure get equivalent results. If different observers or interviewers use the same instrument to score the same thing, their scores should match. For example, the interobserver reliability of an observational assessment of parent-child interaction is often evaluated by showing two observers a videotape of a parent and child at play. These observers are asked to use an assessment tool to score the interactions between parent and child on the tape. If the instrument has high interobserver reliability, the scores of the two observers should match. To reiterate, validity refers to the extent we are measuring what we hope to measure (and what we think we are measuring). How to assess the validity of a set of measurements? A valid measure should satisfy four criteria. == This criterion is an assessment of whether a measure appears, on the face of it, to measure the concept it is intended to measure. This is a very minimum assessment - if a measure cannot satisfy this criterion, then the other criteria are inconsequential. We can think about observational measures of behavior that would have face validity. For example, striking out at another person would have face validity for an indicator of aggression. Similarly, offering assistance to a stranger would meet the criterion of face validity for helping. However, asking people about their favorite movie to measure racial prejudice has little face validity. == Content validity concerns the extent to which a measure adequately represents all facets of a concept. Consider a series of questions that serve as indicators of depression (don't feel like eating, lost interest in things usually enjoyed, etc.). If there were other kinds of common behaviors that mark a person as depressed that were not included in the index, then the index would have low content validity since it did not adequately represent all facets of the concept. == Criterion-related validity applies to instruments than have been developed for usefulness as indicator of specific trait or behavior, either now or in the future. For example, think about the driving test as a social measurement that has pretty good predictive validity. That is to say, an individual's performance on a driving test correlates well with his/her driving ability. == But for a many things we want to measure, there is not necessarily a pertinent criterion available. In this case, turn to construct validity, which concerns the extent to which a measure is related to other measures as specified by theory or previous research. Does a measure stack up with other variables the way we expect it to? A good example of this form of validity comes from early self-esteem studies - self-esteem refers to a person's sense of self-worth or self-respect. Clinical observations in psychology had shown that people who had low self-esteem often had depression. Therefore, to establish the construct validity of the self-esteem measure, the researchers showed that those with higher scores on the self-esteem measure had lower depression scores, while those with low self-esteem had higher rates of depression. So what is the relationship between validity and reliability? The two do not necessarily go hand-in-hand. At best, we have a measure that has both high validity and high reliability. It yields consistent results in repeated application and it accurately reflects what we hope to represent. It is possible to have a measure that has high reliability but low validity - one that is consistent in getting bad information or consistent in missing the mark. *It is also possible to have one that has low reliability and low validity - inconsistent and not on target. Finally, it is not possible to have a measure that has low reliability and high validity - you can't really get at what you want or what you're interested in if your measure fluctuates wildly. For every dimension of interest and specific question or set of questions, there are a vast number of ways to make questions. Although the guiding principle should be the specific purposes of the research, there are better and worse questions for any particular operationalization. How to evaluate the measures? Two of the primary criteria of evaluation in any measurement or observation are: # Whether we are measuring what we intend to measure. # Whether the same measurement process yields the same results. These two concepts are validity and reliability. Reliability is concerned with questions of stability and consistency - does the same measurement tool yield stable and consistent results when repeated over time. Think about measurement processes in other contexts - in construction or woodworking, a tape measure is a highly reliable measuring instrument. Say you have a piece of wood that is 2 1/2 feet long. You measure it once with the tape measure - you get a measurement of 2 1/2 feet. Measure it again and you get 2 1/2 feet. Measure it repeatedly and you consistently get a measurement of 2 1/2 feet. The tape measure yields reliable results. Validity refers to the extent we are measuring what we hope to measure (and what we think we are measuring). To continue with the example of measuring the piece of wood, a tape measure that has been created with accurate spacing for inches, feet, etc. should yield valid results as well. Measuring this piece of wood with a "good" tape measure should produce a correct measurement of the wood's length. To apply these concepts to social research, we want to use measurement tools that are both reliable and valid. We want questions that yield consistent responses when asked multiple times - this is reliability. Similarly, we want questions that get accurate responses from respondents - this is validity. Reliability refers to a condition where a measurement process yields consistent scores (given an unchanged measured phenomenon) over repeat measurements. Perhaps the most straightforward way to assess reliability is to ensure that they meet the following three criteria of reliability. Measures that are high in reliability should exhibit all three. == When a researcher administers the same measurement tool multiple times - asks the same question, follows the same research procedures, etc. - does he/she obtain consistent results, assuming that there has been no change in whatever he/she is measuring? This is really the simplest method for assessing reliability - when a researcher asks the same person the same question twice ("What's your name?"), does he/she get back the same results both times. If so, the measure has test-retest reliability. Measurement of the piece of wood talked about earlier has high test-retest reliability. == This is a dimension that applies to cases where multiple items are used to measure a single concept. In such cases, answers to a set of questions designed to measure some single concept (e.g., altruism) should be associated with each other. == Interobserver reliability concerns the extent to which different interviewers or observers using the same measure get equivalent results. If different observers or interviewers use the same instrument to score the same thing, their scores should match. For example, the interobserver reliability of an observational assessment of parent-child interaction is often evaluated by showing two observers a videotape of a parent and child at play. These observers are asked to use an assessment tool to score the interactions between parent and child on the tape. If the instrument has high interobserver reliability, the scores of the two observers should match. To reiterate, validity refers to the extent we are measuring what we hope to measure (and what we think we are measuring). How to assess the validity of a set of measurements? A valid measure should satisfy four criteria. == This criterion is an assessment of whether a measure appears, on the face of it, to measure the concept it is intended to measure. This is a very minimum assessment - if a measure cannot satisfy this criterion, then the other criteria are inconsequential. We can think about observational measures of behavior that would have face validity. For example, striking out at another person would have face validity for an indicator of aggression. Similarly, offering assistance to a stranger would meet the criterion of face validity for helping. However, asking people about their favorite movie to measure racial prejudice has little face validity. == Content validity concerns the extent to which a measure adequately represents all facets of a concept. Consider a series of questions that serve as indicators of depression (don't feel like eating, lost interest in things usually enjoyed, etc.). If there were other kinds of common behaviors that mark a person as depressed that were not included in the index, then the index would have low content validity since it did not adequately represent all facets of the concept. == Criterion-related validity applies to instruments than have been developed for usefulness as indicator of specific trait or behavior, either now or in the future. For example, think about the driving test as a social measurement that has pretty good predictive validity. That is to say, an individual's performance on a driving test correlates well with his/her driving ability. == But for a many things we want to measure, there is not necessarily a pertinent criterion available. In this case, turn to construct validity, which concerns the extent to which a measure is related to other measures as specified by theory or previous research. Does a measure stack up with other variables the way we expect it to? A good example of this form of validity comes from early self-esteem studies - self-esteem refers to a person's sense of self-worth or self-respect. Clinical observations in psychology had shown that people who had low self-esteem often had depression. Therefore, to establish the construct validity of the self-esteem measure, the researchers showed that those with higher scores on the self-esteem measure had lower depression scores, while those with low self-esteem had higher rates of depression. So what is the relationship between validity and reliability? The two do not necessarily go hand-in-hand. At best, we have a measure that has both high validity and high reliability. It yields consistent results in repeated application and it accurately reflects what we hope to represent. It is possible to have a measure that has high reliability but low validity - one that is consistent in getting bad information or consistent in missing the mark. *It is also possible to have one that has low reliability and low validity - inconsistent and not on target. Finally, it is not possible to have a measure that has low reliability and high validity - you can't really get at what you want or what you're interested in if your measure fluctuates wildly. For every dimension of interest and specific question or set of questions, there are a vast number of ways to make questions. Although the guiding principle should be the specific purposes of the research, there are better and worse questions for any particular operationalization. How to evaluate the measures? Two of the primary criteria of evaluation in any measurement or observation are: # Whether we are measuring what we intend to measure. # Whether the same measurement process yields the same results. These two concepts are validity and reliability. Reliability is concerned with questions of stability and consistency - does the same measurement tool yield stable and consistent results when repeated over time. Think about measurement processes in other contexts - in construction or woodworking, a tape measure is a highly reliable measuring instrument. Say you have a piece of wood that is 2 1/2 feet long. You measure it once with the tape measure - you get a measurement of 2 1/2 feet. Measure it again and you get 2 1/2 feet. Measure it repeatedly and you consistently get a measurement of 2 1/2 feet. The tape measure yields reliable results. Validity refers to the extent we are measuring what we hope to measure (and what we think we are measuring). To continue with the example of measuring the piece of wood, a tape measure that has been created with accurate spacing for inches, feet, etc. should yield valid results as well. Measuring this piece of wood with a "good" tape measure should produce a correct measurement of the wood's length. To apply these concepts to social research, we want to use measurement tools that are both reliable and valid. We want questions that yield consistent responses when asked multiple times - this is reliability. Similarly, we want questions that get accurate responses from respondents - this is validity. Reliability refers to a condition where a measurement process yields consistent scores (given an unchanged measured phenomenon) over repeat measurements. Perhaps the most straightforward way to assess reliability is to ensure that they meet the following three criteria of reliability. Measures that are high in reliability should exhibit all three. == When a researcher administers the same measurement tool multiple times - asks the same question, follows the same research procedures, etc. - does he/she obtain consistent results, assuming that there has been no change in whatever he/she is measuring? This is really the simplest method for assessing reliability - when a researcher asks the same person the same question twice ("What's your name?"), does he/she get back the same results both times. If so, the measure has test-retest reliability. Measurement of the piece of wood talked about earlier has high test-retest reliability. == This is a dimension that applies to cases where multiple items are used to measure a single concept. In such cases, answers to a set of questions designed to measure some single concept (e.g., altruism) should be associated with each other. == Interobserver reliability concerns the extent to which different interviewers or observers using the same measure get equivalent results. If different observers or interviewers use the same instrument to score the same thing, their scores should match. For example, the interobserver reliability of an observational assessment of parent-child interaction is often evaluated by showing two observers a videotape of a parent and child at play. These observers are asked to use an assessment tool to score the interactions between parent and child on the tape. If the instrument has high interobserver reliability, the scores of the two observers should match. To reiterate, validity refers to the extent we are measuring what we hope to measure (and what we think we are measuring). How to assess the validity of a set of measurements? A valid measure should satisfy four criteria. == This criterion is an assessment of whether a measure appears, on the face of it, to measure the concept it is intended to measure. This is a very minimum assessment - if a measure cannot satisfy this criterion, then the other criteria are inconsequential. We can think about observational measures of behavior that would have face validity. For example, striking out at another person would have face validity for an indicator of aggression. Similarly, offering assistance to a stranger would meet the criterion of face validity for helping. However, asking people about their favorite movie to measure racial prejudice has little face validity. == Content validity concerns the extent to which a measure adequately represents all facets of a concept. Consider a series of questions that serve as indicators of depression (don't feel like eating, lost interest in things usually enjoyed, etc.). If there were other kinds of common behaviors that mark a person as depressed that were not included in the index, then the index would have low content validity since it did not adequately represent all facets of the concept. == Criterion-related validity applies to instruments than have been developed for usefulness as indicator of specific trait or behavior, either now or in the future. For example, think about the driving test as a social measurement that has pretty good predictive validity. That is to say, an individual's performance on a driving test correlates well with his/her driving ability. == But for a many things we want to measure, there is not necessarily a pertinent criterion available. In this case, turn to construct validity, which concerns the extent to which a measure is related to other measures as specified by theory or previous research. Does a measure stack up with other variables the way we expect it to? A good example of this form of validity comes from early self-esteem studies - self-esteem refers to a person's sense of self-worth or self-respect. Clinical observations in psychology had shown that people who had low self-esteem often had depression. Therefore, to establish the construct validity of the self-esteem measure, the researchers showed that those with higher scores on the self-esteem measure had lower depression scores, while those with low self-esteem had higher rates of depression. So what is the relationship between validity and reliability? The two do not necessarily go hand-in-hand. At best, we have a measure that has both high validity and high reliability. It yields consistent results in repeated application and it accurately reflects what we hope to represent. It is possible to have a measure that has high reliability but low validity - one that is consistent in getting bad information or consistent in missing the mark. *It is also possible to have one that has low reliability and low validity - inconsistent and not on target. Finally, it is not possible to have a measure that has low reliability and high validity - you can't really get at what you want or what you're interested in if your measure fluctuates wildly.
Do validity mean well grounded?
yup
What is the Validity of IELTS scores?
2 years.
What is regis philbin net worth?
Dave Letterman says 50 billion ...prompting me to check the validity of the statement.
In what situations would reliability be more important that validity?
Considering in test-scoring "reliability" refers to the consistency of the test scores, and "validity" refers to the accuracy of the interpretations made from those scores, then reliability is possible without validity, although validity is not possible without reliability.
Similarity of reliability and validity?
Reliability and validity are both important concepts in research, but they are not the same. Reliability refers to the consistency and stability of a measurement tool, while validity refers to the accuracy and truthfulness of the conclusions drawn from the data collected. Both concepts are crucial in ensuring the credibility and trustworthiness of research findings.
Explain the concept of validity and reliability?
Explain the concepts of reliability,
What are the differences between validity and reliability?
validity is whether the results are valid so the data has no mistakes of as such in it whereas reliability is the dependability; when the results you have are accurate and are of enough quality.
What is validity and reliability in human resource management?
relibality
Characteristics of evaluation?
The characteristics of evaluation are: validity and reliability
What are the 3 major categories of personality measures?
Norms reliability validity
What is the most important when judging the quality of a scientific theory?
validity and reliability
What is the importance of test reliability and validity?
to test if they are measuring what they supposed to measure.
What procedures can be followed to ensure the reliability validity currency and accuracy of data information used by an organisation?
Double checking and verification are some of the procedures that can be followed by an organization to ensure reliability,validity and accuracy of the data information.
What is the criteria for a good test?
A good test should be valid, reliable, and fair. Validity ensures that the test measures what it intends to measure, reliability ensures consistent results upon repeated testing, and fairness ensures that all test takers have an equal opportunity to demonstrate their knowledge or skills.
What is the reliability and validity of California STAR testing?
There is none You're stupid why would you ask that !!!!!!!!!!!!!!!!!!!!!
