For a questionnaire to be regarded as acceptable, it must possess two very important qualities which are reliability and validity. 2. Also, poor reliability degrades the level of precision. Although face validity can be assessed quantitatively—for example, by having a large sample of people rate a measure in terms of whether it appears to measure what it is intended to—it is usually assessed informally. While a reliable test may provide useful valid information, a test that is not reliable cannot possibly be valid. ). It is important to understand the differences between reliability and validity. Validity is defined as the extent to which a measure or concept is accurately measured in a study. Validity refers to how accurately a method measures what it is intended to measure. If at this point your bathroom scale indicated that you had lost 10 pounds, this would make sense and you would continue to use the scale. It involves people's opinions, and opinions can be wrong! The main difference between validity and reliability is that validity is the extent to which a test measures, and what it claims to measure whereas reliability refers to the consistency of the test results.. Tests or research of any kind is measured upon validity and reliability. Types of reliability estimates 5. Validity is the extent to which an instrument measures the attributes of a concept accurately. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure. This is as true for behavioural and physiological measures as for self-report measures. The extent to which the result of a measure corresponds to. We have already considered one factor that they take into account—reliability. Compute Pearson’s. Reliability refers to the consistency of a measure. But how do researchers make this judgment? When an instrument is valid, it truly reflects the concept it is supposed to measure. When you do quantitative research, you have to consider the reliability and validity of your research methods and instruments of measurement. Validity states whether an instrument actually measures what it intends to measure, and reliability refers to the reproduc- ibility of the outcome measure. Things are slightly different, however, in … A person who is highly intelligent today will be highly intelligent next week. This includes the chosen sample set and size, sample preparation, external conditions and measuring techniques. If people’s responses to the different items are not correlated with each other, then it would no longer make sense to claim that they are all measuring the same underlying construct. For example, self-esteem is a general attitude toward the self that is fairly stable over time. When you use a tool or technique to collect data, it’s important that the results are precise, stable and reproducible. Validity is defined as the extent to which a measure or concept is accurately measured in a study. When the criterion is measured at the same time as the construct. In evaluating a measurement method, psychologists consider two general dimensions: reliability and validity. Validity gives us an indication of whether the measuring device measures what it claims to. June 26, 2020. by Reliability is a measure of the internal consistency and stability of a measuring device. Define validity, including the different types and how they are assessed. Standard error of measurement 6. The reliability of an assessment tool is the extent to which it consistently and accurately measures learning. Criteria can also include other measures of the same construct. The thermometer displays the same temperature every time, so the results are reliable. Reliability estimates evaluate the stability of measures, internal consistency of measurement instruments, and interrater reliability of instrument scores. Again, measurement involves assigning scores to individuals so that they represent some characteristic of the individuals. An instrument that is not reliable (internal consistency, test–retest) by definition cannot be valid. Concurrent validity: This occurs when criterion measures are obtained at the same time as test scores,   indicating the ability of test scores in estimating an individual’s current For example, on a test that measures levels of depression, the test would be said to have concurrent validity if it measured the current levels of depression experienced by the test taker. This indicates that the questionnaire has low reliability as a measure of the condition. On the Rosenberg Self-Esteem Scale, people who agree that they are a person of worth should tend to agree that that they have a number of good qualities. Reliability refers to the extent to which the same answers can be obtained using the same instruments more than one time. It’s appropriate to discuss reliability and validity in various sections of your thesis or dissertation. In Quantitative research, reliability refers to consistency of certain measurements, and validity – to whether these measurements “measure what they are supposed to measure”. In the years since it was created, the Need for Cognition Scale has been used in literally hundreds of studies and has been shown to be correlated with a wide variety of other variables, including the effectiveness of an advertisement, interest in politics, and juror decisions (Petty, Briñol, Loersch, & McCaslin, 2009)[2]. If their research does not demonstrate that a measure works, they stop using it. While a reliable test may provide useful valid information, a test that is not reliable cannot possibly be valid. Reliability and validity are two very important qualities of a questionnaire. • Reliability is related with precision, whereas validity is … Methods for conducting validation studies 8. A reliable measurement is not always valid: the results might be reproducible, but they’re not necessarily correct. For example, one would expect new measures of test anxiety or physical risk taking to be positively correlated with existing measures of the same constructs. Were they consistent, and did they reflect true values? • By saying “a sample is reliable,” it doesn’t mean it is valid. When new measures positively correlate with existing measures of the same constructs. While reliability deals with consistency of the measure, validity deals with accuracy of the measure. While reliability reflects reproducibility, validity refers to lack of bias. Even if a test is reliable, it may not accurately reflect the real situation. Face validity is the extent to which a measurement method appears “on its face” to measure the construct of interest. The Minnesota Multiphasic Personality Inventory-2 (MMPI-2) measures many personality characteristics and disorders by having people decide whether each of over 567 different statements applies to them—where many of the statements do not have any obvious relationship to the construct that they measure. It is not the same as mood, which is how good or bad one happens to be feeling right now. Psychologists consider three types of consistency: over time (test-retest reliability), across items (internal consistency), and across different researchers (inter-rater reliability). A split-half correlation of +.80 or greater is generally considered good internal consistency. The very nature of mood, for example, is that it changes. The assessment of reliability and validity is an ongoing process. Reliability and validity The reliability of an assessment tool is the extent to which it measures learning consistently. A group of participants complete a questionnaire designed to measure personality traits. A doctor uses a symptom questionnaire to diagnose a patient with a long-term medical condition. Validity refers to the extent that the instrument measures what it was designed to measure. If similar outcome is resulted at all the attempts, then the measurements are reliable. Questionnaire Reliability. Validity is the extent to which the scores from a measure represent the variable they are intended to. Reliability shows how trustworthy is the score of the test. A measurement can be reliable without being valid. But other constructs are not assumed to be stable over time. [78] While IQ tests are generally considered to measure some forms of intelligence, they may fail to serve as an accurate measure of broader definitions of human intelligence inclusive of creativity and social intelligence . As an informal example, imagine that you have been dieting for a month. The statistical choice often depends on the design and purpose of the questionnaire. 1. This is not the same as reliability, which is the extent to which a measurement gives results that are very consistent. By checking how well the results correspond to established theories and other measures of the same concept. View Notes - 07 Measurement Reliability and Validity notes.pptx from PSY 2060 at Barton College. But if it indicated that you had gained 10 pounds, you would rightly conclude that it was broken and either fix it or get rid of it. Reliability and validity are considered the main measurement properties of such instruments. The results are reliable, but participants’ scores correlate strongly with their level of reading comprehension. Comment on its face and content validity. Every metric or method we use, including things like methods for uncovering usability problems in an interface and expert judgment, must be assessed for reliability. In this first one, I'll cover measurement reliability, because that property is more basic. Are the questions that are asked representative of the possible questions that could be asked? What data could you collect to assess its reliability and criterion validity? When they created the Need for Cognition Scale, Cacioppo and Petty also provided evidence of discriminant validity by showing that people’s scores were not correlated with certain other variables. A statistic in which α is the mean of all possible split-half correlations for a set of items. Most people would expect a self-esteem questionnaire to include items about whether they see themselves as a person of worth and whether they think they have good qualities. It’s important to consider reliability and validity when you are creating your research design, planning your methods, and writing up your results, especially in quantitative research. A valid instrument that is supposed to measure anxiety does so; it does not measure some other concept, such as stress. In general, a test-retest correlation of +.80 or greater is considered to indicate good reliability. We can draw a conclusion about the reliability by taking the same measurement using the same conditions few times. For example, Figure 5.3 shows the split-half correlation between several university students’ scores on the even-numbered items and their scores on the odd-numbered items of the Rosenberg Self-Esteem Scale. So people’s scores on a new measure of self-esteem should not be very highly correlated with their moods. The finger-length method of measuring self-esteem, on the other hand, seems to have nothing to do with self-esteem and therefore has poor face validity. Pearson’s r for these data is +.88. Please click the checkbox on the left to verify that you are a not a bot. When the results of an assessment are reliable, we can be confident that repeated or equivalent assessments will provide consistent results. Consider the SAT, used as a predictor of success in college. This puts us in a better position to make generalised statements about a student’s level of achievement, which is especially important when we are using the results of an assessment to make decisions about teaching and learning, or when we are reporting bac… In essence, it is how well a test or piece of research measures what it is intended to measure. The former measures the consistency of the questionnaire while the latter measures the degree to which the results from the questionnaire agrees with the real world. Reliability and validity are separate psychometric properties. This is the moment to talk about how reliable and valid your results actually were. You cannot draw valid conclusions from a test score unless you are sure that the test is reliable. In a research design, especially in a quantitative research, reliability and validity are highly important. Revised on Practice: Ask several friends to complete the Rosenberg Self-Esteem Scale. Usually, these two measurements are used in psychological tests and research materials. Reliability and validity are two very important qualities of a questionnaire. It’s important to consider reliability and validity when you are creating your research design , planning your methods, and writing up your results, especially in quantitative research . Start studying reliability and validity of a measure. Using validity evidence from outside studies 9. The extent to which the results really measure what they are supposed to measure. You measure the temperature of a liquid sample several times under identical conditions. Assessing convergent validity requires collecting data using the measure. Reliability is the ability to reproduce a result consistently in time and space. Reliability refers to the extent that the instrument yields the same results over multiple trials. Every metric or method we use, including things like methods for uncovering usability problems in an interface and expert judgment, must be assessed for reliability. It is possible to have reliable measurements that lack validity. Exercises. Or imagine that a researcher develops a new measure of physical risk taking. When an instrument is valid, it truly reflects the concept it is supposed to measure. Pearson’s r for these data is +.95. Responsiveness is the ability of the score to monitor changes (sensitivity of the score to measure change over time). However, reliability on its own is not enough to ensure validity. There are several important principles. Validity is defined as the extent to which a concept is accurately measured in a quantitative study. Ensure that you have enough participants and that they are representative of the population. The extent to which different observers are consistent in their judgments. Reliability and validity are closely related, but they mean different things. Discussion: Think back to the last college exam you took and think of the exam as a psychological measure. Reliability is a statistical measure of how reproducible the survey instrument’s data is. If the thermometer shows different temperatures each time, even though you have carefully controlled conditions to ensure the sample’s temperature stays the same, the thermometer is probably malfunctioning, and therefore its measurements are not valid. The second measure of quality in a quantitative … View Notes - 07 Measurement Reliability and Validity notes.pptx from PSY 2060 at Barton College. Different types of reliability can be estimated through various statistical methods. The normal book, fiction, history, novel, scientific research, … Reliability, validity and the structure of the General Health Questionnaire in a Chinese context - Volume 13 Issue 2 - David W. Chan, Tims S. C. Chan Skip to main content Accessibility help We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Your clothes seem to be fitting more loosely, and several friends have asked if you have lost weight. The extent to which the scores from a measure represent the variable they are intended to. If the new measure of self-esteem were highly correlated with a measure of mood, it could be argued that the new measure is not really measuring self-esteem; it is measuring mood instead. Validity should be considered in the very earliest stages of your research, when you decide how you will collect your data. Within validity, the measurement does not always have to be similar, as it does in reliability. As our example suggests, having the first without the second hints at high but inaccurate consistency. Survey reliability on its own doesn’t effectuate/establish validity and vice versa. Validity refers to the property of an instrument to measure exactly what it proposes. It is possible to have reliable measurements that lack validity. Reliability is directly related to the validity of the measure. To assess the validity of a cause-and-effect relationship, you also need to consider internal validity (the design of the experiment) and external validity (the generalizability of the results).

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