In order to establish construct validity you have to meet the following conditions: You have to set the construct you want to operationalize (e.g., self esteem) within a semantic net (or “net of meaning”). Reliability and validity should not be taken as an extra element to the research. Validity refers to how accurately a method measures what it is intended to measure. Establish divergent validity: Little or no relationship should be found between the two scores between the two constructs (e.g., little or no relationship between anger and depression) when comparing the same methods used to collect the data (e.g., comparing anger and depression from the observational scores, and comparing anger and depression from the survey scores). To be able to establish reliability and validity, researchers should not include excessive measures to support their research claims. Discriminant validity (or divergent validity) tests that constructs that should have no relationship do, in fact, have no relationship. Researchers generally establish the construct validity of a measure by correlating it with a number of other measures and arguing from the pattern of correlations that the measure is associated with these variables in theoretically predictable For instance, Item 1 might be the statement “I feel good about myself” rated using a 1-to-5 Likert-type response format. The four types of validity. No single study can establish construct validity [see the article: Construct validity]. Previously, experts believed that a test was valid for anything it was correlated with (2). Therefore, the correct data will be determining true the results of research quality. If they don’t, the questions might not be valid. Construct #1 = Sleep quality For the purpose of this example, let's focus on the scores on the dependent variable, which is sleep quality (i.e., sleep quality is the construct of interest). When participants in the study wake up in the morning, they record their sleep quality using a self-completed survey (i.e., they fill in a questionnaire). 2. There are three sub-sets of criterion validity; convergent, divergent… We say that we are concerned about including these measures within the same measurement procedure because we are unsure whether sleep quality and sleep quantity are part of the same construct or are two different constructs (i.e., let's imagine that no previous studies are able to answer this question for us). Each of these measurement procedures will require a different operational definition. Testing for this type of validity requires that you essentially ask your sample similar questions that are designed to provide you with expected answers. However, now that we look back at Study #1, we are concerned that we included sleep quantity within the same set of measures (e.g., the questions in the survey) that we used when measuring sleep quality. Study #2 4. This is a two-step process: Establish convergent validity: A strong relationship should be established between the two scores for each of the two constructs (e.g., a strong relationship for anger and a strong relationship for depression). JEL Classification: A2, I2. Estimating and Evaluating Convergent and Discriminant Validity Evidence 257 correlated with those crucial variables, test developers and test users gain increased confidence in the test. Validity also establishes the soundness of the methodology, sampling process, d… Another way (divergent validity) is to give people both your questionnaire and one that measures something opposite to what yours measures (scores should be negatively correlated). Types of reliability estimates 5. Imagine that we are interested in studying the relationship between fitness level and sleep quality; that is, the impact that exercise has on how well people sleep. NOTE: Convergent validity is not the same as concurrent validity, which we discuss in more detail in the article: Concurrent validity. However, the survey contains (a) questions that measure sleep quality and (b) questions that measure sleep quantity. Discriminant validity evidence is reported in Rogers et al. To do this, we will have two different measurement procedures and research methods to measure both constructs we are examining. It is far more challenging to create reliable operational definitions for constructs like anger, depression, motivation, and task performance, let alone multiple operational definitions [see the article on Constructs in quantitative research]. Dependent on true or not the data is highly dependent on true or not the same.. 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