

You create a survey to measure the regularity of people’s dietary habits. If some aspects are missing from the measurement (or if irrelevant aspects are included), the validity is threatened and the research is likely suffering from omitted variable bias. To produce valid results, the content of a test, survey or measurement method must cover all relevant parts of the subject it aims to measure. Content validityĬontent validity assesses whether a test is representative of all aspects of the construct. The other types of validity described below can all be considered as forms of evidence for construct validity. The questionnaire must include only relevant questions that measure known indicators of depression. To achieve construct validity, you have to ensure that your indicators and measurements are carefully developed based on relevant existing knowledge. If you develop a questionnaire to diagnose depression, you need to know: does the questionnaire really measure the construct of depression? Or is it actually measuring the respondent’s mood, self-esteem, or some other construct? What is construct validity?Ĭonstruct validity is about ensuring that the method of measurement matches the construct you want to measure. But based on existing psychological research and theory, we can measure depression based on a collection of symptoms and indicators, such as low self-confidence and low energy levels. There is no objective, observable entity called “depression” that we can measure directly.

If you are doing experimental research, you also need to consider internal and external validity, which deal with the experimental design and the generalizability of results. Note that this article deals with types of test validity, which determine the accuracy of the actual components of a measure. In quantitative research, you have to consider the reliability and validity of your methods and measurements.


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