Measurement in Psychology and Statistical Analysis Quiz

Key Concepts in Measurement and Psychometrics

• Levels of measurements: There are four levels of measurement - nominal, ordinal, interval, and ratio - each representing a different level of precision and mathematical operations.
• Observer/expectancy bias: This bias occurs when the observer's expectations or beliefs influence their interpretation or recording of data, leading to inaccurate or biased results.
• Classical test theory: This theory states that an observed score is the sum of a true score and error, and it provides an equation to calculate reliability by comparing true score variance and observed score variance.
• Reliability: Reliability refers to the consistency or stability of a measurement instrument, and it can be estimated empirically using various methods.
• Regression to the mean: This phenomenon occurs when extreme scores on a variable tend to move closer to the mean upon retesting, highlighting the role of random error in measurement.
• Confidence intervals: Confidence intervals provide a range of values within which the true population parameter is likely to fall, and they are used to estimate the precision of a sample statistic.
• Threats to content validity: Content validity refers to the extent to which a measurement instrument adequately covers the content domain of interest, and threats to it include inadequate sampling or inappropriate item selection.
• Scree plot: A scree plot is a graphical representation of the eigenvalues of factors in factor analysis, helping determine the number of factors to extract.
• Higher order and bifactor models: Higher order models involve a second-order factor that explains the relationships among multiple first-order factors, while bifactor models include both specific and general factors.
• Adverse consequences in testing: These refer to negative outcomes or unintended effects that may arise from the use of tests, such as discrimination or misinterpretation of results.
• Reliability vs validity: Reliability refers to consistency, while validity refers to the extent to which a test measures what it intends to measure.
• Approaches to evaluating convergent and discriminant validity evidence: These include correlational, multitrait-multimethod, confirmatory factor analysis, and factor analytic approaches.
• EFA vs CFA: Exploratory factor analysis (EFA) is used to explore the structure of data and identify underlying factors, while confirmatory factor analysis (CFA) tests a pre-specified factor structure.

This quiz covers a range of topics related to measurement in psychology and statistical analysis. Test your knowledge on concepts such as levels of measurement, observer and expectancy bias, classical test theory, reliability calculations, regression to the mean, confidence intervals, threats to content validity, and more. Perfect for students or professionals looking to test their understanding of these key concepts.