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Psychology 2020 Measurement & Observing Behavior

Psychology 2020 Measurement & Observing Behavior. Unit 2. Measurement Reliability. Measurements consist of two components. Both must be inferred because they can’t be directly observed True score The real score of the variable that exists hypothetically and is considered a constant

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Psychology 2020 Measurement & Observing Behavior

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  1. Psychology 2020 Measurement &Observing Behavior Unit 2

  2. Measurement Reliability • Measurements consist of two components. Both must be inferred because they can’t be directly observed • True score • The real score of the variable that exists hypothetically and is considered a constant • Measurement error • The portion of the measurement result that varies from measurement to measurement • The higher the correlation (r near 1) between two measurements, the more reliable the measurement

  3. Assessing the Reliability of Psychological Measures • Test-Retest Reliability • Take the measurement at two different times and correlate the results (r =.8 to be considered reliable). • Internal Consistency Reliability • Split test in half an correlate the scores on the first half with the scores on the second half • Correlate every item score with every other item score (Cronbach’s alpha) • Correlate every item score with the total score • Interrater Reliability • Correlate rater scores with each other

  4. Validity in Research • Validity refers to “truth” and accuracy of measurement • INTERNAL validity (extent to which IV has influence on DV) • EXTERNAL validity (extent to which results obtained can be generalized) • CONSTRUCT validity • Several types

  5. Measurement Validity • If a measurement tool is valid, it is really measuring the construct it purports to measure rather than some other characteristic • A valid measurement tool is said to have “Construct Validity”

  6. Methods to Assess Construct Validity • Face Validity (does it appear valid) • An IQ test that only asked questions about a person’s income, address and clothing preferences would have little face validity • Criterion-Oriented Validity (does it allow accurate predictions) • A safe-driving test that passed people who continued to have driving accidents would lack criterion-oriented validity

  7. Forms of Criterion-Oriented Validity • Predictive Validity- ability to predict something it should theoretically be able to predict. • A measure of math ability accurately predicts who will be a successful engineer • Concurrent Validity- ability to distinguish between groups that it should theoretically be able to distinguish between • A measure of anxiety distinguishes individuals with an anxiety disorder from those with major depression

  8. Forms of Criterion-Oriented Validity • Convergent Validity- results from the measure are similar to other measures of the same construct • The block assembly IQ test yields high IQ scores with the same people who got high IQ scores on a spatial problem solving IQ test. • Discriminant Validity- results from the measure are NOT similar to measures of theoretically different constructs. • An abstract-reasoning test yields different results that a rote-memory test

  9. Measurement Reactivity • Reactivity in measurement is when the very act of measuring a variable changes that variable • Example: recording the amount of food eaten each a day causes the person to eat less • Using unobtrusive measures reduces the probability of measurement reactivity

  10. Measurement Scales

  11. Measurement Scales • Nominal • No numerical properties, only named categories • Examples: male or female, married or single • Ordinal • Has numerical properties but only for the purpose of ordering the categories from first to last • Examples: Academic grades, places in a race, ranking schools or sports teams

  12. Measurement Scales • Interval • Has numerical properties with equal distance between each number on the scale but no zero point (representing a total absence of the thing being measured). • Example: Rating beauty on a scale of 1-10 • Ratio • Same as the interval scale (equal intervals between numbers) except there is a zero point. • Examples: time measures, response rate measures, other physical measurements.

  13. Name the Measurement Scale • A food critic rates restaurants according to the quality of food, service, and atmosphere. She assigns 4 forks for excellent, 3 for good, 2 for fair, and 1 fork for poor • Researchers have identified styles of leadership as relationship-oriented or task-oriented • Rating satisfaction on a scale of 1 to 100 • A measurement of weight

  14. Name the Measurement Scale • Getting a count of the number of automobiles on the highway that were made in Europe, Japan and the USA (totals for each group) • The score you receive on the Beck Depression scale (1-18 is not depressed, above 18 is depressed) • Deciding if a house style is Victorian, Tudor, or Greek Revival • Measuring how long it takes someone to drink a beer

  15. General Observational Approaches • Quantitative approaches • Emphasize numerical properties of the thing being observed • Observational results can be statistically analyzed • Examples • Hours spent studying • Ranking of task difficulty • Percentage of on-task behavior

  16. General Observational Approaches • Qualitative approaches • Emphasizes the nonnumerical aspects of the thing being observed • Usually consists of descriptive paragraphs • Statistical analysis of data in this form is not possible • Examples • Diaries • Film documentaries • Written summaries of main themes and/or styles observed

  17. Naturalistic Observation • Observing and recording behavior in its natural setting • Quantitative or qualitative • Confirmation through multiple observations

  18. Issues in Naturalistic Observation • Participation • Concealment • Accuracy v. ethics • Scope of observation • Complexity • Limits of observation • Public v. private • Uncontrollable factors

  19. Systematic Observation • Careful observation of specific behaviors in specific settings using structured, quantifiable methods (coding systems) • Statistical data analysis

  20. Methodological Issues • Technical equipment (video tape, computers, clocks, etc.) • Reactivity • Reliability • Sampling

  21. Video

  22. Case Studies • Case studies are usually extensive descriptions of one individual or organization over a period of time. • Case studies are one form of naturalistic observation research • Case studies are conducted when an individual is unusual, has a rare disorder or noteworthy condition • Case studies provide valuable information that is not available in other forms of research

  23. Archival Research • Archival research uses data that was previously collected and compiled (usually for other reasons) to answer new questions • Two problems exist for doing archival research • The necessary records or documents may be difficult to obtain • The accuracy of information collected by someone else is always suspect

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