1 / 27

Reliability and Validity

Reliability and Validity. Criteria of Measurement Quality. How do we judge the relative success (or failure) in measuring various concepts? Reliability – consistency of measurement Validity – confidence in measures and design. Reliability and Validity. Reliability focuses on measurement

gussiel
Télécharger la présentation

Reliability and Validity

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Reliability and Validity

  2. Criteria of Measurement Quality • How do we judge the relative success (or failure) in measuring various concepts? • Reliability – consistency of measurement • Validity – confidence in measures and design

  3. Reliability and Validity • Reliability focuses on measurement • Validity also extends to: • Precision in the design of the study – ability to isolate causal agents while controlling other factors • (Internal Validity) • Ability to generalized from the unique and idiosyncratic settings, procedures and participants to other populations and conditions • (External Validity)

  4. Reliability • Consistency of Measurement • Reproducibility over time • Consistency between different coders/observers • Consistency among multiple indicators • Estimates of Reliability • Statistical coefficients that tell use how consistently we measured something

  5. Measurement Validity • Are we really measuring concept we defined? • Is it a valid way to measure the concept? • Many different approaches to validation • Judgmental as well as empirical aspects

  6. Key to Reliability and Validity • Concept explication • Thorough meaning analysis • Conceptual definition: • Defining what a concept means • Operational definition: • Spelling out how we are going to measure concept

  7. Four Aspects of Reliability: • 1. Stability • 2. Reproducibility • 3. Homogeneity • 4. Accuracy

  8. 1. Stability • Consistency across time • repeating a measure at a later time to examine the consistency • Compare time 1 and time 2

  9. 2. Reproducibility • Consistency between observers • Equivalent application of measuring device • Do observers reach the same conclusion? • If we don’t get the same results, what are we measuring? • Lack of reliability can compromise validity

  10. 3. Homogeneity • Consistency between different measures of the same concept • Different items used to tap a given concept show similar results – ex. open-ended and closed-ended questions

  11. 4. Accuracy • Lack of mistakes in measurement • Increased by clear, defined procedures • Reduce complications that lead to errors • Observers must have sufficient: • Training • Motivation • Concentration

  12. Increasing Reliability • General: • Training coders/interviewers/lab personnel • More careful concept explication (definitions) • Specification of procedures/rules • Reduce subjectivity (room for interpretation) • Survey measurement: • Increase the number of items in scale • Weeding out bad items from “item pool” • Content analysis coding: • Improve definition of content categories • Eliminate bad coders

  13. Indicators of Reliability • Test-retest • Make measurements more than once and see if they yield the same result • Split-half • If you have multiple measures of a concept, split items into two scales, which should then be correlated • Cronbach’s Alpha or Mean Item-total Correlation

  14. Reliability and Validity • Reliability is a necessary condition for validity • If it is not reliable it cannot be valid • Reliability is NOT a sufficient condition for validity • If it is reliable it may not necessarily be valid • Example: • Bathroom scale, old springs

  15. Not Reliable or Valid

  16. Reliable but not Valid

  17. Reliable and Valid

  18. Types of Validity • 1. Face validity • 2. Content validity • 3. Pragmatic (criterion) validity • A. Concurrent validity • B. Predictive validity • 4. Construct validity • A. Testing of hypotheses • B. Convergent validity • C. Discriminant validity

  19. Face Validity • Subjective judgment of experts about: • “what’s there” • Do the measures make sense? • Compare each item to conceptual definition • Do it represent the concept in question? • If not, it should be dropped • Is the measure valid “on its face”

  20. Content Validity • Subjective judgment of experts about: • “what is not there” • Start with conceptual definition of each dimension: • Is it represented by indicators at the operational level? • Are some over or underrepresented? • If current indicators are insufficient: • develop and add more indicators • Example--Civic Participation questions: • Did you vote in the last election? • Do you belong to any civic groups? • Have you ever attended a city council meeting? • What about “protest participation” or “online organizing”?

  21. Pragmatic Validity • Empirical evidence used to test validity • Compare measure to other indicators • 1. Concurrent validity • Does a measure predict simultaneous criterion? • Validating new measure by comparing to existing measure • E.g., Does new intelligence test correlate with established test • 2. Predictive validity • Does a measure predict future criterion? • E.g., SAT scores: Do they predict college GPA?

  22. Construct Validity • Encompasses other elements of validity • Do measurements: • A. Represent all dimensions of the concept • B. Distinguish concept from other similar concepts • Tied to meaning analysis of the concept • Specifies the dimensions and indicators to be tested • Assessing construct validity • A. Testing hypotheses • B. Convergent validity • C. Discriminant validity

  23. A. Testing Hypotheses • When measurements are put into practice: • Are hypotheses that are theoretically derived, supported by observations? • If not, there is a problem with: • A. Theory • B. Research design (internal validity) • C. Measurement (construct validity?) • In seeking to examine construct validity: • Examine theoretical linkages of the concept to others • Must identify antecedent and consequences • What leads to the concept? • What are the effects of the concept?

  24. B. Convergent Validity • Measuring a concept with different methods • If different methods yield the same results: • than convergent validity is supported • E.g., Survey items measuring Participation: • Voting • Donating to money to candidates • Signing petitions • Writing letters to the editor • Civic group memberships • Volunteer activities

  25. C. Discriminant (Divergent) Validity • Measuring a concept to discriminate that concept from other closely related concepts • E.g., Measuring Maternalism and Paternalism as distinct concepts

  26. Dimensions of Validity for Research Design • Internal • Validity of research design • Validity of sampling, measurement, procedures • External • Given the research design, how valid are • Inferences made from the conclusions • Implications for real world

  27. Internal and External Validity in Experimental Design • Internal validity: • Did the experimental treatment make a difference? • Or is there an internal design flaw that invalidates the results? • External validity: • Are the results generalizable? • Generalizable to: • What populations? • What situations? • Without internal validity, there is no external validity

More Related