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Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
Chapter 5
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Chapter 5

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  • 1. Measuring Variables and Sampling
  • 2. Roadmap Today: Begin Exam 2 material (Chapters 5, 6, 4)  Scales of measurement  Psychometric properties  Reliability  ValidityTuesday:  Finish chapter 5  Discuss Exam 1
  • 3. Zoom out: where are we? We have:  A research question  An idea for a research design  A hypothesisBut how do we measure what we’re interested in?
  • 4. Scales of Measurement  to measure themWe study variables and need accurately4 scales of measurement  Nominal  Ordinal  Interval  Ratio
  • 5. Nominal Scale symbols classify or categorize into GROUPS or TYPES  Name, Categorize, Classify  Caution: use of numbers to indicate groupExamples- gender, marital status, experimental condition
  • 6. Ordinal Scale A rank order scale of measurementExamples- order of finish, Letter grade in class, social class (low, med., high)Allows you to determine which person is higher or lower but not how much higher or lower.  Can’t make direct comparisons
  • 7. Interval Scale Rank ordering PLUS equal intervals of distance between adjacent numbersExample- Celsius and Fahrenheit temperature, IQ scores, yearNow you can make comparisonsEqual distances but no absolute zero point
  • 8. Ratio Scale rank ordering, equal intervals PLUS an absolute zero pointAbsolute zero = absence of variableExamples- Kelvin temperature, income, weight, height, response time.
  • 9. Psychometric properties Reliability: Consistency/stability of scoresValidity: Are you measuring what you are trying to measure?Ideally, we want:  Measures that are reliable  Inferences that are validReliability is necessary but not sufficient in order to have validity
  • 10. Think about a Target 
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  • 14. Measuring Reliability 4 Primary types  Test-Retest Reliability  Equivalent- Forms Reliability  Internal Consistency Reliability  Interrater ReliabilityIndicate level of reliability with a reliability coefficient  Correlation; should be positive and strong (> .70)
  • 15. Test- Retest Refers to consistency over timeSame measure administered twice (with a time interval between)
  • 16. Equivalent-Forms Reliability Equivalent forms- two versions of the same measure  Administer to the same group of peopleProblem- hard to develop equivalent measuresExample: SAT, GRE
  • 17. Internal Consistency Consistency with which test items measure a single construct.More items increases reliability, but we use as few items as possible  Why?
  • 18. Example: Internal Consistency I feel sadI feel downI feel depressedI feel miserableI feel awful
  • 19. Example: Internal Consistency I feel hungryI feel happyI have green eyesBig Bird is scaryI like turtles  http://www.youtube.com/watch?v=CMNry4PE93Y
  • 20. Internal Consistency Measured using coefficient alpha (α)  a.k.a. Cronbach’s alpha  Should be .7 or higherHigh values mean the items are measuring the same constructIf your scale measures more than 1 thing, each construct gets its own coefficient α
  • 21. Interrater Reliability  of ratings madeInterrater reliability- consistency by different judges  GRE writing section  Expressive writing studies  Correlation between ratings should be strong/positive
  • 22. Interobserver Agreement  observers agreepercentage of times different  % of times raters agree- easy to calculate and understand
  • 23. Validity Accuracy of inferences or interpretations made on the basis of scoresMeasuring schizophrenia, or love  We can’t directly observe it!  It’s the accuracy of the interpretation from the test
  • 24. Validity ConstructOperationalizationImportant to consider:  Does your operationalization truly reflect what you’re measuring?ValidationNever-ending process
  • 25. Obtaining Validity: Based on Content Content validity: judgment of the degree to which items adequately represent a construct’s domain.  Do items appear to represent the thing you’re trying to measure? (face validity)  Does your measure exclude any important parts of what you’re trying to measure?  Does your test measure something besides what you wanted? (i.e., include irrelevant items)
  • 26. Obtaining Validity: Based on Internal Structure Some constructs are multidimensional and need measures that address all dimensionsHomogeneity—degree to which a set of items measure a single construct  Item-to-total correlation  Coefficient alpha
  • 27. Obtaining Validity: Based on Relations to Other Variables Criterion-related validity: degree to which scores predict or relate to an already established testTwo types of criterion validity:  Predictive: using your measure to predict future performance  Concurrent: using your measure to predict current performance on the same construct, or a related one.
  • 28. Obtaining Validity: Based on Relations to Other Variables Convergent validity: relationship between your measure and other measures of that same constructDiscriminant validity: evidence that scores from your measure are NOT similar to scores of tests on different constructs.
  • 29. Appropriate Use of Reliability and Validity Info Reliability and validity info apply to the measure of interest in the reported sample  Situation-specific, not broadStandardized tests: norming group  If you want to use a test with a group not represented in the norming group, be cautiousReport R & V for your own sample, and be wary of articles that make blanket statements about a measure’s R & V

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