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Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
Measurement - Intro to Quantitative
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Measurement - Intro to Quantitative

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  • Numbers are assigned to things… assign numbers, and you have to create rules on whether and the way numbers are assigned. We care about whether our measures are measuring what they intending to measure
  • When conceptualize, we specify what every term means. Concepts vary in their level of abstraction, in turn, which affects how easily we can identify indicators to measure them.
  • Respondents have explicit options from which to choose & it is easier to analyze with stats.
  • The mathematical precision with which variables can be expressed. The last three progressively become more precise mathematically. You have to decide at which level you will measure each variable. You must be aware whether your variable is at the one of these levels.
  • The nominal has no mathematical interpretation. A person may be a truck driver or a doctor, but he or she does not represent three units more occupation than the other. Gender is an example of a dichotomous variable. It only have 2 values. Republican is assigned 1 Democrat 2
  • Every case can only have one attributeEvery case can be classified into one of those categories. “Other” option is often used to ensure that the response are valid.
  • Permits the researcher not to assess either/or, but rather than greater than or less than. Cultures have to agree that something is less than or greater than which affects the generalizability of the questionnaire
  • Favorable attitudes toward antisocial behavior scale
  • You can add or substract, but because there is no zero…
  • Core alcohol and drug survey
  • Divide and multiply… it is more precise, but also have to think of response. Income level should consist of ranges because people do not like to report their income levels
  • Warning message Falling or number of times falling Gender falling order Jack and Jill went up the hillTo fetch a pail of water.Jack fell down and broke his crown,And Jill came tumbling after Nursery Rhyme
  • Variable that has more thnan one item
  • Structurelikert, semantic differential
  • Sibling communication satisfaction – 15 items, you may have to start with 30 items… I like math.. People will respond to emotions rather than the item. I hate it when my supervisor corrects my mistakesI always communicate competently because no one can honestly say they always communicate compententlyReligious should not have to pay taxes… Religious groups should have to pay taxes would be betterMental Measures Yearbook Buros has a database of mental measures
  • Adding up scores assigned to individual attributesGive 1 point for each of the actions takenObviously people who areThe key is that you want variance. You want reponses to items to vary.
  • Latent variable
  • Attitudinal measurement from Osgood (1952). The most common number of steps is seven. McCroskey and Teven’s (1999) source credibility scale interval level variable that broken down into three dimensions: competence, trustworthiness, caring/goodwill Avoid using jargon such as extraverted/intraverted… talkative/quiet
  • You learned about measurement, now we want to talk about how to prevent measurement error. The goal is to try to reduce error.Pilot study, seek expert advise, use validated scales,
  • Researchers say that a measure is valid if it design measure when it meant to measure. Are your measures measure the full essence of the variable? The measure produces stable, consistent reuslts
  • Mich Alcoholism Screening Test measures 24 questions reflecting the following subscales: recognition of alcohol problems by self & others, legal, social, work problems, help seeking, maritial and family difficulties, liver pathology. Many experts would agree that these dimensions capture the full range of possibilities… the scale is said to have content validity.
  • Judgment-basedCounting the number of drinks people had consumed in the past week would be a face-valid measure of alcohol consumptionHowever, assessing political competence candidates by how mature their faces look may not be a valid indicator
  • Theory building at the operationally levelDrop items with low loadings Internal reliability is critical… more so than predictive reliability
  • Criterion validity is how accurately it predicts a criterion or a well-accepted concept. You calculate the correlation between measures. Measuring the degree to which it predicts another variable. If a particular group rates high on a related variable… and rates high on your variable. It is expected to concurrent validityThe measure of the variable is NOT related to other variables that it theoretically should not be related to.
  • If a measure if reliable, it is affected less by random error.
  • Reliability more than .70 or above is means that people are responding to the test in a consistent manner. Ask for a subset of the sample to retake the survey a few weeks later. Reliability is usually calculated where validity is more difficult to assess
  • Half of the questions in part and the other half in another part. Answers will be 100% in perfect agreement are not ideal, but around 70% is good between halves.
  • Basically are responding to the same way to related items. Reliabilitycoefficent – a numerical value that tells the percentage of time that measure is reliable 1.00 perfect consistency… 0.00 is no consistency Cronbachs most consistently reported reliability test in the social sciencesMcCroskey… If you use an existing scale you have to report the alpha reliability… and if you create one, you have to report it
  • Percent agreement
  • .80
  • Transcript

    • 1. +MeasurementFrom concepts to observationsBy @drcarp | Serena Carpenter
    • 2. +Proposal Paper
    • 3. +Measurement
    • 4. +MeasurementThe process of systematic observation andassignment of numbers to phenomenaaccording to rules
    • 5. +Operationalization
    • 6. +OperationalizationProcess of connecting concepts toobservationsDeveloping procedures to measure variationin variables Process of specifying the operations that willindicate the value of cases on a variable
    • 7. +Concepts Variables |Dimensions IndicatorsBinge Drinking Frequency of heavyepisodic drinking“How often within thepast two weeks did youconsume 5 or moredrinks containingalcohol in a row?”Poverty Subjective povertyAbsolute poverty“Would you say youare poor?”Family income/PovertythresholdSocioeconomicStatusIncomeEducationOccupational prestigeIncome + education +prestige
    • 8. +Constructing questionsAsking people questions is often the mostcommon way to measure social variablesClosed-ended vs. Open-ended
    • 9. +Levels of measurementNominalOrdinalIntervalRatio
    • 10. +NominalVariables have two or more categoriesNo numeric scales but assigned a numberGroups such asMale-femaleStudy in quiet room vs noisy room
    • 11. +Attributes must be:Mutually exclusiveExhaustive
    • 12. +OrdinalRank order points on a scaleIntervals between items are not known or arenot equalExamples:2, 3, or 4-star restaurantsRanking TV shows by popularity
    • 13. +Withinthe last year about howhave used…..Didnotuse1Xperyear6X peryear1X permonth2X permonth1xperweek3Xperweek5XperweekEverydayTobaccoAlcoholMarijuanaCocaineAmphetaminesSedativesOther illegal drugs
    • 14. +IntervalIntervals between points on the scale are ofequal valueNo true “zero” amount
    • 15. +How do you think your closefriends feel (or would feel) aboutyou……Don’tdisapprove DisapproveStronglydisapproveTrying marijuana once or twiceSmoking marijuana occasionallySmoking marijuana regularlyTrying cocaine once or twiceTaking cocaine regularlyTrying LSD once or twiceTaking LSD regularly
    • 16. +Ratio scaleA true zero point – absence of the variableZero on weight means no weightCan form ratios: 10 pounds is twice as heavyas 5 poundsUse more sophisticated statistical tests forratio and interval scalesYou can always transform ratio-levelvariables into lower-level variables
    • 17. +Having observed two youngsters take a nasty spill while fetching water,Research Smith wondered if a warning message to “be careful whileclimbing the hill” might help avert this sort of mishap.He also wondered if males were more likely to fall first, causing their femalepartners (hanging onto the bucket) to come tumbling after.Smith recruited 60 pairs of 10-year-old children to participate in hisexperiment. Each pair consisted of one boy and one girl. Each pair wasgiven a bucket and instructed to go up the hill and fetch a pail of water.Half of the groups were told to “be careful while climbing the hill.” The otherhalf were simply told to fetch the water with no warning. The pairs wererandomly assigned to a “warning” and “no warning” group. The participantsperformed each task separately.Three observers watched all of the pairs. The observers noted if any of thechildren fell down while fetching the water and which child (boy or girl) fellfirst.1. IVs and DVs2. How are they operationally defined?3. What type of measures for each variable (N, O, I, R)
    • 18. +ExerciseList the variables that will be in your studyand place a N, O, I, R to tell me at what levelyou plan to measure your variables
    • 19. +Scales
    • 20. +ScaleComposite measure of a variable
    • 21. +Constructing scales Determine what you want to measure Generate a large pool of items Determine format structure Have a pool of experts to review it Administer it to sample Evaluate items Optimize scale length
    • 22. +Scale creation guidelines Start with twice as many items as you will need Negative worded items Every item should reflect the construct Construct short items (20 words or less) Avoid emotionally-loaded items Double-barreled Avoid using always, never Avoid double negatives/positives
    • 23. +Index Composite measure that summarizes and rank-orders specificobservations and represents some more general dimension Political Activism Wrote a letter to a public official Signed a political petition Gave money to a political cause Gave money to a political candidate Wrote a political letter to the editor Persuaded someone to change his or her voting plans
    • 24. +LikertStrongly disagree, disagree, neither nordisagree, agree, strongly agreeVariable created that cannot be directlyobserved
    • 25. +Semantic DifferentialRespondents rate their opinions on a linearscale between two endpoints that haveopposite meaningsGood/Bad, Dirty/Clean, Moral/ImmoralGood 1 2 3 4 5 6 7 Bad
    • 26. +Measurement error Error is a combo of random error and measurementerror Random – error that cannot be predicted orcontrolled Measurement – faulty measurement procedures
    • 27. +Evaluating levels of measurement:Validity & reliability Validity Face validity Criterion validity Construct validity Reliability Test-retest reliability Interobserver reliability Interitem reliability vs split-half reliability
    • 28. +
    • 29. +Unreliable measureGood 1 2 3 4 5 6 7 BadWrong 1 2 3 4 5 6 7 RightHarmful 1 2 3 4 5 6 7 BeneficialFair 1 2 3 4 5 6 7 UnfairWise 1 2 3 4 5 6 7 FoolishNegative 1 2 3 4 5 6 7 Positive
    • 30. +ValidityDoes the measure cover the full range of theconcept’s meaning?
    • 31. +Face validityThe degree to which a measurement deviceappears to accurately measure a variable
    • 32. +Construct or factorial validity Operational definition of a variable Statistical analysis used to see how items correlate withone another and do not correlate with other items The degree to which the measurement or manipulation ofthe variable accurately reflects the underlying theoreticalconstruct Grouped items are called factors (dimensions)
    • 33. +Criterion validityThe degree to which a measurement deviceaccurately predicts behavior on a criterionmeasurePredictiveConcurrentDiscriminant Validity
    • 34. +ReliabilityConsistency indicates high reliability
    • 35. +Test – retest reliabilityTake measure two timesReliability established when the two scoresare very similarReliability coefficient – a correlationcoefficient that ranges from 0.00 to 1.00Highly similar scores are close to 1.00
    • 36. +Split-half ReliabilityOne administration of the surveyCompare responses to odd- and even-numbered items
    • 37. +Cronbach’s Alpha Reliability Better approach used to establish 0.90+ Excellent 0.80 - .0.90 Good 0.70 - 0.80 Respectable 0.65 - 0.70 Minimally acceptable 0.60 - 0.65 Undesirable - .0.60 Unacceptable
    • 38. +Inter-rater reliabilityExamines the agreement of observationsmade by two or more raters
    • 39. +Intercoder reliabilityTwo or more observers/coders judge thesame phenomenaNominalCohen’s kappa and Scott’s piInterval and ratioCoefficient Alpha
    • 40. +FutureExerciseManuscript structureCritique journal articles exercisesExam Feb. 14thAccess to a computer?

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