Chapter 05 Measurement

measurementChapter 5Measurement is --The use of numbers as a tool for identifying and presenting informationThe process that links the conceptual to the empiricalNecessary to conduct quantitative researchMeasurement principlesNumbers measure value, intensity, degree, depth, length, width, distanceDescriptive and evaluative deviceNumbers have no value until we provide meaning Includes everything the researcher does to arrive at a numberDetails the operationalization of the variableLevels of measurementData are discrete or continuous Both can represent communication phenomenaEach produces different kind of dataHow data are collected determines how they can be used in statistical analysesDiscrete dataThe presence or absence of some characteristicAlso known as nominal or categorical dataCategories Reflect different types not differing amountsHave no inherent valueMust be mutually exclusive, exhaustive, and equivalentContinuous levels of measurementReveals quantity, intensity, or magnitudeValues that differ in degree, amount, or frequency can be ordered on a continuumThree typesOrdinal dataInterval dataRatio dataOrdinal data Ranks elements in logical numerical order1st, 2nd, 3rd, 4th . . .Sequence suggests value of dataRanking positions are relative Distance between ranks is unknownZero does not existInterval dataIdentifies highest, next highest, and so on4, 8, 10, 14, 22, 25, 29, 31, 32, 37, 41, 42 . . . Identifies exact difference between and among scoresAcknowledges zeroAllows meaningful comparisons2 types of interval scalesLikert-type scalesSemantic differential scalesStrongly disagreeDisagreeUndecidedAgreeStrongly agree12345Not at allfriendly--------------Very friendlyratio dataAll of the characteristics of interval data Zero is absoluteIndicates complete lack of the variable measuredProvides measure of degree to which something actually exists0, 4, 8, 10, 14, 22, 25, 29, 31, 32, 37, 41, 42 . . .validityExtent to which it measures what you want it to measure and not something elseValidity is a matter of degreeInternal validityFace validityContent validityCriterion-related validity: concurrent or predictiveConstruct validityreliabilityDegree of consistency among similar itemsReliability coefficient – 0.0 to 1.0Closer to 1.00, the greater the degree of reliabilityGenerally, above .70 is acceptableInternal reliabilityMultiple items invoke similar responseRelationship between validity and reliabilityA measurement should be both valid and reliableValidity and reliability connected in fundamental waysReliable measurements can be obtained without validityWhen validity is achieved, reliability is presumedThreats to validity and reliabilityIssues of data collectionInternal validityReliability over timeIssues of sample representativenessExternal validityEcological validityDo alternative explanations exist?Issues of data representationResearchers responsible for Collecting data accurately and ethicallyInterpreting and reporting data responsiblyQuality of data interpretation cannot be better than quality of data collectedMeasurement is central to quality of outcomes and links to theory