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 Measuring Anything That Exists  Concepts as File Folders  Three Classes of Things That can be Measured (Kaplan, 1964) ▪ Direct Observables--Color of.

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Presentation on theme: " Measuring Anything That Exists  Concepts as File Folders  Three Classes of Things That can be Measured (Kaplan, 1964) ▪ Direct Observables--Color of."— Presentation transcript:

1  Measuring Anything That Exists  Concepts as File Folders  Three Classes of Things That can be Measured (Kaplan, 1964) ▪ Direct Observables--Color of the Apple or a Check Mark in a Survey ▪ Indirect Observables--The Check Mark Beside Female in a Questionnaire Indirectly Observes Gender or Historical Accounts of Social Acts ▪ Constructs--Theoretical Creations base on Observations

2  Indicators are Observations We Choose to Represent as a Variable of a Concept We Wish to Study. Going to Church may be Chosen as an Indicator of Religiosity.  Dimensions are Facets or Aspects of Concepts. What are Some Dimensions of LOVE?

3  Different Indicators of a Concept, all Represent to Some Degree, the Same Concept, then all should behave the same way  If Women are More Compassionate Than Men We Should be Able to Observe That Difference by Using any Reasonable Measure of Compassion

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6 Conceptualization Nominal Definition--assigned to a term Operational Definition--spells out how a concept will be measures Measurements in the Real World

7  Concept can be Measured anyway you Choose  But, Most Likely You Will Measure in a way not too Different from Other Peoples Mental Images of the Concept  Measures become Established (CES-D)

8 Why is Level of Measurement Important?  knowing the level of measurement helps you decide how to interpret the data from that variable.  knowing the level of measurement helps you decide what statistical analysis is appropriate on the values that were assigned.

9 There are typically four levels of measurement that are defined: Nominal Ordinal Interval Ratio

10  In nominal measurement the numerical values just "name" the attribute uniquely. No ordering of the cases is implied. For example, jersey numbers in basketball are measures at the nominal level.  A player with number 30 is not more of anything than a player with number 15, and is certainly not twice whatever number 15 is.

11  In ordinal measurement the attributes can be rank-ordered. Here, distances between attributes do not have any meaning.  On a survey you might code Educational Attainment as 0=less than H.S.; 1=some H.S.; 2=H.S. degree; 3=some college; 4=college degree; 5=post college.  In this measure, higher numbers mean more education. But is distance from 0 to 1 same as 3 to 4?

12  In interval measurement the distance between attributes does have meaning.  Measure temperature (in Fahrenheit), the distance from 30-40 is same as distance from 70-80.  The interval between values is interpretable.  Because of this, it makes sense to compute an average of an interval variable.

13  ratio measurement there is always an absolute zero that is meaningful.  This means that you can construct a meaningful fraction (or ratio) with a ratio variable.  In applied social research most "count" variables are ratio, for example, the number of clients in past six months.  Why? Because you can have zero clients and because it is meaningful to say that "...we had twice as many clients in the past six months as we did in the previous six months."

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16  Precision -- Fineness in distinction of measurement -- Region Vs. State Vs. Mailing Address  Accuracy -- reflection of the real world  Do Not Confuse Precision With Accuracy

17  The quality of a measurement that suggests that the same data would be collected each time in repeated observations of the same phenomenon.  Which would give more reliable information: 1) Did you attend church last week? 2) How many times have you attended church in your lifetime?

18  Single Observer as a source of data  Different sort of interviewers get different answers on telephone surveys (social response bias)  May not understand the question  May not care

19  Test-Retest Method -- ask the same questions twice -- the degree that answers vary reflects unreliability  Split-Half Method -- items that measure the same concept are “split in half” and randomly assigned to respondents. Should classify respondents the same way and be correlated  Use established measures  Reliability of research workers

20  Term that describes a measure that accurately reflects concept it is intended to measure. Hard to establish

21  Face Validity -- the degree to which a measure seems reasonable  Criterion-Related Validity -- degree to which a measure relates to an external criterion -- college board and college success

22  Content Validity -- degree that the measures covers the range of meanings included in a concept.  Construct Validity -- degree to which a measure relates to other variables as expected within a system of theoretical relationships

23  Often the specification of a reliable instrument robs the richness of meaning and validity in a concept  Difference between qualitative and quantitative research and idiographic and nomothetic research.


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