POL SOC 360 Measurement

1. POL / SOC 360-01
Spring 2015

5.  Measurement
 Systematic observation and representation using
scores or numerals of variables under investigation
 Numeral: Symbol in form 1, 2, 3, or I, II, III, etc.
 Numeral with quantitative meaning = Number
 Numbers: Description, Explanation, Prediction

6.  Numbers assigned to objects or events
 Example: DummyVariable for Gender
▪ 1 = Females, 0 = “Otherwise” (Males)
 A rule specifies a process used to assign numerals
or numbers to objects and events
 Example: Freedom House

7. POLITICAL RIGHTS
 Electoral Process
 Political Participation
 Functioning of
Government
CIVIL LIBERTIES
 Freedom of Expression
 Associational /
Organizational Rights
 Rule of Law
 Personal Autonomy and
Individual Rights
Free = 1.0 to 2.5
Partly Free = 3.0 to 5.5 Not Free = 5.5 to 7.0

8. FREE PARTLY FREE NOT FREE
Americas 24 (69%) 10 (28%) 1 (3%)
Asia-Pacific 16 (41%) 15 (38%) 8 (21%)
Central /
East Europe
13 (45%) 9 (31%) 7 (24%)
Middle East /
North Africa
1 (6%) 4 (22%) 13 (72%)
Sub-Saharan
Africa
9 (18%) 21 (43%) 19 (39%)
Western Europe 24 (96%) 1 (4%) 0 (0%)

9.  Restating concept so it can be tested
 How will we measure concept?
 Operational Definition – Deciding what
kinds of observations should be made to
measure occurrence of attribute or behavior

10.  Step #1: Thinking through what concept means
and how will we define it
 Step #2: Decide which variables we will use
to measure concept
 Step #3: Propose specific indicators of concept
 Step #4: Select data sets or instruments to
measure indicators

13. INSTRUCTIONS
Devise a measurement strategy
for the following concept:
Conservatism

15. ORDERABLE
 Ordinal Level
 Internal Level
 Ratio Level
NON-ORDERABLE
 Nominal Level

17.  Variable X has values X1, X2, and X3
 X1 < X2 < X3
 Uncertainty of Equality BetweenValues
 Example: Olympic Performance
 X1 = Bronze Medal
 X2 = Silver Medal
 X3 = Gold Medal

19.  Variable X has values X1, X2, and X3
 X1 > X2 > X3
 Equality
 NoTrue Zero
 Example:
Temperature

21.  Interval variable with true zero point
 Examples: Income,Years of Education

23.  Classification of observations into categories
 Examples:
 Religious Faith
▪ 1 = Christian, 2 = Jewish, 3 = Muslim
 Race
▪ 1 =White, 2 = African-American, 3 =Asian
▪ 4 = Native American, 5 = Pacific Islander

25.  Dichotomous
 Variable that can take on only two values
 Example: Gender (Either Male or Female)
 Discrete
 Orderable variable that can take on limited values
 Examples: 1, 2, 3, 4; 1979, 1980, 1981, 1982
 Continuous
 Orderable variable that can take on limitless set of values
 Example: Decimals Pi = 3.14159…

28.  Extent to which a measurement procedure
measures what it intends to measure
 Valid measure provides true and accurate
picture of something

29.  Does the measure appear to be valid “on face?”
 To properly assess face validity, need to know:
▪ Meaning of the concept being measured
▪ Whether information collected is germane to concept
 Examples: Political Ideology; IQTests

30.  Similar to face validity
 Involves more detailed analysis:
 Determining full domain of concept
 Measures of all portions of this domain are included in the
measurement technique
 Does the measure encompass the entire
domain of the concept?
 Example: Freedom House Measure

31.  Occurs when one measure of a concept is
related to measure of another concept with
which original concept is thought to be related
 Concepts should be related in a particular way
 Example of Positive Association
 Example of Negative Association

32.  Involves two measures that theoretically are
not expected to be related to one another
 Correlation is low / weak
 Example: Undergrad GPA and GRE Score

34.  Extent to which measuring instrument
consistently measures what it is measuring
 Consistent results across individuals / times
 Reliability calculated in many ways

35.  Apply same “test” to same observations
after a period of time and then comparing results of
the different measurements
 Example: Liberalism
 Potential problems with this method:
 Measuring at two different points
 First measure affects second measure

36.  Measures same attribute more than
once, but uses two different measures of concept
 Example: Liberalism
 Economic Liberalism
 Social Liberalism

37.  Applies two measures of concept at same time
 Results of two measures compared
 Method avoids problem that concept being
measured may change between measures
 Example: Liberalism