Chapter 6: Measurement

1. Chapter 6: Measurement Measurement – systematic observation and representation by numbers of the variables we are trying to examine. • Measurement Strategies • Operationalization • Identify concepts (wealth, income, religiosity, etc.) • Select a measure or indicator of the presence, absence, or amount of these concepts using numbers. So, if you are examining the relationship between two concepts (literacy and democracy), then you need to find measures of two concepts. • Examples of Political Measurement (religiosity, state policy-liberalism, individual conservatism, political participation, liberal judges, liberal courts, informed voter, SC adherence to stare decisis). See example of Segal and Cover p. 156. • Accuracy of Measurement – two threats to measurement confidence; they could be unreliable and/or invalid

2. Reliability – the extent to which the measurement technique/indicator yields the same results given repeated trials. • Examples: a. Concept: my weight. Indicators: ask 20 people to guess it or use a bathroom scale. Which is most reliable? b. Concept: political ideology over time. Indicators: are you a conservative, liberal, or moderate? Or ask them their opinion on 10 policy issues. Most reliable? • Reliability testing • Test-retest – apply the same test to the same observations after a period of time and then compare results of different measurements. Step on the same scale twice to measure weight. • Alternative-form method – measuring the same attribute more than once, but using two different measures of the concept. Compare results. (e.g., step on two different scales to measure weight).

3. c. Split-halves method – using two measures of the concept, but applying them at the same time. Compare them. (e.g., 10 questions of liberalism, split in half, compare them; if about the same, 10-question survey = reliable) • Validity – the extent to which the measurement technique/indicator actually measures (captures) the concept. • Examples: weight and guessing. Valid? • Size of police force and crime (p. 161). Valid? • Testing Validity – • Face validity – simply draw a logical connection between concept and indicator. • Content validity – determine full domain/meaning of concept (all possible understandings) and assess extent to which the indicator speaks to each. C. Practice: Trying to capture drug use with: Did you use illegal drugs last year? Reliable? Valid? • Level of Measurement (precision) • Nominal – whenever values are assigned to categories or classifications. No category is more or less than another category.

4. Examples: race, region, gender (binary or dichotomous) • Must be exhaustive (includes all possible categories for the measure) and mutually exclusive (should be differentiated in such a way that a case will fit into only one category). • Ordinal – categories are assigned values that indicate more or less of some attribute (ranking). Yet, the numbers do NOT represent exact distances from each other. Examples: Letter-grades, 7-point party affiliation scale, 3-categories of education attainment. • Interval – measurement where the values (or intervals between them) have meaning (i.e., they represent equal distances between them). Examples: percent, dollars, years, counts. Practice: 6-3/6-1 KEY POINT: WE DETERMINE THE APPROPRIATE STATISTICAL TECHNIQUE ACCORDING TO THE LEVEL OF MEASUREMENT FOR THE DEPENDENT VARIABLE (OLS Regression for Interval, Logistic Regression for Dichotomous-Nominal, Multinomial logit for nominal data with more than 2 categories, Ordered Probit for Ordinal)