1 Measurement Adapted from The Research Methods Knowledge Base, William Trochim (2006). & Methods for Social Researchers in Developing Counries, The Ahfad University for Women & Online Statistics Education: A Multimedia Course of Study, David M. Lane, Rice University.

2 Agenda Introduction Validity Reliability Reliability & Validity Level of measurement 2

3 Introduction All collection of data involves measurement Measurements of some attributes can be complex –Ex: empowerment of women; health Good measurement scales need to be both valid and reliable

4 Validity The validity of a test refers to whether the test measures what it is supposed to measure Three common types of validity: –Face Validity: same as above –Predictive Validity: a test’s ability to predict relevant behavior –Construct Validity: how well you translate your ideas or theories into actual programs or measures

5 Construct Validity Essentially a labeling issue –Example: when you measure empowerment, is that really what you are measuring? Can be established by showing convergent and divergent validity –Convergent: Whether your test correlate with other tests that measure the same construct –Divergent: Whether your test does not correlate with tests of other constructs –Example: Testing spatial ability  Convergent: correlates with other measures of spatial ability  Divergent: correlates less with tests of verbal ability

6 Reliability Reliability is the “consistency” or “repeatability” of your measures The reliability of our measure is affected by random or systematic error –Random error: caused by factors that randomly affect measurement of variable across the sample –Systematic error: caused by factors that systematically affect measurement of variable

7 Reliability & Validity Recall: –Reliability is how “consistent” the measurement is –Validity is whether we are measuring the right concept (hitting the target)

8 Level of measurement Refers to the relationship among the values that are assigned to the attributes of a variable There are four levels of measurement: –Nominal: Merely “names” the attribute, no ordering implied –Ordinal: Attributes can be rank-ordered but distances do not have any meaning –Interval: Rank-ordered + distances have meaning –Ratio: Starts from an absolute zero point such that a meaningful fraction/ratio can be constructed. Ex: Age, 20 x 2 = 40