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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.

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Agenda

• Introduction• Validity• Reliability• Reliability & Validity• Level of measurement

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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

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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

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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

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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

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Reliability & Validity

• Recall:– Reliability is how “consistent” the measurement is– Validity is whether we are measuring the right concept

(hitting the target)

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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