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Understanding Measurement and Reliability in Research: Key Concepts and Techniques

This comprehensive recap explores essential concepts in measurement and reliability, including operationalization, validity, and various methods for assessing reliability such as test-retest, alternate forms, and split-halves. It discusses correlation coefficients and Cronbach's Alpha as measures of association and reliability of scales. Additionally, it highlights challenges to reliability and different levels of measurement (nominal, ordinal, interval, ratio). The document also covers scale construction using techniques like Likert and Guttman scales and the Semantic Differential approach, providing a thorough understanding of these fundamental research principles.

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Understanding Measurement and Reliability in Research: Key Concepts and Techniques

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Presentation Transcript

  1. More on Measurement

  2. Recap • Measurement • Operationalization • Validity

  3. Reliability • The extent to which a test, experiment, scale, etc. give the same results from one time to the next. • Test retest method • Alternate form • Split Halves • Interitem Association

  4. Measuring Reliability • Correlation matrix • Correlation • Measure of Association • Ranges from -1 to +1 • -1 is perfect negative relationship • 1 is perfect positive • 0 is absolutely no relationship • Cronbach’s Alpha (α) • Measures association of all items with scale • Ranges from 0-1 • Good Scales are >.6

  5. Challenges to Reliability • Changes in method of measurement over time • Extraneous factors • Forget to account for reverse coded items • Items really measure different things

  6. Level of Measurement • Nominal • Ordinal • Interval • Ratio

  7. Combining Items • It is often preferable to combine scores • Items may all represent same thing • Easier to deal with • Downside- • losing some information • Need similar items (reliability) • Need to cover relevant dimensions (construct validity)

  8. Indexes • Sum up items related to each other • Use sum as new number • Problem- Treats all items as equally important • Problem- often haphazard

  9. Scales • More systematic in choice of items • Likert Scale • Begin with agreement/Disagreement questions • Sum • Find items that differentiate highs from lows • Based on results from data, not researcher • Problems • Does not weight for importance • Not sure if all dimensions are covered • Cannot know what set of responses gives score

  10. Guttman Scale • Also determined by data • Start with easy and hard items • Look to see if they form patterns • Example- Political Participation • Voting • Button • Bumper Sticker • Yard Sign • Donating • Volunteering • We would expect people who do the harder activities to have done the easier ones as well. • Statistical Test to see how well Guttman Scaling applies

  11. Semantic Differential • More a type of question than a scaling technique • Ask respondent pairs of words (e.g. honest/dishonest) and have them rate item somewhere between two. • Can ask for multiple traits • Problem- confusing way to ask question

  12. An Example- The RWA Scale • Right Wing Authoritarianism • Measure of obedience, traditionalism, hostility towards outgroups • Conventionalism, Authoritarian Aggression, Authoritarian Submission • 34 items • Sum • Check reliability (high)

  13. Review

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