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Defining and Measuring Variables. Slides Prepared by Alison L. O’Malley. Passer Chapter 4. Think of something that would not be considered a variable…. Variables: Qualitative vs. Quantitative. Qualitative Variable levels are categories – values reflect difference in kind

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## Defining and Measuring Variables

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**Defining and Measuring Variables**Slides Prepared by Alison L. O’Malley Passer Chapter 4**Think of something that**would not be considered a variable…**Variables: Qualitative vs. Quantitative**• Qualitative • Variable levels are categories – values reflect difference in kind • E.g., make of car, region of country • Quantitative • Variable levels exist on a continuum from low to high – values reflect difference in amount • E.g., number of siblings, quiz score**Variables: Discrete vs. Continuous**• Discrete • Intermediate values are impossible • E.g., # of cars owned, # of Oscars won • Continuous • Intermediate values are possible – precision limited only by our measurement tools • E.g., height (62.675... inches), weight • In practice, ultimately converted into discrete values**The nature of our variables paves the way for how we make**sense of them Which type of variable is depicted in (a)? (b)?**Independent and Dependent Variables**Identify the independent variable and dependent variable in this research question: Is aggressive behavior influenced by alcohol consumption?**Independent and Dependent Variables**• Discuss independent and dependent variables in terms of “cause” and “effect” • Note that this causal language pertains only to experimental research designs! • Generate an example of an independent variable that cannot be manipulated**Constructs**• Psychological scientists have their work cut out for them, as they tend to be interested in phenomena that are not directly observable. Love? Motivation? Creativity?**Constructs**• Constructs must be translated into something measurable • This process occurs via operationalization • Generate an operational definition for aggression Underlying Construct Measurable Variable**Moderator Variables**• A moderator variable influences the direction and/or strength of the relationship between two variables Moderator IV DV**Moderator Variables**• E.g., Social support moderates the relationship between stress and turnover • The relationship between stress and turnover (i.e., leaving one’s job) is stronger when social support is low vs. when social support is high Social Support Stress Turnover**Mediator Variables**• Mediators explain a causal relationship, shedding light on the process by which the IV influences the DV Mediator IV DV**Mediator Variables**• Oishi, Kesebir, & Diener (2011) identified perceived fairness as a mediating variable accounting for the negative relationship between income inequality and happiness • High income inequality is associated with low happiness due (in part) to low perceived fairness Perceived fairness Income inequality Happiness**Scales of Measurement**• Measurement:Assignment of numbers to aspects of objects or events according to rules • Scale of measurement impacts how you analyze data**Scales of Measurement**• Nominal • Ordinal • Interval • Ratio Least precise Most precise**Scales of Measurement**• Nominal • Group objects into categories • Variable levels differ in kind, not in degree • E.g., Political party affiliation • Ordinal • Interval • Ratio**Scales of Measurement**• Nominal • Ordinal • Values reflect rank ordering 1st place 2nd place 3rd place 4th place 1 hour 2 hours 3 hours 4 hours 5 hours 6 hours 7 hours 8 hours**Scales of Measurement**• Nominal • Ordinal • Interval • Numbers reflect actual amounts • Equal distance between intervals • 0 point is arbitrary • E.g., Temperature (in ° Celsius or Fahrenheit) • Ratio**Scales of Measurement**• Nominal • Ordinal • Interval • Ratio • Interval scales, but zero point reflects true absence of property • Scores can be compared as ratios or percents • E.g., speed, dollars**Are Our Measures Any Good?**Accuracy, Reliability, and Validity • Accuracy reflects the degree to which measure aligns with known standard • What does accuracy have to do with systematic error (bias)?**Are Our Measures Any Good?**Accuracy, Reliability, and Validity • Reliability refers to the consistency of measurement • What does reliability have to do with random measurement error?**Are Our Measures Any Good?**Accuracy, Reliability, and Validity • Several forms of reliability • Test-rest • Consistency of scores over time • Internal consistency • Consistency of a measure within itself • Assumes multiple items – do the items strongly correlate with each other?**Are Our Measures Any Good?**Accuracy, Reliability, and Validity • Validity addresses the alignment between our construct and the measurement tool we employed to gain insight into the construct • Like reliability, validity can be addressed in several ways**Are Our Measures Any Good?**Accuracy, Reliability, and Validity • Face validity • Measure appears appropriate to participants • E.g., Job applicants perceived that an interviewer asked job-relevant questions • Content validity • Measure adequately covers the domain of interest • E.g., A course exam samples from all of the content students were exposed to in and out of class**Are Our Measures Any Good?**Accuracy, Reliability, and Validity • Criterion validity • Measure predicts an outcome • E.g., Conscientiousness is a positive predictor of job performance**Are Our Measures Any Good?**Establishing Criterion Validity Jane Doe Conscientiousness (Personality Test) ______________ _______________ Jane Doe Job Performance Data ______________ _______________ Predictor John Pahn Test 1 ______________ _______________ John Pahn Test 1 ______________ _______________ Criterion John Pahn Test 1 ______________ _______________ John Pahn Performance Appraisal ____________ _____________ Valid? (Correlated?)**Are Our Measures Any Good?**• Construct validity • Measure authentically represents the construct of interest • Demonstrated in part via convergent and discriminant validity • Convergent example: Scores on new creativity test correlate with scores on established creativity measures • Discriminant example: Scores on new creativity test are not correlated with scores on an assertiveness measure • Creativity and assertiveness are different constructs!**Are Our Measures Any Good?**• Scholars may differ in terms of how they approach validity and reliability, but they converge on the following ideas: • Reliability is a necessary but insufficient condition for validity • Construct validity is the most fundamental validity**Are Our Measures Any Good?**Accuracy, Reliability, and Validity • Consider a student who takes the SAT twice, and receives a much higher score the second time. Discuss this scenario in terms of accuracy, reliability, and validity.

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