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Between and Within Subject Measures of Affect. William Revelle and Eshkol Rafaeli-Mor Northwestern University European Association of Personality Psychology Krakow, Poland, July, 2000 http://www.personality-project.org http://pmc.psych.nwu.edu.
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Between and Within Subject Measures of Affect William Revelle and Eshkol Rafaeli-Mor Northwestern University European Association of Personality Psychology Krakow, Poland, July, 2000 http://www.personality-project.org http://pmc.psych.nwu.edu
Between and Within Subject Measures of Affect • William Revelle and Eshkol Rafaeli-Mor • With the collaboration of • Kris Anderson, GAO • Erin Baehr, Northwestern University • Douglas Billings, St. Marys College • Gregory Rogers, University of Chicago • Rishi Agrawal, Northwestern University • Neera Mehta, University of Illinois, Chicago • Support from • US ARI contract MDA903-93-K-0008
Between and Within Subject Measures of Affect • Personality traits and affective states • Between versus within measures of mood and affect • Traditional measures of dimensionality, stability and variability of affect • Alternative within subject measures • Studies of the “tides of emotion” • Applications to cognitive performance
Personality traits and affective states • Personality: a musical metaphor • A tune may be recognizable even if played with different notes with a different instrument • A person is recognizable by the patterning of affective and cognitive states even though specific behavioral acts vary • Personality traits are coherent patterns of changes of states • Multi-level modeling of parameters of affect • Level – Amplitude • Phase – Coherence • Synchrony (of multiple affects)
The long and short term predictability of affect • How happy will you feel 12 years from today? • Are some people more likely to be happy than others? • How happy will you feel 12 hours from now? • Are some people more predictable over time? • How do affective rhythms allow for a better understanding of cognitive processes?
Multiple formulations of the measurement of affect • Two dimensional models • Affective Valence and Arousal (Russell et al.) • Positive and Negative Affect (Tellegen, Watson & Clark) • Energetic and Tense Arousal (Thayer) • Multidimensional models • Energetic and Tense Arousal, and Hedonic Tone (Matthews) • Hierarchical models (Watson and Tellegen)
Multiple sources of data-1 • Between subject “snap shots” <-- • Adjective check lists • Rating scales • Within subject “diary” studies • Very high frequency/continuous studies • High frequency sampling • Low frequency sampling
Between subject “snap shots” • Adjective check lists (“I feel …”) • Energetic – Tense • Sleepy – Calm • Rating scales (“I feel …”) • very happy, happy, sad, very sad (Bipolar) • not at all, somewhat, very happy (Unipolar)
Typical between subject structure • Measures • Motivational State Questionnaire (MSQ) • 68-72 Item rating (0-3) scale • Items taken from • Thayer’s Activation-Deactivation ACL • Watson and Clark’s PANAS • Diener and Larson Circumplex measures • Example Items: • Alert Sleepy Tense Calm • Lively Tired Anxious Relaxed
Typical between subject structure • Subjects • >2700 participants aggregated from > 40 studies of personality and cognition at NU over 6 years • Method • Baseline measurements taken using the MSQ (R) • Studies done from 5:30 am to 10:30 pm • (additional analyses of effects of caffeine, exercise and movies on affect-not reported here)
Typical between subject structure • Results • Factor extraction using PF and ML • Factor number determined by Very Simple Structure (VSS) • Clear 2 factor solution • Differential skew leads to suggestions of more factors • 4 cluster solution representing +/- ends of two dimensions
Multiple sources of data-2 • Between subject “snap shots” • Adjective check lists • Rating scales • Within subject “diary” studies <-- • Very high frequency/continuous studies • High frequency sampling • Low frequency sampling
Within subject diary studies-1 • Very High Frequency (continuous) measurements • Physiological assays • Cortisol • Body temperature <-- • Core body temperature collected for ≈ 2 weeks • Data taken by aggregating subjects from multiple studies conducted by Eastman and Baehr on phase shifting by light and exercise
Body Temperature as f(time of day)(Baehr, Revelle & Eastman, 2000)
Morningness/Eveningness and BT(Baehr, Revelle and Eastman, 2000)
Multiple sources of data-3 • Between subject “snap shots” • Adjective check lists • Rating scales • Within subject “diary” studies • Very high frequency/continuous studies • High frequency sampling <-- • Low frequency sampling
Within subject diary studies-2 • Measures • Check lists • Rating scales • High frequency sampling <-- • Multiple samples per day • Low frequency sampling • Once a day • Sometimes at different times
High frequency measures of affect • Measures taken every 3 hours during waking day for 6-14 days • Paper and pencil mood ratings • Short form of the MSQ -- Visual Analog Scale • Sampled every 3 hours • Portable computer (Palm) mood ratings <-- • Short form of the MSQ • Sampled every 3 hours
Traditional measures • Mean level • Energetic arousal • Tense arousal • Positive affect • Negative affect • Variability • Correlation across measures (Synchrony)
Phasic measures of affect • Fit 24 hour cosine to data • Iterative fit for best fitting cosine • Permutation test of significance of fit • Measure • Fit (coherence) • Amplitude • Phase
Affective rhythms can differ in phase (simulation - double plotted to show rhythm)
William Revelle: Should this come before the 24 hour slide Phase differences of simulated daily data
Phase and Coherence differences (simulated data -- double plotted)
Multi-level analysis of patterns of affect across time-1: Method • Within subject estimates of basic parameters • Level • Scatter (variability) • Phase • Coherence (fit) • Between subject measures of reliability • Week 1/Gap/Week 2
Multi-level analyses of affect-2: 1-2 week Test-Retest Reliability
Design: High frequency diary study of affect combined with a low frequency study of reaction time Subjects: 28 NU undergraduate volunteers Method: 1 week diary study 5 times a day Simple reaction time once a day at 5 different times using a Mac program at home Affective rhythms and cognitive performance-1
Affective rhythms and cognitive performance-2 • Low negative correlations of RT with concurrent measures of Energetic Arousal • Stronger negative correlations of RT with Cosine fitted Energetic Arousal • => Diurnal variation in RT may be fitted by immediate and patterns of arousal
Between and Within Subject Measures of Affect • Personality traits and affective states • Between versus within measures of mood and affect • Alternative within subject measures- studying the “tides of emotion” • Applications to cognitive performance • More information found on links from the personality project -- http://www.personality-project.org and the Personality-Motivation lab http://pmc.psych.nwu.edu