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Moving Away From Aggregate Statistics: Observation Oriented Modeling and Assessement Lisa D. Cota, MS Statistical Analyst Office of University Assessment & Testing Oklahoma State University

Moving Away From Aggregate Statistics: Observation Oriented Modeling and Assessement

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Moving Away From Aggregate Statistics: Observation Oriented Modeling and Assessement. Lisa D. Cota, MS Statistical Analyst Office of University Assessment & Testing Oklahoma State University. Why not NHST?. - PowerPoint PPT Presentation

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Page 1: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Moving Away From Aggregate Statistics: Observation Oriented Modeling and

Assessement

Lisa D. Cota, MSStatistical Analyst

Office of University Assessment & TestingOklahoma State University

Page 2: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Why not NHST?• Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49, 997–1003.

Retrieved from http://psycnet.apa.org/journals/amp/49/12/997/• Haller, H., & Krauss, S. (2002). Misinterpretations of significance: A problem students

share with their teachers. Methods of Psychological Research, 7(1), 1–20. Retrieved from http://www2.uni-jena.de/svw/metheval/lehre/0405-ws/evaluationuebung/haller.pdf

• Hoekstra, R., Morey, R. D., Rouder, J. N., & Wagenmakers, E.J. (2014). Robust misinterpretation of confidence intervals. Psychonomic Bulletin & Review. doi:10.3758/s13423-013-0572-3

• Lamiell, J. T. (2013). Statisticism in personality psychologists’ use of trait constructs: What is it? How was it contracted? Is there a cure? New Ideas in Psychology, 31(1), 65–71. doi:10.1016/j.newideapsych.2011.02.009

• Lykken, D. What’s wrong with psychology anyway? (1991). In Thinking Clearly About Psychology. University of Minnesota Press.

• Toomela, A. (2010). Quantitative methods in psychology: Inevitable and useless. Frontiers in Psychology, 1(July), 29. doi:10.3389/fpsyg.2010.00029

Page 3: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Why not NHST?

• Assessment should be understandable– NHST: Not easily understood…in fact easily

misunderstood• Oakes, 1986; Gigerenzer, 2004• Hoekstra, Morey, Rouder, & Wagonmaker, 2014

• One problem (of many) with NHST:– Variance Explained ≠ Accuracy

Page 4: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

y = 0.5x + 3, R2 = 0.663

Page 5: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

y = 0.5x + 3, R2 = 0.663

Page 6: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

y = 0.5x + 3, R2 = 0.663

Page 7: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

y = 0.5x + 3, R2 = 0.663

Page 8: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Assumptions

• Assumptions for independent samples t-test under NHST:– Null hypothesis is true– Observations are independent between and

within groups– Population variances are exactly equal– Random sampling / random assignment (???)* Continuous DV* DV has a normal population distribution

Page 9: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Observation Oriented Modeling

• No meaningless aggregates• Person-centered • No assumption-laden p-values

Page 10: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Observation Oriented Modeling: Ordinal Pattern Analysis

Page 11: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Results

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Page 18: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Randomization Test

Page 19: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Results, with chance-value

Page 20: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

VALUE Rubric Data

Page 21: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Results

Page 22: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement
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Page 24: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Significant ≠ Meaningful

Page 25: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Significant ≠ Meaningful

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Page 27: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Significant ≠ Meaningful

Page 28: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Transparency, Honesty, and Progress

Page 29: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Raw Numbers

Page 30: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Proportions

Page 31: Moving Away From Aggregate Statistics: Observation Oriented Modeling and  Assessement

Compare w. SPSS….

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SPSS Legacy Dialog, k Independent Samples

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Proportions

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Advantages of OOM

• Assumption-free• Transparent• Honest

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OOM website

• “We’ve never actually looked at the data!” …before now!

• www.idiogrid.com/OOM