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Population Sample I.V. D.V. Scale of measurement

Population Sample I.V. D.V. Scale of measurement. Scales of Measurement. Ratio Interval Ordinal Nominal. Vignette 1.

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Population Sample I.V. D.V. Scale of measurement

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  1. Population • Sample • I.V. • D.V. • Scale of measurement

  2. Scales of Measurement • Ratio • Interval • Ordinal • Nominal

  3. Vignette 1 • The Pharmco Corporation has developed a new antidepressant drug called happydaze. In order to test the effectiveness of happydaze, 42 volunteers who have been diagnosed with clinical depression agreed to take part in the experiment. Twenty-one of the volunteers were randomly chosen to receive happydaze for 6 weeks, while the other 21 volunteers received a placebo with no actual drug for 6 weeks. At the end of the 6 weeks, all participants were clinically evaluated for depression using the Torx-Maxim Method. The scores are shown here (high scores = high depression).

  4. Vignette 2 • Brave New Worlds, a pharmaceutical corporation, has just developed a new drug called Alphathink that is supposed to increase intelligence. Brave New Worlds decides to perform a clinical trial to determine if Alphathink works. Twenty volunteers from the community take a baseline intelligence test. Then the twenty volunteers take Alphathink tablets daily for six months. At the end of the six month period, the twenty volunteers again take the intelligence test.

  5. Vignette 3 • A new drug (Relaxase) has been developed to combat anxiety. A biological psychologist has been hired to test Relaxase on laboratory rats. Ten laboratory rats were initially tested (pretest) on the Elevated Plus Maze, which measures anxiety levels in rats by timing how long a rat will spend in the open-exposed arms. After all ten rats were infused with Relaxase for two weeks, the rats were again tested (posttest) on the Elevated Plus Maze. Three months after the completion of the Relaxase therapy, the rats were once again tested (3 month follow-up test) on the Elevated Plus Maze (higher score = less anxiety).

  6. Introduction to Validity True Experiment – searching for causality What effect does the I.V. have on the D.V. Correlation Design – searching for an association between variables No causation, but often very accurate predictors of results

  7. Introduction to Validity • What is validity? Are the ideas that are being investigated the same ideas that are being measured? How appropriate or sound is the methodology that is being employed?

  8. Overview of Today’s Lecture • Topics: • Statistical Validity • Construct Validity • External Validity • Internal Validity

  9. Statistical Validity • Are the results of the data due to a systematic factor (I.V.) or are the results due to chance? • Appropriate statistical test (Chi-square, t-test, ANOVA) A common threat to statistical validity is the violation of 1 or more assumptions of the test

  10. Statistical Validity • P – value and the null hypothesis • Psychology and the .05 Alpha shelf • Significance vs. Meaningfulness • The final question of statistical validity- How accurate are the results of a statistical test?

  11. Construct Validity • Research hypotheses must have a theoretical basis • Construct validity is concerned with how results support the underlying theory • Is the theory that is supported the best theoretical explanation?

  12. Construct Validity Steps to help maintain construct validity: 1.Operationally define variables with clear definitions 2.Develop hypotheses that are based upon strong, well supported theories

  13. External Validity • Generalizability of findings to other: Participants Subjects Places Times Environmental Conditions

  14. External Validity • To generalize from one sample to a population requires appropriate representation of the population • Random selection from a population of interest helps in controlling for possible confounds

  15. External Validity • Ecological Validity – Properly generalizing from the laboratory to the “real world”

  16. Internal Validity • Is the I.V. responsible for the observable changes that occur in the D.V. • Any factor (variable) that varies with the I.V. is a confound

  17. Internal Validity • Nine primary confounding variables: • Maturation (normal age change) • History (9/11) unrelated events • Testing (test-retest) • Instrumentation (alteration in calibration) • Regression to the mean

  18. Internal Validity 6. Selection (non-equivalent groups) 7. Attrition (those who drop-out are likely different from the remaining) 8. Diffusion of treatment (talk among participants) 9. Sequence effects (experience during one part of the study influencing another part of the study)

  19. Conclusion Validity concerns accuracy: Are our statistical results accurate? Are we using an accurate theoretical basis? Are we accurate in implying that our results can be generalized to a population? Are we measuring what we say that we are measuring?

  20. APA Formatting • Margins – 1 inch on all four sides (Page Layout, Margins) • Font – Times New Roman 12 pt. • Page numbering (Insert, page numbering) • Running head (insert, header) maximum of 50 characters, including letters, punctuation, and spaces • Title (do not exceed 12 words)

  21. Library • From homepage, go to Walter Stern Library • Articles & Databases • Psychology • PsycINFO &, or PubMed • We will discuss your viable topics on January 21st

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