LIS 570

1. LIS 570 Session 8.1 Making Sense of Data: Exploratory data analysis; Elaboration Model

2. Objectives • Reinforce distinction between experimental design statistics and data analysis statistics • Review exploratory data analysis methods • Understand the principles underlying the elaboration model for bivariate data analysis

3. Agenda • Review concepts: compare “experimental design” with “data analysis” • Review some earlier concepts as ways to do exploratory data analysis • Discuss the elaboration model for bivariate analysis

4. Perspective on data analysisExperiments and Other Studies Experiments • Planned • Controlled (to differing degrees) Other studies • Planned or opportunistic • Offer opportunities to extend understanding

5. Experiments Theory usually precedes design Often: objective is to test hypothesis Designed in advance: data collection, coding, analysis Sampling designed for statistical significance Statistical tests specified in advance Outcome may be “generalizable” and often provides either “support” or “non-support” for hypothesis and theory

6. Experiential Learning Cycle(Kolb, 1984) Concrete Experience Active Experimentation Reflective Observation Abstract Conceptualization

7. Analysis of Data from Other Studies Theory may be sketchy or non-existent Sampling may be non random, but data collection and coding can be specified in advance Data analysis intended to detect patterns and uncover associations Outcome may be “postulates,” “propositions,” or even “hypotheses” that can be further studied or tested

8. Exploratory Data Analysis • Histograms • Scatter plots • “Stem and leaf” • “Box and whisker”

9. “Stem & Leaf” Dataset: 39, 42, 44, 47, 48, 48, 51, 52, 53, 53, 54, 55, 55, 55, 55, 56, 56, 57, 57, 58, 58, 59, 59, 59, 59, 61, 61, 62, 63, 63, 64, 65, 65, 65, 66, 66, 66, 67, 69, 69, 71, 71, 76, 81, 84, 92 Plot: 3 | 94 | 2 4 7 8 85 | 1 2 3 3 3 4 5 5 5 55 | 6 6 7 7 8 8 8 9 9 9 96 | 1 1 2 3 3 4 5 5 56 | 6 6 6 7 9 97 | 1 1 68 | 1 49 | 2 Adapted from http://www-micro.msb.le.ac.uk/1010/DH2.html

10. “Box & Whisker” Plot Adapted from http://www-micro.msb.le.ac.uk/1010/DH2.html

11. Elaboration Elaborate: “…give more detail about” Preliminary data analysis shows (or suggests) a relationship Can anything else be said about this relationship?

12. Elaborating Relationships • Why does the relationship exist? • What is the nature of the relationship? • How general is the relationship? • Elaboration model • interpretation method • the Columbia School • Lazarsfeld method

13. Elaboration Paradigm Objective to provide a logical/ statistical technique that would allow researchers to elaborate on the nature of observed relationships

14. Elaboration Model • Replication—the relationship is replicated or repeated under different conditions • Specification—relationship appears only under certain conditions and not others • Intervening variable • Spurious relationships—an “artefact” of the data • Partial correlations

15. Specification or Replication • The original bivariate relationship is called a zero order relationship • Partial table (trivariate table) • Third variable (control or test variable) introduced • Within each subgroup of the test variable, construct a table to examine the original relationship. • Measurement of bivariate relationships in each of the partial tables (partial relationships)

16. Specification or replication Comparison with zero order relationship Specification Replication Partial/Conditional relationship Zero order relationship

17. Replication Epsilon = 12 percentage points “Do you approve or disapprove of the proposition that men and women should be treated equally in all regards”

18. Replication Epsilon = 12 percentage points Epsilon = 12 percentage points

19. Specification • the relationship between the original two variables differs for various types of people • the specific types for whom it does or does not hold • the relationship is not general but subgroup specific • statistical interaction (De Vaus) • The effect of X on Y is partly dependent on additional characteristics of the person.

20. Specification (Glock) Social Class and Church Involvement Church involvement provides an alternative form of gratification for people denied gratification in secular society People of lower social class have fewer opportunities to gain self esteem from secular society

21. Specification Social Class and Holding Office in Organisations Social class is strongly related to the likelihood that a woman has every held an office in a secular organization

22. Specification Church Involvement by Social Class and Holding Secular Office Mean church involvement for Rough indicator of gratification in secular society

23. Interpretation - Intervening Variable (Stoufler) Education and Acceptance of Being Drafted Friends Deferred Education Attitudes

24. Intervening Variable Relating education to acceptance of being drafted through the factor of having friends deferred

25. Explanation—Spurious Relationships • Spurious - not a genuine relationship • Test variable must be antecedent Strength of peace movement Likelihood of war Strength of peace movement International tensions Likelihood of war

26. Spurious relationship Number of fire trucks Size of the fire Damage done

27. Test for Spurious Relationship • Compare the initial bivariate relationship with the conditional relationship—if no relationship in the conditional table, we have explained the original relationship • Can have completely and partly spurious relationships

28. Reporting your research • The presentation of the results • A discussion and interpretation of the results, i.e., what they mean to you, and any limitations or concerns, for example ethical, validity, reliability. • Conclusions

29. Drawing conclusions • What did you ask? • What did you find? • What do you conclude? • To whom do your conclusions apply?