Psychology 598 Research Methods

1. Psychology 598 Research Methods Carolyn R. Fallahi, Ph. D. Class #1 and 2

2. Case Study • The study of one subject. • Discuss Freud example.

3. Single-Case and Small-N research designs • Hermann Ebbinghaus example. • Single-case designs.

4. The Single case design • A-B-A design • A phase = baseline or pretreatment period • B phase = the introduction of the independent variable.

5. Single case designs • A-B design, the DV measured repeatedly throughout the pretreatment and treatment phases of the study. • In the A-B-A design, the treatment is withdrawn at the end, and the behavior is measured.

6. Single case designs • A-B-BC-B design, B and C refer to 2 therapeutic conditions.

7. Single Case Designs • A-B-A-B design. • 2 occasions (B to A and then A to B) for demonstrating the positive effects for the treatment variable.

8. Correlational versus Causal Research • Correlational Research: associational research • Not causation • Causal – comparative research

9. Survey Research • The enumerative survey • Purpose: to count (enumerate) a representative sample and then make inferences about the frequencies of occurrence in the population as a whole.

10. The Interview • involves having the researcher ask questions directly of the subjects.

11. Interview • Open-ended versus structured interviews • Open-ended participants can expand on their answers, to express feelings, motives, or behavior quite spontaneously. • “Tell me in your own words how you felt when ________?” • critical incident technique.

12. Interview • “Think about the last time you saw your mother drink herself under the table. What thoughts were associated with that incident?” • Tell me exactly what you did to deal with this situation? • In contrast to open-ended questions, structure (closed) questions are those with a clear cut response option. For example... There are often many reasons why a child does not do well in school. Motivation can sometimes be an issue. Of the following statements, please indicate which applies to your child.

13. Interview • 1. tries very very hard • 2. Tries somewhat more than the average student • 3. tries about like the average student • 4. tries somewhat less than the average student • 5. doesn’t try at all.

14. Qualitative research • Qualitative research: using words to describe. For example, how do counselors specializing in substance abuse deal with a defensive patient?

15. Quantitative Research / Ethnographic study • Quantitative Research: How well, how much, numbers. • Ethnographic study • Ethnographic record

16. Historical Research • Historical research • Biography • Phenomenology – research that focuses on particular issue.

17. Historical research / Action Research • We are trying to look at a historical incident and see the effects on people and variables. • Action Research: change conditions within a particular situation. We are not caring about generalizing to other situations.

18. Meta-analysis • Look at all studies within a topic and statistically analyze the results across the studies. • Example: Rosenthal study

19. Conducting Research • Problem Statement • Hypothesis • Operational definition versus constitutive definition • Constitutive definition – is basically a dictionary definition. • You could clarify the hypothesis by example. • Operational definition

20. Conducting Research • Variables • Literature Review • Sample/population • Instruments • Procedure • Results • Conclusion/Discussion

21. Variables • Variable: a noun that stands for a variation within a class of objects • For example: gender, motivation • Example: reinforcement: 3 types: verbal praise, money, points on examination. • Quantitative Variables: On a continuum, example weight and height. • Categorical variables: DK vary in degree or amount, but are qualitatively different. For example, gender, religious preference.

22. Variables • IV • A True study focuses on the question: “How things are and how they got to be that way?” • DV: refers to the status of the effect of outcome in which the research is interested. • Example: Jogging makes you feel better. • The IV would be jogging status (jogging or not jogging) and the DV would be feeling status (feeling better or not feeling better).

23. Variables • Extraneous variables or control variables • IVs that have not been controlled

24. Variables • Another example: new medication … Schizerall … design the study with them and talk about potential extraneous variables.

25. Hypotheses • Two types: operational and theoretical

26. The Null hypothesis in significance testing • The lingo used in an experiment • Ho (null hypothesis) • H1 or Ha • The two hypotheses must be mutually exclusive of each other.

27. Ethics • Talk about Milgram study and Zimbardo’s study. • ApA Ethics • The use of deception • Debriefing • Consent forms • Confidentiality • Regulation of research – IRB form – hand out.

28. Review of the Literature • References • Primary versus secondary sources • Search terms • Descriptors • Professional journals – peer edited

29. Sampling • Before we implement a research design, there are a few more issues to discuss. • One huge issue is that of sampling. • Population • Target population • Sample • Random sampling – Table of random numbers

30. Different types of random sampling • Systematic selection: here we have sampling units in sequences separated on lists by the interval of selection.

31. Stratified random sampling • A separate sample is randomly selected within each homogeneous stratum (or layer) of the population.

32. Area Probability Sampling / or cluster random sampling • This is a type of stratification sampling procedure. • In this case the population is divided into selected units that have the same probability of being chosen as the unselected units in a population cluster.

33. Two-stage random sampling • Combine cluster random sampling with individual random sampling • For example… select 25 classes / 100 randomly selected. • Then randomly select 4 students out of each class.

34. Nonrandom sampling • Convenience sampling • Purposive sampling

35. Generalizability from a sample • Population generalizability: the degree to which a sample represents the population of interest. • Representative sample • When random sampling is not feasible

36. Instrumentation • Data • Instrumentation: the design of the research and procedures and conditions under which a design is administered. • Instruments used within the research design • Must have validity – measures what they are suppose to measure • Reliability – give the instrument multiple times – consistent results.

37. Buros Mental Measurements Yearbook / Subject completed Instruments • Investigation of a previously researched instrument • Subject completed instruments: • Self-checklists (e.g. go into a counseling office and check of current symptoms) • Attitude scales • Often given in likert scale design – e.g. 1-5, 1-7.

38. Types of tests • Personality Tests • MMPI2/MMPIA – true/false format • Projective tests, e.g. TAT, Incomplete sentences blank, Rorschach • Achievement Tests • Woodcock Johnson (based on grade level) • Aptitude Tests • Measures your ability to perform a task

39. Types of Scores • Raw scores • Derived scores – derived from a raw score and used in a more standardized format • E.g. IQ tests – take the raw score and convert numbers to a standardized score based on the average of 100 IQ. Draw normal curve. • Age and grade-level equivalents – child compared to the age/grade level of the typical level of performance, e.g. Woodcock Johnson

40. Norm-referenced versus criterion-referenced instruments • Norm group – the group used to determine a derived score. • For example … have a depression inventory. Give the inventory to a norm group of clinically depressed individuals. • Compare the items that clinically depressed patients respond to with that of the subject. • Called a normed-referenced instrument.

41. Criterion referenced instrument • There is a specific criterion for each person to achieve. • The criterion for mastery or passing is fairly high. • Example … Sylvan learning center …

42. Measurement Scales • Nominal scale: Assign a number to different categories. • E.g. 1=women; 2=men • Ordinal Scale: data ordered in some way, e.g. rank order students from highest grade to lowest. • Interval scale: same as ordinal, but distances between points are equal, e.g. temperature distances between 0-10; 10-20 is the same. • Ratio scale: an interval scale with a true zero point, e.g. scale measurements like height. Zero=the absence of height.