Download ppt - PSY 239 401 CHAPTER 3 SLIDES

© 2013 W. W. Norton & Company, Inc.

The Personality PuzzleSixth Edition

by David C. Funder

Chapter 3: Personality Psychology as Science:

Research Methods

Slides created by:Tera D. LetzringIdaho State University 1

Objectives

• Discuss research methods that are particularly important to personality psychology

• Discuss the difference between scientific education and technical training

• Discuss aspects of data quality• Discuss common research designs• Discuss some statistical issues• Discuss research ethics

2© 2013 W. W. Norton & Company, Inc.

Psychology’s Emphasis on Methods

• Psychologists sometimes seem to know more about research methods than about the mind and behavior.

• Goal: improving hypotheses• Question everything, be skeptical, think

analytically.


Scientific Education and Technical Training

• Technical training• Scientific education

– Question what is already “known”– Learning to explore the unknown– Research: the exploration of the unknown


Quality of Data: Reliability

• Definition• Measurement error

– Also called error variance– The cumulative effect of extraneous influences

• States versus traits


Quality of Data: Factors that Undermine Reliability

• Low precision of measurement• The state of the participant• The state of the experimenter• The environment


Quality of Data: Enhancing Reliability

• Be careful• Use a standardized procedure or protocol • Measure something that is important and

engages participants


Quality of Data: Enhancing Reliability

• Aggregation – Allow random influences to cancel each other out– Especially important for predicting behavior– Spearman-Brown formula


Quality of Data: Validity

• Definition• A “slippery” concept

– Reliability is necessary but not sufficient for validity.

– Invokes the idea of “ultimate truth”


Quality of Data: Validity

• Difficulty of measuring a construct– Assessing personality is similar to testing a theory.

• Construct validation– Gather as many measurements as possible.– Look for the ones that hang together.


Quality of Data: Generalizability

• The distinction between reliability and validity is regarded as “fuzzy” by some.

• Definition



• Generalizability over participants– Gender bias: Women are more likely to volunteer

and show up.– Shows versus no-shows– Cohort effects: the tendency of a group of people

living at a particular time to be different in some way from those who lived earlier or later

– Ethnic and cultural diversity



• The burden of proof– Avoid simplistic generalizations to members of

other cultures and people in different times (including differences).

– Those who question the generalizability of a study should propose when, how, and why it is not generalizable.


Research Design: Case Method

• Definition• Can yield explanations of particular events,

general lessons, and scientific principles• Case studies of ourselves


Research Design: Case Method

• Advantages– Describes the whole phenomenon– Source for ideas– Sometimes necessary for understanding an

individual

• Disadvantages– No control– Findings must be confirmed by other cases, which

is not usually possible.15


Research Design: Experimental Method

• Definition: a research technique that establishes the causal relationship between an independent variable (x) and a dependent variable (y) by randomly assigning participants to experimental groups characterized by differing levels of x, and measuring the average behavior y that results in each group



• Test differences between groups with statistical tests to determine if the difference is larger than would be expected by chance



18

Leaders (high

power)Measure

interpersonal

sensitivityLeaders’ assistants

(low power)

Rank list of items

needed to survive in a lifeboat on the open

sea



19

F (1, 72) = 4.91, p = .03


Research Design: Correlational Method

• Definition• Scatter plot• Correlation coefficient


Research Design: Correlational Study

21

Measure power

Determine the

relationship

Measure interperson

al sensitivity

r = .25


Research Design: Comparing the Experimental and Correlational

Methods• Both attempt to assess the relationship

between two variables.• The statistics (with two groups) are

interchangeable.• The experimental method manipulates the

presumed causal variable, and the correlational method measures it.



Methods

• Only experiments can assess causality.– Correlational studies: unknown direction of cause;

third-variable problem



Methods• Complications with experiments

– Uncertainty about what was really manipulated • Third-variable problem

– Can create unlikely or impossible levels of a variable

– Often require deception– Not always possible

• Experiments are not always better.24


Research Design: Representative Design

• Frequent concern: representativeness of participants

• Less frequent, but important, concerns– Representativeness across stimuli– Representativeness across responses


Research Design: Representative Design

• Solution: use a representative design– Seldom done because it is expensive and time-

consuming


Thinking About Representativeness

• How is the psychology of today’s college students different from that of their parents? Would the conclusions of research done with college students apply to their parents? What areas are most likely to be different?


Thinking About Representativeness

• Is research done with the predominantly white college students in Western cultures also relevant to members of ethnic minorities or to people who live in other cultures? In what areas would you expect to find the most differences?


Significance Testing

• Statistical significance: a result that would only occur by chance less than 5% of the time

• p-level: probability level of obtaining a result from a statistical test if there really is no difference between groups or no relationship between variables

• Null-hypothesis significance testing (NHST)


Significance Testing: Problems with NHST

• The logic is difficult to describe (and understand).

• “Significant” does not necessarily mean strong or important.

• The criterion for significance is an arbitrary rule of thumb.

• Chances of significance vary with sample size.


Significance Testing: Problems with NHST

• Nonsignificant results are often interpreted as “no result.”

• Only provides information about the probability of one type of error– Type I error vs. Type II error

• Cannot really tell you if a result is important


Correlations and Effect Sizes

• Effect size definition• More meaningful than a significance (p) level• Correlation coefficient

– Can be used for correlational and experimental studies

• Between -1 and +1– 0 = no relationship

• Positive and negative correlations


Correlations and Effect Sizes

• Use for prediction• Interpreting correlations

– Look at the actual size– r2 = percent of variance explained; “a terrible way

to evaluate effect size” (p. 92)– Binomial Effect Size Display (BESD)


BESD

Lived DiedDrug 50 50 100No drug 50 50 100

100 100 200

34

r = .00


BESD

Lived Died

Drug 50 + (r*100)/2 = 65

50 - (r*100)/2 = 35 100

No drug 50 - (r*100)/2 = 35

50 + (r*100)/2 = 65 100

100 100 200

35

r = .30


BESD

High I.S. Low I.S.High power 62.5 37.5 100

Low power 37.5 62.5 100

100 100 200

36

r = .25

If you are worried about being interpersonally sensitive, do you want to have high power?


Thinking About Statistical Issues

• Let’s say we find that you score 4 points higher on a “conscientiousness” test than does another person. Alternatively, imagine that women score 4 points higher on the same test, on average, than men do. In either case, is this difference important? What else would we have to know to be able to answer this question?


Research Ethics

• The uses of psychological research– Make sure it is not harmful, or at least that the

potential harm does not outweigh the potential good.

• Truthfulness– Avoid plagiarism and fabrication of data.


Research Ethics: Deception

• Definition• Purpose: usually to make the research realistic• APA guidelines• Review by the Institutional Review Board (IRB)

or Human Subjects Committee (HSC)



• Arguments in favor of deception– Informed consent– It usually does no harm.– Certain topics cannot be investigated without

deception.



• Arguments against deception– Informed consent for deception is not possible.– When does the deception stop?– Harms credibility of psychology– Alternative: Investigate topics in the real world.

• What do you think about deception? Is it justified?


Clicker Question #1

In order to say that one variable caused another, a researcher musta)calculate the correlation between the variables. b) conduct an experiment.c) construct a BESD.d) use deception.


Clicker Question #2

In order for data to have a high degree of validitya)they must also have a high degree of reliability.b) they must come from an experiment.c) they must have low generalizability.d)one must know the ultimate truth about the construct being assessed.


Clicker Question #3The case method should be used whena)the researcher is especially concerned that the results have high generalizability.b)the researcher wants to establish the cause of a particular behavior.c)the researcher wants to have lots of control.d)there is an individual that the researcher wants to understand as fully as possible.
