Ted Bundy, a convicted serial killer, showed the personality characteristics of a classic sociopath.

as an attorney), as well as the common personality dispositions that are often linked with serial killers (e.g., torturing animals, bedwetting; see also the recent case of Keith Hunter Jesperson, who confessed to raping and killing eight women, in Olson, 2002). In Bundy's case, his personality and his life both ended, and he will kill no more. After two successful escapes from jail, Bundy went on to kill his final victims in Florida an was finally captured and convicted. After a decade of legal appeals were eventually exhausted, Ted Bundy was executed in Florida in 1989.

Despite the strengths of the in-depth case study method, it has some critical limitations. The most important one is that findings based on one individual cannot b generalized to other people. A case study is to the other research designs what a study of the planet Mars is to the study of planetary systems. We may find out a great dea about Mars (or a particular person), but what we find out may not be applicable t other planets (or other people). For this reason, case studies are most often used as a source of hypotheses and as a means to illustrate a principle by bringing it to life. Nonetheless, case studies of personality can be viewed as an exceptionally valuable research method, and often can be intrinsically interesting in illuminating the lives of exceptional individuals.

When to Use Experimental, Correlational, and Case Study Designs

Each of the three major types of research designs has strengths and weaknesses or , more precisely, questions that each is good at answering and questions that each is poor at answering. The experimental method is ideally suited for establishing causal relationships among variables. For example, it can be used to determine whether noisy conditions hamper the performance of introverts but not of extraverts. On the other

hand, the experimental method is poor at identifying the relationships among variables as they occur naturally in everyday life. Moreover , it may be impractical or unethical to use the experimental method for some questions. For example, if a researcher is interested in the role of nutrition in the development of intelligence, it is unethical to conduct an experiment in which half of the participants are put on a starvation diet for several years as children to see if it af fects their IQs as adults.


Think of a question about one aspect of personality. Most questions take the form of "Is variable A related to or caused by variable B?" For example, are extraverted persons better than introverts at coping with stress? Are people with high self-esteem more likely to be successful than people with low self-esteem? Do narcissistic persons have problems getting along with others? Write down your question about personality. Now think about how you might approach your question using an experiment, using the correlational method, and doing a case study. Briefly describe how you would use each of these three research designs to try to answer your question.

However, there are people who, for whatever unfortunate circumstances, have had several years of very poor nutrition. Thus, a correlational study could be done on whether level of nutrition is related to the development of intelligence. The weakness of the experimental research design is precisely the strength of the correlational design. Correlational designs are ideally suited for establishing the relationships between two or more variables that occur in everyday life, such as between height and dominance, conscientiousness and grade-point average, or anxiety and frequency of illness. But correlational designs are poor at establishing causality . They cannot determine, for example, whether frequent illnesses lead to anxiety , whether anxiety leads to illness, or whether a third variable accounts for being both frequently ill and frequently anxious.

Case studies are ideally suited for generating hypotheses that can be tested subsequently using correlational or experimental methods. Case studies can be used to identify patterns in individual psychological functioning that might be missed by the more rigorous but artificial experimental approach and the limited correlationa designs. Furthermore, case studies are wonderful in depicting the richness and complexity of human experience. Despite these strengths, case studies cannot establish causality, as can experimental methods, nor can they identify patterns of covariation across individuals as they occur in nature. Case studies also cannot be generalized to anyone beyond the single individual being studied. Together, all three designs provide complementary methods for exploring human personality .


Personality assessment and measurement start with identifying the sources of personality data—the places from which we obtain information about personality . The four major sources of personality data are self-report (S-data), observer report (O-data), laboratory tests (T -data), and life history outcomes (L-data). Each of these data sources has strengths and weaknesses. In self-report, for example, participants might fake or lie. Observers in the O-data mode may lack access to the relevant information. Laboratory tests may be inadequate for identifying patterns that occur naturally in everyday life. Each source of personality data is extremely valuable, however , and each provides information not attainable through the other sources. Furthermore, new measurement techniques continue to be invented and explored; a recent example is fMRI, or functional magnetic resonance imaging, which detects locations and patterns of brain activity when individuals perform particular tasks.

Once sources of data have been selected for measuring personality , the researcher then subjects them to tests to evaluate their quality . Personality measures, ideally, should be reliable in the sense of attaining the same scores through repeated measurement. They should be valid, measuring what they are supposed to measure. And researchers should establish how generalizable their measures are—determining the people, settings, and cultures to which the measure is most applicable. Scales applicable only to college students in the United States, for example, are less generalizable than scales applicable to people of dif fering ages, economic brackets, ethnic groups, and cultures.

The next step in personality research involves selecting a particular research design within which to use the measures. There are three basic types of research designs. The first, the experimental research design, which involves controlling o manipulating the variables of interest, is best suited to determining causality between two variables. The second, correlational research design, is best for identifying relationships between naturally occurring variables but is poorly suited to determining causality. The third is the case study method, which is well suited to generating new hypotheses about personality and to understanding single individuals.

Perhaps the most important principle of personality assessment and measurement is that the decisions about data source and research design depend heavily on the purpose of the investigation. There are no perfect methods; there are no perfect designs. But there are data sources and methods that are better suited for some purposes than for others. Thus, as we examine the theories and research findings in thi book, bear in mind that dif ferent investigators use dif ferent data sources and dif fer-ent research designs because they have different purposes in conducting their research.


Self-Report Data (S-Data) 26 Structured versus Unstructured 26 Likert Rating Scale 28 Experience Sampling 29 Observer-Report Data (O-Data) 30 Inter-Rater Reliability 30 Multiple Social Personalities 31 Naturalistic Observation 31 Test Data (T-Data) 32 Functional Magnetic Resonance

Imaging (fMRI) 36 Projective Techniques 36

Life-Outcome Data (L-Data) 38 Reliability 41 Repeated Measurement 41 Validity 42 Face Validity 42 Predictive Validity 42 Criterion Validity 42 Convergent Validity 42 Discriminant Validity 42 Construct Validity 43 Theoretical Constructs 43 Generalizability 43

Experimental Methods 44 Manipulation 44 Random Assignment 44 Counterbalancing 44 Statistically Significan 46 Correlational Method 47 Correlation Coefficien 47 Directionality Problem 51 Third Variable Problem 51 Case Study Method 51


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