Chapter 2

Methods in the Study of Personality

Modified: 2022-06-23 4:01 pm

Psychologists of all kinds use different kinds of methods to research their areas. Personality psychologists use case studies, experience sampling, correlations, experiments, and multifactor studies to investigate personality. Some methods lead to more generalizability than others.

• Learning Objectives:
  • 2.1 Define case study, experience sampling, and the concept of generality
  • 2.2 Examine the process of establishing two kinds of relationships between variables
• 2.1 Gathering Information (p. 9)
  • All scientists ask questions about their respective fields
  • Personality psychologists ask those questions using particular methods
    • There are two sources: your own personal experience and other people react to the world
  • 2.1.1 Observe Yourself and Observe Others
    • Introspection is when we look inside ourselves
      • Introspection is distorted because of the special relationship between you and your memory
    • Observing others is another way of gathering data
      • We can only observe other's behavior, we cannot see inside their minds
  • 2.1.2 Depth Through Case Studies
    • Case studies come from Henry Murray's personology
    • Case studies:
      • Are rich in detail
      • Create vivid descriptions
      • Are situated in normal life and situations
  • 2.1.3 Depth from Experience Sampling
    • Experience sampling or diary studies:
      • Take place over relatively long periods
      • Ask people to respond to prompts throughout the day (using cell phones now)
      • Yield less memory distortion because of short intersample intervals
      • Produce much information
      • Called ideographic methods
  • 2.1.4 Seeking Generality by Studying Many People
    • Case studies cannot provide generalizability
    • Research must generalize
      • Done via larger and diverse samples
        • FYI: American college student samples are not enough
        • Sampling: SES, Culture, Age, and Gender help ensure generalizability
• 2.2 Establishing Relationships among Variables (p. 11)
  • Variables must have at least two values (e.g., male and female)
  • Variables may have infinite values (e.g., self-esteem)
  • Figure 2.1 (below) illustrates why research cannot just look at one level of a variable, in this case self-esteem is divided into 5 levels.
  • Note how looking at only low self esteem reveals nothing about the relationship of self esteem and GPA
  • Researchers need to examine a range of variability

Figure 2.1

• 2.2.1 Correlation between Variables
  • Correlations operationalize relationships between variables
  • Correlation values may range from +1.00 to -1.00 (see examples below)
  • Correlations near 0 indicate little or no relationship
  • Correlations DO NOT establish cause and effect relationships
  • Look at the various scatterplots below to see a variety of relationships
  • In the examples below each point represents a pair of values, one from the X axis and one from the Y axis
  • Note that the value of the correlation indicates its strength with higher values indicated stronger relationships
  • The (+) and (-) signs indicate the direction of the correlation.
    • My favorite example of a strong negative correlation is the price of a bicycle and its weight.
    • Simply put, heavy bicycles cost less and light bicycles cost more.
  • Researchers label correlations:
    • greater than +/- 0.60 as strong
    • between +/- .0.30 and 0.50 as moderately strong
    • below +/- 0.30 as weak

• 2.2.2 Two Kinds of Significance
• The word "significant" has a special meaning in psychological research
• Researchers label results as statistically significant if it exceeds a table value indicating that the results has a 1/20 chance (e.g., 5%) of being incorrect (That means that it has 95% chance of being correct)
• The word "significant" is also use to indicate results that are statistically significant and have practical or clinical importance
• 2.2.3 Causality and a Limitation of Inference
  • As noted above, correlations cannot yield cause and effect conclusions
  • One reason for that is the third variable problem
    • That third, unmeasured variable, may be the cause of the strong correlation between the two measured variables. See Fig. 25 (below)
  • In this case, the unknown third variable may be the cause for the correlation between self-esteem and GPA

• 2.2.4 Experimental Research
  • Properly conducted experiments enable researchers to determine cause and effect relationships.
  • To do so, they create an independent variable (IV)
    • The IV must have at least two levels (it may have more if desired)
    • In this example, researchers will create two levels for a hypothetical sleeping pill: Nox-Out©
    • The levels will be: dosage of Nox-Out© (the experimental group) vs no dosage (the control group)
  • They must also find a suitable dependent variable (DV)
    • The DV depends on the IV
    • In this case DVs could be: length of sleep, quality of sleep, or latency of sleep
  • They must also control extraneous variables
    • Extraneous variable are those which might affect the DV in some way
    • They might include in this case: the location of the experiment, the age of the participants, their gender, or how long it has been since the participants last slept
  • Random assignment of participants to experimental and control groups is a convenient way to ensure control provided that large enough samples are created
    • Random assignment ensures that both groups will be similar on any variable of psychological interest
  • Two Examples of Experiments
    • The first one on toothpaste is a little silly
    • The second on on Nox-Out© illustrates the failure of control
• 2.2.5 Recognizing Types of Studies
  • True experiments use random assignment of participants to groups
  • When naturally occurring groups are used that is a correlational study (sometimes called a quasi experiment)
• 2.2.6 What Kind of Research is Best
  • While experiments can yield cause and effect conclusions they may not be suited for the types of information that personality researchers seek
  • Experiments:
    • Typically are of short duration
    • Often require carefully controlled conditions
  • Correlations:
    • Can examine events over long periods
    • Can examine topics that would be unethical to experiment upon
      • Could I, for instance, finally lay to rest the nature-nurture issue regarding gender by taking children from their parents at birth and raising them in four randomly assigned groups:
        • Boys raised as boys normally are
        • Girls raised as girls normally are
        • Boys raised as girls normally are
        • Girls raised as boys normally are
      • While this experiment is designable it is not ethically acceptable (I hope you agree)
• 2.2.7 Experimental Personality Research and Multifactor Studies
  • Thus far, all of the examples have involved a single predictor variable
  • It is possible to design multifactor research as well
  • In multifactor research psychologists analyze two or more variables separately
  • That yields more and requires more attention to increased numbers of factors
  • Figure 2.7 (below) illustrates a simple two-factor study using self-esteem and experimental manipulation of a success-failure factor
  • This is a crossed design, meaning that self-esteem is a personality variable and success-failure is a manipulated experimental variable by ecause the researchers made the tasks easy vs impossible.
  • They wanted to see how participants with high or low self-esteem would respond to success or failure
  • High and low self-esteem groups then either failed or succeeded on the first task
  • The dependent variable was performance on the second task
  • Studies such as this one are called: experimental personality research when one variable is a personality variable and the other is an experimental manipulation

• 2.28 Reading Figures from Multifactor Research
  • Main Effects and Interactions
    • Main effects are independent of other factors in experimental personality research
    • Interactions occur when one group's performance differs in opposite ways from another's
    • Figure 2.8 (below) shows two possible HYPOTHETICAL interactions
    • In A, an initial failure for the low esteem group leads to poorer performance on the second test. But, the high esteem group is unaffected by initial failure
    • In B, an initial failure for the low esteem group leads to poorer performance but for the high esteem group leads to better performance

• Taking a new job is another good example of multifactor decision making. Those offered a new job must consider a number of competing factors simultaneously: salary, job location, schools, safety, climate, and many more.
• Making such decisions is complicated and may not be easy to do

• Summary (p. 19)
  • Research in Personality depends on:
    • Observations
      • Personal
      • Of others
  • Case Studies examine individuals closely
  • Generalizability is desired in research
  • Correlations provide a measure of degree of relationship between two variables
  • The experimental method can analyze cause and effect
  • Multifactor studies examine more than one variable at a time
    • When multifactor studies involve a personality variable and an experimental manipulation they are called experimental personality research
• Research in personality relies on observations of both the self and others. The desire to understand a person as an integrated whole led to case studies: in-depth examinations of specific persons.
• The desire for generalizability—conclusions that would apply to many rather than to just a few people—led to studies involving examination of many people.
• Gathering information is only the first step toward examining relationships between and among variables.
• Relationships among variables are examined in two ways, corresponding to two kinds of relationships.
• Correlational research determines the degree to which two variables tend to go together in a predictable way when measured at different levels along the dimensions.
• This technique determines two aspects of the relationship: its direction and its strength.
• The special relationship of cause and effect cannot be determined by this kind of study, however.
• A second technique, called the experimental method, is a test for cause and effect.
• In an experiment, an independent variable is manipulated, other variables are controlled (made constant), and anything that cannot be controlled is treated by random assignment.
• An effect caused by the manipulation is measured in the dependent variable.
• Experimental and correlational techniques are often combined in multifactor studies.
• When the study contains a personality variable and an experimental manipulation, it’s termed experimental personality research. Multifactor studies permit the emergence of interactions.

  KEY TERMS

• Case study: An in-depth study of one individual.
• Causality (causal relationship): A relationship such that variation in one dimension produces variation in another.
• Clinically significant: An association large enough to have some practical importance.
• Correlation: A relationship in which two variables or dimensions covary when measured repeatedly.
• Correlation coefficient: A numeric index of the degree of correlation between two variables.
• Dependent variable: The variable measured as the outcome of an experiment; the effect in a cause–effect relation.
• Descriptive statistics: Statistics used to describe or characterize some group.
• Experience sampling: Method in which people report repeatedly on their current experiences.
• Experimental control: The holding constant of variables that are not being manipulated.
• Experimental method: The method in which one variable is manipulated to test for causal influence on another variable.
• Experimental personality research: A study involving a personality factor and an experimental factor.
• Generality (generalizability): The degree to which a conclusion applies to many people.
• Idiographic: Relating to an approach that focuses on a particular person across situations.
• Independent variable: The variable manipulated in an experiment, tested as the cause in a cause–effect relation.
• Inferential statistics: Statistics used to judge whether a relationship exists between variables.
• Interaction: A finding in which the effect of one predictor variable differs depending on the level of another predictor variable.
• Main effect: A finding in which the effect of one predictor variable is independent of other variables.
• Multifactor study: A study with two (or more) predictor variables.
• Personology: The study of the whole person, as opposed to studying only one aspect of the person.
• Practical significance: An association large enough to have practical importance.
• Random assignment: The process of putting people randomly into groups of an experiment so their characteristics balance out across groups.
• Statistical significance: The likelihood of an obtained effect occurring when there is no true effect.
• Third-variable problem: The possibility that an unmeasured variable caused variations in both of two correlated variables.
• Variable: A dimension along which two or more variations exist.

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