Methods - personality 333

Page 2:

  • Personality is a construct

  • Construct: An idea about a psychological attribute that goes beyond what might be assessed through any particular method of assessment

  • Data: Observations or measurements, usually (but not always) quantified and obtained in the course of research

  • Variables: A condition in an experiment or a characteristic of an entity, person, or object that can take on different categories, levels, or values and that can be quantified

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  • Importance of being clear about variables in research

  • Conceptual definition: A description of something in terms of what it means

  • Operational definition: A description of something in terms of the operations (procedures, actions, or processes) by which it could be observed and measured

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  • S Data (Self-Report)

    • Obtained by asking individuals directly

    • Often in the form of surveys

    • Straightforward and easy to obtain

    • Face validity

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  • I Data (Informant Report)

    • Obtained by asking someone who knows the person of interest

    • Can use reworded S Data measurements

    • May come from any relevant source

    • Relevance depends on the reason why data is gathered

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  • L Data (Life Outcomes)

    • Verifiable, concrete, real-life facts that may hold psychological significance

    • Can be thought of as the "residue" of personality

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  • B Data (Behavioral Observations)

    • Obtained by observing the person's behavior

    • Inherently interpretative

    • May be hard to categorize

    • Natural vs. Laboratory B data

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  • Advantages and disadvantages of different sources of data for personality assessment

  • S Data: Self-Reports

    • Advantages: Large amount of information, access to thoughts and feelings, simple and easy

    • Disadvantages: Error reports, bias, some S data are true by definition, causal force

  • I Data: Informant Reports

    • Advantages: Large amount of information, real-world basis, common sense

    • Disadvantages: Limited behavioral information, lack of access to private experience, error, bias, causal force

  • L Data: Life Outcomes

    • Advantages: Objective and verifiable, intrinsic importance, psychological relevance

    • Disadvantages: Multi-determination

  • B Data: Behavioral Observations

    • Advantages: Wide range of contexts, appearance of objectivity

    • Disadvantages: Difficult and expensive, uncertain interpretation

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  • Not all data can be easily categorized

  • Behavioroid: A type of data where participants report what they think they would do under various circumstances

  • A piece of data may have elements of two or more types of data

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  • Reliability: The tendency of an instrument to provide the same comparative information on repeated occasions

  • Measurement error: The variation of a number around its true mean due to uncontrolled, essentially random influences

  • Improving reliability through care, standardization, measuring something important, aggregating, and using the Spearman-Brown formula

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  • Internal consistency and stability across time as measures of reliability

  • Test-Retest reliability and Inter-rater reliability

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  • Validity: The degree to which a measure actually measures what it's intended to measure

  • Must be reliable

  • Conceptual definition vs. operational definition

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  • Types of validity: Construct validity, Criterion validity, Convergent validity, Discriminant validity, Face validity

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  • Considerations for validity: Cultural differences, variation in meaning of constructs, interpretation differences, response sets, acquiescence, reverse-coded items, social desirability

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  • Reliability vs. validity metaphor using target shooting

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  • Generalizability: The degree to which a measurement or conclusion can be found under diverse circumstances

  • Threats to generalizability: Undergraduate samples, lack of ethnic and cultural diversity, gender bias, cohort effects, shows vs. no-shows and response rates

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  • Projective tests: Assessment in which individuals project from the unconscious onto ambiguous stimuli

  • Projective hypothesis: Individuals supply structure to unstructured stimuli based on their own unique patterns of conscious and unconscious needs, fears, desires, impulses, conflicts, and ways of perceiving and responding

  • Types of projective tests: Rorschach inkblot, Thematic Apperception Test

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  • Validity of projective tests is mixed

  • Weaknesses of B data

  • Projective tests still heavily used in psychotherapy settings

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  • Objective tests: Personality tests consisting of a list of questions to be answered by the participant

  • Used in many areas inside and outside of psychology

  • Need to be reliable and valid

  • Single-trait vs. omnibus tests

Page 23:

  • Different methods for developing personality assessments: Rational (Theoretical) method, Factor analytic method, Empirical method

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  • Rational method: Items directly related to what is being measured, may come from theory or participant's thoughts/experiences/views

  • Example: Woodworth's Personality Data Sheet (WPDS)

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  • Four conditions for validity of measurement in the rational method

  • Many rationally constructed personality tests fail to meet one or more criteria

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  • Factor analytic method: Statistical method for finding order amid seeming chaos

  • Identifies groupings within a list of items

Page 27:

  • How factor analysis works

  • Subjective process of labeling factors based on theoretical motivations or item contributions

Page 28: The Factor Analytic Method

  • Limitations of factor analysis:

    • Quality of information limited by quality of items

    • Factors don't always make sense

    • Difficulty and subjectivity in deciding how items are conceptually related

  • Uses of factor analysis:

    • Reduce list of traits to essential few

    • Refine personality tests

Page 29: The Empirical Method

  • Data-driven approach to test construction

  • Basic assumption: Certain kinds of people will have distinctive ways of answering questions on personality inventories

  • Steps in the empirical method:

    1. Gather lots of items

    2. Administer items to people already divided into groups

    3. Compare the answers of the different groups

  • Items may seem absurd or unrelated to personality

Page 30: Minnesota Multiphasic Personality Inventory (MMPI) Sample Items

  • Examples of items from the MMPI:

    • I like mechanic magazines

    • I have a good appetite

    • I think I would like the work of a librarian

    • My father was a good man

    • There seems to be a lump in my throat much of the time

    • My daily life is full of things that keep me interested

    • I enjoy detective or mystery stories

    • I am sure I get a raw deal from life

Page 31: The Empirical Method (continued)

  • Same information as on page 29

Page 32: MMPI Scales

  • Different scales of the MMPI:

    • Hypochondriasis

    • Depression

    • Hysteria

    • Psychopathic Deviate

    • Masculinity-Femininity

    • Paranoia

    • Psychasthenia

    • Schizophrenia

    • Hypomania

    • Social-Introversion

Page 33: The Empirical Method (continued)

  • Implications of ignoring item content/low face validity:

    • Items can seem contrary or absurd

    • Responses are difficult to fake

    • Tests are only as good as the criteria by which they are developed and/or cross-validated

  • Considered B data though it is dependent on self-report

  • Can also be used with factor analysis (and the rational approach)

Page 34: How Do We Study Personality?

  • Observing the self and others as a starting point

  • Research designs:

    • Case study

    • Correlational

    • Experimental

    • Multi-factor studies

Page 35: Case Studies

  • In-depth study of one person over a long period of observation

  • Typically includes unstructured interviews

  • Usually used for extraordinary situations

  • May undermine current thinking or initiate new models

  • Provides rich detailed information

  • May not generalize (idiographic)

Page 36: Relationships Among Variables

  • Psychologists examine how different variables relate to each other

  • Two forms of examining relationships between variables:

    • Associative (correlational)

    • Causal (experimental)

  • Statistical significance vs. practical significance

Page 37: Correlational Research

  • Correlational research establishes the relationship (not necessarily causal) between two or more variables

  • Variables are measured, not manipulated

Page 38: Correlational Research (continued)

  • Predictor variable (x) is used to predict another variable in a correlation/regression analysis

  • Criterion variable (y) is the variable being predicted by another variable in a correlation/regression analysis

Page 39: Correlational Research (continued)

  • Correlation coefficients express the strength and direction of the relationship

  • Range between -1 and +1

  • Depicted by r (e.g., r = -.35)

  • +/- expresses direction

  • Number depicts strength

Page 40: Correlation

  • Visual representation of correlation coefficients

  • Shows the strength and direction of the relationship

Page 41: Correlation Does Not Imply Causation

  • Correlational data cannot determine causation

  • Relationships may be due to:

    • Causation

    • Reverse causation

    • Bidirectional

    • Third-variable problem

Page 42: Correlational Research (continued)

  • Advantages of correlational research:

    • Establishes a relationship and can make predictions

    • Can be quick and easy

    • May be the only way to study a relationship in the real world

  • Disadvantages of correlational research:

    • Cannot determine causation

Page 43: Experimental Research

  • Experimental research involves manipulating one or more variables to test for causal influence on another variable

  • Variables are categorized as independent (IV) or dependent (DV) variables

  • Within-subjects vs. between-groups design

Page 44: Experiments Can Make Causal Claims

  • Three criteria for causality: covariation, temporal precedence, and internal validity

  • Experimental control and random assignment for between-groups experiments

Page 45: Experimental Research (continued)

  • Advantages of experimental research:

    • Controls for extraneous factors to rule out alternative explanations

    • Can make causal claims

  • Disadvantages of experimental research:

    • Confounding variables

    • May not generalize to "real-life"

    • Placebo effects

    • Experimenter/observer expectancies may bias results

Page 46: The Myth of Experimental Research as the Gold Standard

  • Experiments have limitations:

    • Not always possible

    • May not generalize beyond the study

    • Effects might not be long-lasting

    • Difficulty in determining the exact cause and effect relationship

    • Oversimplification of the relationship

Page 47: Multifactor Studies

  • Studies with two or more predictor/independent variables

  • Variables can be manipulated, measured, or a combination

  • Subject (participant) variables help examine the complexity of life

  • Experimental personality research examines the relationship between a personality factor and an experimental manipulation on a dependent variable

Page 48

Main effects: A finding where the effect of one predictor variable has an effect on the dependent variable, independent of other variables

• Interactions: A finding where the effect of one predictor variable differs depending on the level of another predictor variable