Discuss aspects of data quality: reliability, validity, and generalizability Activity 3-1: What Kind of Thing is Personality?
Goal: improving hypotheses (not finding truth)
Technical training: conveying what is already known about a subject so that the knowledge can be applied Scientific education: teaching what is known and how to find out what is not yet known
Definition: the tendency of a measurement instrument to provide the same comparative information on repeated occasions; getting the same result more than once Measurement error: the cumulative effect of extraneous influences on a test score States vs. traits: differ in expected level of stability, in terms of what are considered extraneous influences or sources of measurement error; with traits – can you get the same result more than once? State vs. trait anxiety: Is the current situation (e.g., party, employment interview) an extraneous influence? How much stability do you expect? How much individual variation do you expect? (most people will be anxious at an interview, few at a party)
Precision: Make measurements as exact as possible; data should be correctly recorded, scored, and entered into a database. State of participant: may not depend on the study (illness, affect, distraction, fatigue, etc.) State of experimenter: may not treat all participants the same; participants may respond differently to aspects of the experimenter (gender, age, attractiveness) The environment: temperature of the room, the weather, noise in the building Activity 3-3: Interruption Olympics: Bill O’Reilly Versus Jon Stewart
Be careful: double-check measurements, check data entry, check accuracy of scoring Use a standardized procedure or protocol: adequate training of research assistants and monitoring to ensure procedures are followed Measure something important: Do you care about the health care debate? If you do, then your opinion will be more easy to measure reliably than that of someone who doesn’t care, whose opinion is more likely to be influenced by extraneous factors.
Aggregation: especially important when measurements contain a lot of error Especially important for predicting behavior: because single behaviors are influenced by many factors other than personality. What influences whether you make your bed in the morning? (lots of things, but over time, conscientious people will make their beds more often) Spearman-Brown formula: a mathematical formula that predicts the degree to which the reliability of a test can be improved by adding more items Activity 3-2: Why So Many Observations of the Same Thing?
Definition: degree to which a measurement actually reflects what one thinks or hopes it does Ultimate truth: It’s difficult, or impossible, to know what constructs (intelligence, honesty) really are, so it’s difficult to know if they are measured validly.
Construct definition: an idea about a psychological attribute that goes beyond what might be assessed through any particular method of measurement Construct validation: the strategy of establishing the validity of a measure by comparing it to a wide range of other measures Cronbach & Meehl article from the reader: Construct Validation in Psychological Tests
Fuzzy distinction: How much can a test be changed before it becomes a different test and assessments of reliability become assessments of validity? Definition: the degree to which a measurement or result of an experiment applies to other tests, situations, or people
Gender bias: Much early research (pre-1970s) only used male participants. Are women importantly different from men, which is why they are more likely to volunteer and show up? Are the men who volunteer and show up importantly different from other men? Shows vs. no-shows: There’s a problem if people in these groups are systematically different. What if you are trying to study the effects of punctuality but can only use participants who show up within 5 minutes of the start of the experiment? Cohort effect definition: 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 How does growing up with the current technology (Internet, cell phones, iPods) influence people differently from people who grew up without it? How does growing up during a time of war differ from growing up during a time of peace? Ethnic and cultural diversity: Most research is with white middle-class college students.
Ongoing example: relationship between power and interpersonal sensitivity (Schmid Mast, Jonas, & Hall, 2009) Definition: closely studying a particular event or person of interest in order to find out as much as possible Case studies of ourselves: might help us understand others better Case method example: observe that someone in a high-power position has a high level of sensitivity
No control: impossible to determine which facts and variables are crucial or incidental to understanding the person
Activity 3-4: Experimental and Correlational Studies
Measure of interpersonal sensitivity: inferences of thoughts and feelings of a videotaped interaction (Ickes paradigm)
Definition: a research technique that establishes the relationship between two variables by measuring both variables in a sample of participants Scatter plot: chart on which each point represents an individual’s scores on two variables Correlation coefficient: reflects the strength and the direction of the relationship
Statistics are interchangeable: t can be converted to r.
Uncertainty about what was really manipulated: Manipulation may affect a variable other than the one intended (competence instead of power; but this was checked and did not differ between high- and low-power groups). Third-variable problem: Manipulation may have affected an unintended variable, and this could affect both variables of interest (people who are more confident may feel more powerful and also have higher interpersonal sensitivity). Can create unlikely or impossible levels of a variable: results in exaggerated group differences (if one person has all of the power and the other has none); correlational studies measure natural levels Not always possible: especially true for personality, so experiments are rarely used by personality psychologists
Representativeness across stimuli: Schmid Mast, et al. manipulated power in more than one way (also with a word completion priming task—leadership vs. service, writing about a time when the person had high or low power) Representativeness across responses: Schmid Mast, et al. measured IS in more than one way; also with the Diagnostic Analysis of Nonverbal Sensitivity (DANVA) —decoding of emotional facial expressions—and Profile of Nonverbal Sensitivity (PONS) , decoding of nonverbal cues
Representative design: sampling across the domains to which you wish to generalize
I left the definitions on the slides because these are confusing. NHST: the traditional method of statistical data analysis
Chances of significance vary with sample size: Nature hasn’t changed, just the conclusion about nature has changed.
Chances of significance vary with sample size: Nature hasn’t changed, just the conclusion about nature has changed. Type I error: deciding that one variable has an effect on or a relationship to another variable, when really it does not; crying wolf Type II error: deciding that one variable does not have an effect on or a relationship to another variable, when really it does
Effect size: an index of the strength of the relationship between the variables Correlation coefficient: the most commonly used measure of effect size Positive correlation = as one variable goes up, so does the other Negative correlation = as one variable goes up, the other goes down
.25 squared = .0625, so power explained 6.25% of the variance in interpersonal sensitivity Binomial Effect Size Display (BESD): one method for displaying and understanding more clearly the magnitude of an effect reported as a correlation
Rosenthal & Rubin article from the reader: A Simple, General-Purpose Display of Magnitude of Experimental Effects
I.S. = interpersonal sensitivity
Avoid plagiarism and fabrication of data, which undermine the foundation of science.
Definition: telling research participants something that is not true APA guidelines: “Psychologists strive to benefit those with whom they work and take care to do no harm. . . . Psychologists respect the dignity and worth of all people, and the rights of individuals to privacy, confidentiality, and self-determination.” (http://www.apa.org/ethics/code/index.aspx)
Alternative is to investigate topics in the real world that cannot be manipulated in the lab (but this will only be correlational)