Chapter #2: Data and Assessment

Personality Data and Assessment

Research

exploration of the unknown that requires a gathering of data

Technical Training

teaching us how to use preexisting knowledge; scientific training teaches how to explore

Funder’s Second Law

there are no perfect indicators of personality; there are only clues, and clues are always ambiguous

Funder’s Third Law

something beats nothing, two times out of three

High Face Validity

degree to which an assessment instrument appears to measure what it is intended to measure

Self Efficacy

what you think you are capable of and the kind of person you want to be

Self-Verification

people work to convince others to treat them in manners confirming of their self-conceptions

Fish-and-Water Effect

people do not notice their most obvious characteristics because they are always that way

I-Data

judgements via information from people like acquaintances, coworkers, or clinical psychologists

L-Data

verifiable, concrete, real-life facts that hold psychological significance; legal records, bank statements, medical files, and the internet

B-Data

observation of daily life or in a lab

Natural B Data

based on real life; electronically activated recorder, wearable cameras, social media, diary, etc

Ambulatory Assessment

using computer-assisted methods to assess behavior, thoughts, and feeling during normal daily activities

Laboratory B Data

Observing behavior in the laboratory; observable data

Behavioroid

participants report what they think they would do; mix of S and B-Data

Omnibus Inventories

measure wide range of traits

Roeschach Inkblot Test

 thoughts revealed by inkblots are not always deep, hidden, or mysterious

Draw-A-Person Test

interpreted based on what kind of person is drawn, exaggerated or omitted body parts

Thematic Apperception Test (TAT)

tell stories about drawings of people and ambiguous events; used to assess motivational states

Rational Method

write items that seem direct. Obviously, and rationally related to what is supposed to be measured

Face Validity

relational tests seek to measure exactly what they seem to be measuring, in their “face”

Factor Analysis

a statistical technique that identifies groups of things that seem to have something in common

Empirical Method

identify items based on how people in pre-identified groups respond

Cross-Validation

determine whether the test can predict behavior, diagnosis, or category membership in a new sample