John Rust, Michal Kosinski, David Stillwell

Modern Psychometrics

The Science of Psychological Assessment

• Broschiertes Buch

Produktbeschreibung

This popular text introduces the reader to all aspects of psychometric assessment, including its history, how to construct and administer traditional tests and the latest techniques for psychometric assessment online.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Jenny Stanford Publishing
• 4th edition
• Seitenzahl: 180
• Erscheinungstermin: 24. Dezember 2020
• Englisch
• Abmessung: 246mm x 174mm x 11mm
• Gewicht: 331g
• ISBN-13: 9781138638631
• ISBN-10: 1138638633
• Artikelnr.: 59984391

Autorenporträt

John Rust is the founder of The Psychometrics Centre at the University of Cambridge, UK. He is a Senior Member of Darwin College, UK, and an Associate Fellow of the Leverhulme Centre for the Future of Intelligence, University of Cambridge, UK. Michal Kosinski is an associate professor of organizational behavior at Stanford Graduate School of Business, USA. David Stillwell is the academic director of the Psychometrics Centre at the University of Cambridge, UK. He is also a reader in computational social science at the Cambridge Judge Business School, UK.

Inhaltsangabe

1. The history and evolution of psychometric testing
Introduction
What is psychometrics?
Psychometrics in the 21st century
History of assessment
Chinese origins
The ability to learn
The nineteenth century
Beginnings of psychometrics as a science
Intelligence testing
Eugenics and the dark decades
Psychometric testing of ability
The dark ages come to an end
An abundance of abilities
Tests of other psychological constructs
Personality
Integrity
Interests
Motivation
Values
Temperament
Attitude
Belief
Summary
2. Constructing your own psychometric questionnaire
The purpose of the questionnaire
Making a blueprint
Writing items
Alternate-choice items
Multiple-choice items
Rating-scale items
All questionnaires
Knowledge-based questionnaires
Person-based questionnaires
Designing the questionnaire
Piloting the questionnaire
Item analysis
Facility
Discrimination
Distractors
Obtaining the reliability
Cronbach's alpha
Split-half reliability
Assessing validity
Face validity
Content validity
Standardization
3. The Psychometric principles
Reliability
Test-retest reliability
Parallel-forms reliability
Split-half reliability
Interrater reliability
Internal consistency
The standard error of measurement (SEM)
Comparing test reliabilities
Restriction of range
Validity
Face validity
Content validity
Predictive validity
Concurrent validity
Construct validity
Differential validity
Standardization
Norm referencing
Criterion referencing
Equivalence
Differential item functioning
Measurement invariance
Adverse impact
Summary
4. Psychometric measurement
True-score theory
Identification of latent traits with factor analysis
Spearman's two-factor theory
Vector algebra and factor rotation
Moving into more dimensions
Multidimensional scaling
Application of factor analysis to test construction
Eigenvalues
Identifying the number of factors to extract using the Kaiser
criterion
Identifying the number of factors to extract using the Cattell scree
test
Other techniques for identifying the number of factors to extract
Factor rotation
Rotation to simple structure
Orthogonal rotation
Oblique rotation
Limitations of the classical factor-analystic approach
Criticisms of psychometric measurement theory
The Platonic true score
Psychological vs. physical true scores
Functional assessment and competency testing
Machine learning and the black box
Summary
5. Item response theory and computer adaptive testing
Introduction
Item banks
The Rasch model
Assessment of educational standards
The Birnbaum model
The evolution of modern psychometrics
Computer adaptive testing
Item equating
Polytomous IRT
An intuitive graphical description of item tesponse theory
Limitations of classical test theory
A graphical Introduction to item response theory
The logistic curve
3PL-model: difficulty parameter
3PL model: discrimination parameter
3PL model: guessing parameter
The Fisher information function
The test information function and its relationship to the standard
error of measurement
How to score an IRT test
Principles of computer adaptive testing
Summary of item response theory
Confirmatory factor analysis
6. Personality theory
Theories of personality
Psychoanalytic theory
Humanistic theory
Social learning theory
Behavioral genetics
Type and trait theories
Different approaches to personality assessment
Self-report techniques and personality profiles
Reports by others
Online digital footprints
Situational assessments
Projective measures
Observations of behavior
Task performance methods
Polygraph methods
Repertory grids
Sources and management of bias
Self-report techniques and personality profiles
Reports by others
Online digital footprints
Situational assessments
Projective measures
Observations of behavior
Task performance methods
Polygraph methods
Repertory grids
Informal methods of personality assessment
State versus trait measures
Ipsative scaling
Spurious validity and the Barnum Effect
Summary
7. Personality assessment in the workplace
Prediction of successful employment outcomes
Validation of personality questionnaires previously used in
employment
Historical antecedents to the five-factor model
Stability of the five-factor model
Cross-cultural aspects of the five-factor model
Scale independence and the role of facets
Challenges to scale construction for the five-factor model
Impression management
Acquiescence
Response bias and factor structure
Development of the five OBPI personality scales
Assessing counterproductive behavior at work
The impact of behaviorism
Prepsychological theories of integrity
Modern integrity testing
Psychiatry and the medical model
The dysfunctional tendencies
The dark triad
Assessing integrity at work
The OBPI integrity scales
Conclusion
8. Employing digital footprints in psychometrics
Introduction
Types of digital footprint
Usage logs
Language data
Mobile sensors
Images and audiovisual data
Typical applications of digital footprints in psychometrics
Replacing and complimenting traditional measures
New contexts and new constructs
Predicting future behavior
Studying human behavior
Supporting the development of traditional measures
Advantages and challenges of employing digital footprints in psychometrics
High ecological validity
Greater detail and longitude
Less control over the assessment environment
Greater speed and unobtrusiveness
Less privacy and control
No anonymity
Bias
Enrichment of existing constructs
Developing digital-footprint-based psychometric measures
Collecting digital footprints
How much data is needed?
Preparing digital footprints for analysis
Respondent-footprint matrix
Data sparsity
Reducing the dimensionality of the respondent-footprint matrix
Singular value decomposition
Latent Dirichlet allocation
Building prediction models
9. Psychometrics in the era of the intelligent machine
History of computerization in psychometrics
Computerized statistics
Computerized item banks
Computerized item generation
Automated advice and report systems
The evolution of AI in psychometrics
Expert systems
Neural networks (machine learning)
Parallel processing
Predicting with statistics and machine learning
Explainability
Psychometrics in cyberspace
What and where is cyberspace?
The medium is the message
Moral development in AI
Kohlberg's theory of moral development
Do machines have morals?
The laws of robotics
Artificial general intelligence
Conclusion

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1. The history and evolution of psychometric testing

Introduction

What is psychometrics?

Psychometrics in the 21^st century

History of assessment

Chinese origins

The ability to learn

The nineteenth century

Beginnings of psychometrics as a science

Intelligence testing

Eugenics and the dark decades

Psychometric testing of ability

The dark ages come to an end



An abundance of abilities

Tests of other psychological constructs

Personality

Integrity

Interests

Motivation

Values

Temperament

Attitude

Belief

Summary

2. Constructing your own psychometric questionnaire

The purpose of the questionnaire

Making a blueprint

Writing items

Alternate-choice items



Multiple-choice items

Rating-scale items

All questionnaires

Knowledge-based questionnaires

Person-based questionnaires

Designing the questionnaire

Piloting the questionnaire

Item analysis

Facility

Discrimination

Distractors

Obtaining the reliability

Cronbach's alpha

Split-half reliability

Assessing validity

Face validity



Content validity

Standardization

3. The Psychometric principles

Reliability

Test-retest reliability



Parallel-forms reliability

Split-half reliability

Interrater reliability

Internal consistency

The standard error of measurement (SEM)

Comparing test reliabilities

Restriction of range

Validity

Face validity



Content validity

Predictive validity

Concurrent validity

Construct validity

Differential validity

Standardization

Norm referencing



Criterion referencing

Equivalence

Differential item functioning



Measurement invariance

Adverse impact

Summary

4. Psychometric measurement

True-score theory

Identification of latent traits with factor analysis

Spearman's two-factor theory



Vector algebra and factor rotation

Moving into more dimensions

Multidimensional scaling

Application of factor analysis to test construction

Eigenvalues

Identifying the number of factors to extract using the Kaiser criterion

Identifying the number of factors to extract using the Cattell scree test

Other techniques for identifying the number of factors to extract

Factor rotation

Rotation to simple structure

Orthogonal rotation

Oblique rotation

Limitations of the classical factor-analystic approach

Criticisms of psychometric measurement theory

The Platonic true score



Psychological vs. physical true scores

Functional assessment and competency testing

Machine learning and the black box

Summary

5. Item response theory and computer adaptive testing

Introduction

Item banks

The Rasch model

Assessment of educational standards

The Birnbaum model

The evolution of modern psychometrics

Computer adaptive testing

Item equating

Polytomous IRT

An intuitive graphical description of item tesponse theory

Limitations of classical test theory

A graphical Introduction to item response theory

The logistic curve

3PL-model: difficulty parameter

3PL model: discrimination parameter

3PL model: guessing parameter

The Fisher information function

The test information function and its relationship to the standard error of measurement

How to score an IRT test

Principles of computer adaptive testing

Summary of item response theory

Confirmatory factor analysis

6. Personality theory

Theories of personality

Psychoanalytic theory

Humanistic theory

Social learning theory

Behavioral genetics

Type and trait theories

Different approaches to personality assessment

Self-report techniques and personality profiles

Reports by others

Online digital footprints

Situational assessments

Projective measures

Observations of behavior

Task performance methods

Polygraph methods

Repertory grids

Sources and management of bias

Self-report techniques and personality profiles

Reports by others

Online digital footprints

Situational assessments

Projective measures

Observations of behavior

Task performance methods

Polygraph methods

Repertory grids

Informal methods of personality assessment

State versus trait measures

Ipsative scaling

Spurious validity and the Barnum Effect

Summary

7. Personality assessment in the workplace

Prediction of successful employment outcomes

Validation of personality questionnaires previously used in employment



Historical antecedents to the five-factor model

Stability of the five-factor model

Cross-cultural aspects of the five-factor model

Scale independence and the role of facets

Challenges to scale construction for the five-factor model

Impression management

Acquiescence

Response bias and factor structure

Development of the five OBPI personality scales

Assessing counterproductive behavior at work

The impact of behaviorism



Prepsychological theories of integrity

Modern integrity testing

Psychiatry and the medical model

The dysfunctional tendencies

The dark triad

Assessing integrity at work

The OBPI integrity scales

Conclusion

8. Employing digital footprints in psychometrics

Introduction

Types of digital footprint

Usage logs

Language data

Mobile sensors

Images and audiovisual data

Typical applications of digital footprints in psychometrics

Replacing and complimenting traditional measures

New contexts and new constructs

Predicting future behavior

Studying human behavior

Supporting the development of traditional measures

Advantages and challenges of employing digital footprints in psychometrics

High ecological validity

Greater detail and longitude

Less control over the assessment environment

Greater speed and unobtrusiveness

Less privacy and control

No anonymity

Bias

Enrichment of existing constructs



Developing digital-footprint-based psychometric measures
Collecting digital footprints

How much data is needed?

Preparing digital footprints for analysis

Respondent-footprint matrix

Data sparsity

Reducing the dimensionality of the respondent-footprint matrix

Singular value decomposition

Latent Dirichlet allocation

Building prediction models

9. Psychometrics in the era of the intelligent machine

History of computerization in psychometrics

Computerized statistics

Computerized item banks

Computerized item generation

Automated advice and report systems

The evolution of AI in psychometrics

Expert systems

Neural networks (machine learning)

Parallel processing

Predicting with statistics and machine learning

Explainability

Psychometrics in cyberspace

What and where is cyberspace?

The medium is the message

Moral development in AI

Kohlberg's theory of moral development

Do machines have morals?

The laws of robotics

Artificial general intelligence

Conclusion

Rezensionen

"There is a robust science for predicting and explaining what people do in any area of life, and this remarkable book, by three leading scholars, will forever change the way you think about human behavior: a true masterpiece!" - Tomas Chamorro-Premuzic, Columbia University, USA and University College, UK.

"Measurement is the foundation of all science, and Psychology is no exception. So, with its authoritative, updated, and comprehensive coverage of psychometrics, this volume is set to become the go-to guide for any serious psychological scientist." - Sam Gosling, University of Texas, USA.

"The science of psychometrics is already changing our lives. For better or worse, it will shape our digital futures. This welcome new edition to the classic introduction to the field could hardly be more timely. " - Huw Price, University of Cambridge, UK.

"There is a robust science for predicting and explaining what people do in any area of life, and this remarkable book, by three leading scholars, will forever change the way you think about human behavior: a true masterpiece!" - Tomas Chamorro-Premuzic, Columbia University, USA and University College, UK.

"Measurement is the foundation of all science, and Psychology is no exception. So, with its authoritative, updated, and comprehensive coverage of psychometrics, this volume is set to become the go-to guide for any serious psychological scientist." - Sam Gosling, University of Texas, USA.

"The science of psychometrics is already changing our lives. For better or worse, it will shape our digital futures. This welcome new edition to the classic introduction to the field could hardly be more timely. " - Huw Price, University of Cambridge, UK.