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Related Concept Videos

Introduction to Personality Psychology01:29

Introduction to Personality Psychology

Personality encompasses a set of enduring traits and behavioral patterns that define how individuals think, feel, and interact, ultimately shaping their unique identities. The concept of personality has deep historical roots, deriving from the Latin term "persona," which means "mask." This term initially referred to the roles played by actors in ancient theater, signifying the different facets individuals display in various contexts.
Early Theories of Personality
The study of personality dates...
Implicit Personality Theories01:23

Implicit Personality Theories

Implicit personality theory explains how individuals make assumptions about the relationships between personality traits, behaviors, and character types. When people learn that someone possesses a particular trait, they tend to infer the presence of other related characteristics, forming a cohesive impression. This cognitive shortcut plays a crucial role in social interactions and interpersonal judgments.Central Traits and Their InfluenceSolomon Asch's seminal 1946 study highlighted the power...
The Behavioral Perspective on Personality01:19

The Behavioral Perspective on Personality

Behaviorists view personality as primarily shaped by environmental reinforcements and consequences. According to this perspective, behavior is influenced by external stimuli, and individuals adjust their actions based on rewards and punishments. Over time, learning histories — accumulated patterns of reinforcement — play a significant role in shaping personality. Behaviors that lead to positive outcomes are reinforced, while those resulting in negative outcomes are diminished. Radical...
Personality Theory by Eysenck and Eysenck01:29

Personality Theory by Eysenck and Eysenck

Hans and Sybil Eysenck developed a widely recognized theory of personality, which emphasizes the role of temperament and genetically based differences in shaping individual traits. Their theory posits that biological factors primarily determine personality and can be understood through two main dimensions: extroversion/introversion and neuroticism/stability.
In the extroversion/introversion dimension, highly extroverted people are sociable, outgoing, and easily connect with others. In contrast,...
Self-Report Tests of Personality01:22

Self-Report Tests of Personality

Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
Psychodynamic Perspectives on Personality01:27

Psychodynamic Perspectives on Personality

The psychodynamic perspective in psychology asserts that most personality functions operate unconsciously, outside of awareness. This means that the motives and emotions driving behavior often remain hidden, automatically buried in the unconscious mind as a defense mechanism to shield us from psychological distress. According to this theory, the unconscious mind contains thoughts, memories, and emotions that are too disturbing to face directly.
Psychodynamic theorists argue that unconscious...

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Related Experiment Video

Updated: Jun 5, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

Multilevel modeling: current and future applications in personality research.

Stephen G West1, Ehri Ryu, Oi-Man Kwok

  • 1Psychology Department, Arizona State University, Tempe, AZ 85287-1104, USA. sgwest@asu.edu

Journal of Personality
|January 13, 2011
PubMed
Summary
This summary is machine-generated.

Multilevel models address data dependency from grouped or repeated observations. This statistical approach enhances personality research by enabling new data analyses and insights.

Related Experiment Videos

Last Updated: Jun 5, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

Area of Science:

  • Psychology
  • Statistics

Background:

  • Traditional statistical methods struggle with dependent data from groups or repeated individual observations.
  • Data dependency can compromise the validity of standard statistical analyses.

Purpose of the Study:

  • To introduce multilevel models for handling data dependency.
  • To review the application of multilevel modeling in personality research.
  • To illustrate model specification and interpretation with an empirical example.

Main Methods:

  • Introduction to multilevel model concepts and their application.
  • Review of multilevel modeling usage in three personality journals.
  • Empirical example demonstrating model building and interpretation for Level 1 and Level 2 predictors.
  • Discussion of longitudinal data trends, centering, estimation, and model evaluation.

Main Results:

  • Multilevel modeling is concentrated in experience sampling and longitudinal growth studies within personality research.
  • The study illustrates how to specify, interpret, and evaluate multilevel models.
  • Key considerations for estimation, model comparison, and outlier detection are discussed.

Conclusions:

  • Multilevel models effectively address data dependency issues in psychological research.
  • These models offer new analytical opportunities for personality researchers, allowing for more nuanced questions and robust findings.
  • The paper covers foundational concepts and advanced developments in multilevel modeling.