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Related Concept Videos

Measures of Intelligence01:29

Measures of Intelligence

Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this; it...
Strategies of Self-Presentation III: Self-Monitoring01:24

Strategies of Self-Presentation III: Self-Monitoring

Self-monitoring is a central construct in understanding individual differences in self-presentation strategies across social contexts. It refers to how individuals observe, regulate, and control their expressive behavior and self-presentation following situational cues. Self-monitoring reflects a person's sensitivity to social appropriateness and willingness to adapt behavior to fit varying interpersonal demands.High vs. Low Self-Monitoring IndividualsIndividuals high in self-monitoring are...
Central Tendency: Analysis01:10

Central Tendency: Analysis

Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
Social Foundations of Self II: The Generalized Other01:20

Social Foundations of Self II: The Generalized Other

According to George Herbert Mead, as children progress beyond the game stage, they develop a more comprehensive understanding of societal rules and norms. This cognitive and social development enables them to internalize the expectations of the broader community, refining their ability to regulate behavior.Consistent participation in organized activities is crucial in helping children recognize that their actions are not isolated but contribute to a more significant, interconnected group effort.
Nominal Level of Measurement00:56

Nominal Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal scale is...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
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Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

Implicit measures: A normative analysis and review.

Jan De Houwer1, Sarah Teige-Mocigemba2, Adriaan Spruyt1

  • 1Department of Psychology, Ghent University.

Psychological Bulletin
|April 22, 2009
PubMed
Summary
This summary is machine-generated.

Implicit measures are outcomes automatically caused by psychological attributes. Establishing a measure as implicit requires examining causality, process nature, and automaticity for research organization.

Related Experiment Videos

Last Updated: Jun 23, 2026

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

Area of Science:

  • Psychology
  • Psychological Measurement
  • Cognitive Science

Background:

  • Implicit measures assess psychological attributes through automatic processes.
  • Previous research lacks a unified framework for evaluating implicit measures.
  • Implicit Association Tests (IAT) and affective priming tasks are popular but require clear criteria.

Purpose of the Study:

  • To define implicit measures based on their causal properties.
  • To propose a normative framework for evaluating implicit measures.
  • To organize and guide future research on implicit measurement.

Main Methods:

  • Conceptual analysis of measurement outcomes.
  • Examination of causal pathways from psychological attributes to outcomes.
  • Review of existing implicit measures using the proposed framework.

Main Results:

  • Implicit measures are defined by automatic causal links to psychological attributes.
  • A heuristic framework is presented to evaluate implicit measures.
  • The framework was applied to Implicit Association Tests and affective priming tasks.

Conclusions:

  • The proposed framework provides criteria for identifying and validating implicit measures.
  • This framework aids in organizing past research and directing future investigations.
  • Clear criteria enhance the reliability and validity of psychological attribute measurement.