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Related Concept Videos

Surveys02:16

Surveys

14.8K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

216
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
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Regression Toward the Mean01:52

Regression Toward the Mean

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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

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People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about...
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Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

2.5K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.5K
Reliability and Validity01:29

Reliability and Validity

12.8K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Related Experiment Video

Updated: Jul 16, 2025

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
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An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

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Assessing the self-reported honesty threshold in adolescent epidemiological research: comparing supervised machine

Janaka V Kosgolla1, Douglas C Smith2, Shahana Begum2

  • 1School of Social Work, University of Illinois Urbana-Champaign, 1010 W. Nevada St, Urbana, IL, 61801, USA. janakak2@illinois.edu.

BMC Medical Research Methodology
|September 22, 2023
PubMed
Summary

This study validates a self-report honesty item for adolescent substance use surveys. The findings show this item reliably identifies honest responses, improving data accuracy in epidemiological research.

Keywords:
AdolescentsEpidemiological surveysMachine learningResponse validitySelf-reported honestySubstance use

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Area of Science:

  • Epidemiology
  • Adolescent Health
  • Survey Methodology

Background:

  • Self-report surveys are crucial for adolescent substance use data but face credibility issues.
  • Assessing data quality directly by asking participants about honesty is an underutilized method.

Purpose of the Study:

  • To evaluate the accuracy of a self-report honesty item in epidemiological surveys.
  • To establish an optimal threshold for this honesty item to improve data quality and point estimates.

Main Methods:

  • Utilized data from the 2020 Illinois Youth Survey, a school-based self-report study.
  • Employed supervised machine learning (random forest) and logistic regression to analyze data subsets based on honesty item responses.
  • Investigated relationships between honesty thresholds, fake drug use, social desirability, and missing data.

Main Results:

  • Confirmed the appropriateness and reliability of the honesty item and its threshold across different analyses.
  • Found a correlation between lower honesty scores and reported fake drug use, increased missingness, and social desirability bias.
  • Honesty thresholds were consistent between machine learning and logistic regression analyses.

Conclusions:

  • The honesty item and its threshold are reliable for assessing data quality in adolescent epidemiological research.
  • Researchers should incorporate self-report honesty items to model accurate point estimates and address questionable reporting.
  • Missing data analysis further validated the honesty threshold, reinforcing the study's findings and methodology.