Literature DB >> 34565940

Is Measurement Noninvariance a Threat to Inferences Drawn from Randomized Control Trials? Evidence From Empirical and Simulation Studies.

James Soland1,2.   

Abstract

Randomized control trials (RCTs) are considered the gold standard when evaluating the impact of psychological interventions, educational programs, and other treatments on outcomes of interest. However, few studies consider whether forms of measurement bias like noninvariance might impact estimated treatment effects from RCTs. Such bias may be more likely to occur when survey scales are utilized in studies and evaluations in ways not supported by validation evidence, which occurs in practice. This study consists of simulation and empirical studies examining whether measurement noninvariance impacts treatment effects from RCTs. Simulation study results demonstrate that bias in treatment effect estimates is mild when the noninvariance occurs between subgroups (e.g., male and female participants), but can be quite substantial when being assigned to control or treatment induces the noninvariance. Results from the empirical study show that surveys used in two federally funded evaluations of educational programs were noninvariant across student age groups.
© The Author(s) 2021.

Entities:  

Keywords:  bias; evaluating interventions; measurement invariance; randomized control trials; testing

Year:  2021        PMID: 34565940      PMCID: PMC8361374          DOI: 10.1177/01466216211013102

Source DB:  PubMed          Journal:  Appl Psychol Meas        ISSN: 0146-6216


  9 in total

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Authors:  M A Sprangers; C E Schwartz
Journal:  Soc Sci Med       Date:  1999-06       Impact factor: 4.634

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Authors:  Herbert W Marsh; Benjamin Nagengast; Alexandre J S Morin
Journal:  Dev Psychol       Date:  2012-01-16

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Authors:  Frans J Oort
Journal:  Qual Life Res       Date:  2005-04       Impact factor: 4.147

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Authors:  Stephen Stark; Oleksandr S Chernyshenko; Fritz Drasgow
Journal:  J Appl Psychol       Date:  2006-11

6.  Comparative fit indexes in structural models.

Authors:  P M Bentler
Journal:  Psychol Bull       Date:  1990-03       Impact factor: 17.737

7.  An application of structural equation modeling to detect response shifts and true change in quality of life data from cancer patients undergoing invasive surgery.

Authors:  Frans J Oort; Mechteld R M Visser; Mirjam A G Sprangers
Journal:  Qual Life Res       Date:  2005-04       Impact factor: 4.147

8.  Measurement Invariance Conventions and Reporting: The State of the Art and Future Directions for Psychological Research.

Authors:  Diane L Putnick; Marc H Bornstein
Journal:  Dev Rev       Date:  2016-06-29

9.  Response shifts in mental health interventions: an illustration of longitudinal measurement invariance.

Authors:  Marjolein Fokkema; Niels Smits; Henk Kelderman; Pim Cuijpers
Journal:  Psychol Assess       Date:  2013-01-21
  9 in total
  1 in total

1.  Evidence That Selecting an Appropriate Item Response Theory-Based Approach to Scoring Surveys Can Help Avoid Biased Treatment Effect Estimates.

Authors:  James Soland
Journal:  Educ Psychol Meas       Date:  2021-05-03       Impact factor: 2.821

  1 in total

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