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Related Experiment Video

Updated: Jun 9, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

The Influence of Study Selection Criteria on Statistical Conclusion Validity: A Simulation Study.

Allyson L Hayward¹, Jeffrey A Shero¹, Jessica A R Logan¹

¹Department of Special Education, Vanderbilt University, Nashville, USA.

Contemporary School Psychology

|June 8, 2026

Summary

Different methods for identifying students with reading difficulties (SWRD) in educational research can bias intervention effect estimates. This inconsistency may distort understanding of intervention efficacy, necessitating further research for valid and feasible solutions.

Keywords:

Simulation study Struggling readers Tier 2 reading interventions

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Last Updated: Jun 9, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

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Published on: January 11, 2020

An R-Based Landscape Validation of a Competing Risk Model

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Published on: September 16, 2022

Area of Science:

Education Research
Intervention Effectiveness Studies
Quantitative Psychology

Background:

Randomized controlled trials (RCTs) are crucial for evaluating educational interventions.
Screening students with reading difficulties (SWRD) is common but uses varied criteria.
Inconsistent SWRD identification criteria can introduce bias in research.

Purpose of the Study:

To examine how varying eligibility criteria for SWRD impact estimated intervention effects.
To assess the bias introduced by different SWRD selection methods in educational RCTs.
To understand the influence of practical constraints on SWRD identification and effect estimation.

Main Methods:

A simulation study was conducted using a single underlying population with a fixed true intervention effect.
Different common methods for identifying SWRD were applied to this population.
The impact of each eligibility criterion on the estimated intervention effect size was analyzed.

Main Results:

All tested SWRD identification methods introduced some degree of bias in effect size estimation.
The magnitude and direction of this bias were inconsistent and unpredictable across methods.
Study-specific decisions in defining SWRD can lead to distorted intervention effect estimates.

Conclusions:

Variability in defining students with reading difficulties significantly impacts intervention effect estimation.
The current landscape of SWRD criteria may hinder accurate understanding of intervention efficacy.
Future research should aim to develop statistically valid and practically feasible SWRD identification standards.