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Accuracy in parameter estimation for targeted effects in structural equation modeling: sample size planning for

Keke Lai¹, Ken Kelley

¹Department of Psychology, University of Notre Dame, Notre Dame, IN 46556, USA.

Psychological Methods

|March 23, 2011

Summary

Researchers can now plan sample sizes for structural equation models (SEM) to ensure narrow confidence intervals for parameter estimation. This improves the precision of effect size estimates in SEM analyses.

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Area of Science:

Psychometrics
Statistical Modeling
Quantitative Psychology

Background:

Evaluating structural equation models (SEM) involves assessing overall fit and specific model parameters.
Confidence intervals for SEM parameters are crucial for understanding the magnitude of effects.
Wide confidence intervals, even with good overall model fit, can limit the interpretability of targeted effects.

Purpose of the Study:

To develop sample size planning methods for SEM based on the accuracy in parameter estimation approach.
To ensure sufficiently narrow confidence intervals for key model parameters.
To provide researchers with tools for precise estimation in SEM.

Main Methods:

Developed methods for sample size planning focused on achieving narrow confidence interval widths.
Introduced a procedure to guarantee confidence intervals do not exceed desired widths with a specified assurance.
Utilized a Monte Carlo simulation study to validate the effectiveness of the developed procedures.

Main Results:

The developed sample size planning methods effectively control confidence interval width for SEM parameters.
Simulation studies confirmed the procedures' accuracy in realistic scenarios.
The methods provide a means to obtain precise estimates of population effects in SEM.

Conclusions:

The proposed accuracy in parameter estimation methods are effective for sample size planning in SEM.
These methods enhance the ability of researchers to obtain informative confidence intervals.
The procedures have been implemented in the R package MBESS for practical application.