Sample Size Planning for RMSEA in SEM

Sample size planning for the population root mean square error of approximation (RMSEA) from the accuracy in parameter estimation (AIPE) perspective. The sample size is planned so that the expected width of a confidence interval for the population RMSEA is no larger than desired.

Usage

ss_aipe_rmsea(RMSEA, df, width, conf_level = 0.95)

Arguments

RMSEA

The input RMSEA value

df

Degrees of freedom of the model

width

Desired confidence interval width

conf_level

Desired confidence level (e.g., .90, .95, .99, etc.)

Value

Returns the necessary total sample size in order to achieve the desired degree of accuracy (i.e., the sufficiently narrow confidence interval).

References

Kelley, K., & Lai, K. (2011). Accuracy in parameter estimation for the root mean square error of approximation: Sample size planning for narrow confidence intervals. Multivariate Behavioral Research, 46, 1–32. doi:10.1080/00273171.2011.543027

Maxwell, S. E., Delaney, H. D., & Kelley, K. (2027). Designing experiments and analyzing data: A model comparison perspective (4th ed.). Routledge.

See also

ci_rmsea

design_consequences for what a chosen design delivers: power, the Type S (sign) and Type M (exaggeration) errors of the significance filter, and the expected confidence interval width.

Author

Ken Kelley kkelley@nd.edu

Examples

ss_aipe_rmsea(RMSEA = .035, df = 50, width = .05, conf_level = .95)
#> Note: The lower confidence limit of the noncentrality parameter is at its lower bound, so the lower RMSEA limit is set to 0 based on RMSEA's definition.
#> Note: The lower confidence limit of the noncentrality parameter is at its lower bound, so the lower RMSEA limit is set to 0 based on RMSEA's definition.
#> Note: The lower confidence limit of the noncentrality parameter is at its lower bound, so the lower RMSEA limit is set to 0 based on RMSEA's definition.
#>  term        value
#>  necessary_N 361  
#> 
#> Confidence level: 95%