semTools (version 0.5-6)

findRMSEAsamplesize: Find the minimum sample size for a given statistical power based on population RMSEA

Description

Find the minimum sample size for a specified statistical power based on population RMSEA. This function can be applied for both test of close fit and test of not-close fit (MacCallum, Browne, & Suguwara, 1996)

Usage

findRMSEAsamplesize(rmsea0, rmseaA, df, power = 0.8, alpha = 0.05, group = 1)

Arguments

rmsea0

Null RMSEA

rmseaA

Alternative RMSEA

df

Model degrees of freedom

power

Desired statistical power to reject misspecified model (test of close fit) or retain good model (test of not-close fit)

alpha

Alpha level used in power calculations

group

The number of group that is used to calculate RMSEA.

Details

This function find the minimum sample size for a specified power based on an iterative routine. The sample size keep increasing until the calculated power from findRMSEApower function is just over the specified power. If group is greater than 1, the resulting sample size is the sample size per group.

References

MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130--149. 10.1037/1082-989X.1.2.130

Jak, S., Jorgensen, T. D., Verdam, M. G., Oort, F. J., & Elffers, L. (2021). Analytical power calculations for structural equation modeling: A tutorial and Shiny app. Behavior Research Methods, 53, 1385--1406. 10.3758/s13428-020-01479-0

See Also

• plotRMSEApower to plot the statistical power based on population RMSEA given the sample size

• plotRMSEAdist to visualize the RMSEA distributions

• findRMSEApower to find the statistical power based on population RMSEA given a sample size

Examples

# NOT RUN {
findRMSEAsamplesize(rmsea0 = .05, rmseaA = .08, df = 20, power = 0.80)

# }