GAIPE (version 1.1)

GAIPE.RMSEA: Sample size planning by GAIPE framework on RMSEA

Description

Draws the graph for sample size planning by GAIPE framework on RMSEA.

Usage

GAIPE.RMSEA(rmsea, df, width = NULL, clevel = 0.95, N = c(100, 1800, 15), 
PA_method = c("exact.fit", "close.fit", "not.close.fit"), 
H0rmsea = NULL, alpha = 0.05, power = c(0.8, 0.9, 0.95))

Arguments

rmsea

vector of the expected RMSEA values.

df

model degrees of freedom.

width

vector of desired confidence interval widths to be highlighted in the graph.

clevel

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

N

vector of specifying the range and the increment of sample size for drawing confidence intervals. Note that N[1:2] represents the range whereas N[3] represents the increment.

PA_method

a character string specifying the desired hypothesis test for power analysis, can be one of "exact.fit", "close.fit", or "not.close.fit".

H0rmsea

RMSEA for null hypothesis.

alpha

type I error rate for power analysis.

power

vector of specifying the power values for which horizontal lines are to be added in the graph.

Details

If user wants to implement the power analysis based on RMSEA in GAIPE, the PA_method and H0rmsea have to be specified. In such a case, the first value of rmsea is the RMSEA for the alternative hypothesis.

References

Lin, T.-Z. & Weng, L.-J. (2014) Graphical Extension of Sample Size Planning With AIPE on RMSEA Using R. Structural Equation Modeling, 21, 482-490. doi:10.1080/10705511.2014.915380

Examples

# NOT RUN {
# Drawing the graphs in  Lin & Weng (2014) #

# FIGURE 2 #
GAIPE.RMSEA(rmsea=.05,df=30,width=c(.03,.04))

# FIGURE 3 #
GAIPE.RMSEA(rmsea=c(.05,.08),df=30,width=c(.03,.04))

# FIGURE 4 #
GAIPE.RMSEA(rmsea=.025,df=30,width=c(.03,.04),PA_method="not.close.fit",H0rmsea=0.05)

# FIGURE 5 #
GAIPE.RMSEA(rmsea=.05,df=30,width=c(.03,.04),PA_method="exact.fit",H0rmsea=0) 

# }