GAIPE.RMSEA | R Documentation |
Draws the graph for sample size planning by GAIPE framework on RMSEA.
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))
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. |
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.
Tzu-Yao Lin
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
# 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)
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