Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup, message=FALSE, warning=FALSE--------------------------------------
## load package
# install.packages("equaltestMI")
library(equaltestMI)
## ----setup2, message=FALSE, warning=FALSE-------------------------------------
# install.packages("devtools")
# library(devtools)
# devtools::install_github("gabriellajg/equaltestMI", force=TRUE)
library(equaltestMI)
## -----------------------------------------------------------------------------
data(LeeAlOtaiba)
# contains sample covariance matrices and sample means of four groups
## -----------------------------------------------------------------------------
## group 1 = boys ineligible for free-reduced lunches
Group1 <- LeeAlOtaiba$BoysIneligible
Group1 <- as.matrix(Group1)
## group 2 = boys eligible for free-reduced lunches
Group2 <- LeeAlOtaiba$BoysEligible
Group2 <- as.matrix(Group2)
# sample means:
M1 <- Group1[1,]
M2 <- Group2[1,]
# sample covariance matrices:
Cov1 <- Group1[2:7,]
Cov2 <- Group2[2:7,]
## ---- echo=FALSE--------------------------------------------------------------
M1
## ---- echo=FALSE--------------------------------------------------------------
round(Cov1, 3)
## ---- echo=FALSE--------------------------------------------------------------
M2
## ---- echo=FALSE--------------------------------------------------------------
round(Cov2, 3)
## -----------------------------------------------------------------------------
## lavaan model syntax
model <- '
AlphabetKnowledge =~ Letter_Name+ Letter_Sound
PhonologicalAwareness =~ Blending + Elision
Spelling =~ Real_Words + Pseudo_Words
'
## ---- eval=FALSE--------------------------------------------------------------
# ## the results using equivalence testing and projection method
# ## full R output will be presented in Part 3
# test <- eqMI.main(model = model,
# sample.nobs = c(78, 174),
# sample.mean = list(M1, M2),
# sample.cov = list(Cov1, Cov2),
# meanstructure = TRUE,
# output = 'both',
# quiet = TRUE,
# equivalence.test = TRUE, adjRMSEA = TRUE,
# projection = TRUE, bootstrap = FALSE)
## ---- echo=FALSE--------------------------------------------------------------
## the results using equivalence testing and projection method
test <- eqMI.main(model = model,
sample.nobs = c(78, 174),
sample.mean = list(M1, M2),
sample.cov = list(Cov1, Cov2),
meanstructure = TRUE,
output = 'both',
quiet = FALSE,
equivalence.test = TRUE, adjRMSEA = TRUE,
projection = TRUE, bootstrap = FALSE)
## ---- eval=FALSE--------------------------------------------------------------
# test1 <- eqMI.main(model = model,
# sample.nobs = c(78, 174), sample.cov = list(Cov1, Cov2),
# sample.mean = list(M1, M2), meanstructure = TRUE,
# equivalence.test = FALSE, adjRMSEA = FALSE)
## ---- eval=FALSE--------------------------------------------------------------
# test2 <- eqMI.main(model = model,
# sample.nobs = c(78, 174), sample.cov = list(Cov1, Cov2),
# sample.mean = list(M1, M2), meanstructure = TRUE,
# equivalence.test = FALSE, adjRMSEA = FALSE,
# projection = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# test3 <- eqMI.main(model = model,
# sample.nobs = c(78, 174), sample.cov = list(Cov1, Cov2),
# sample.mean = list(M1, M2), meanstructure = TRUE,
# equivalence.test = TRUE, adjRMSEA = FALSE)
## ---- eval=FALSE--------------------------------------------------------------
# test4 <- eqMI.main(model = model,
# sample.nobs = c(78, 174), sample.cov = list(Cov1, Cov2),
# sample.mean = list(M1, M2), meanstructure = TRUE,
# equivalence.test = TRUE, adjRMSEA = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# test5 <- eqMI.main(model = model,
# sample.nobs = c(78, 174), sample.cov = list(Cov1, Cov2),
# sample.mean = list(M1, M2), meanstructure = TRUE,
# equivalence.test = TRUE, adjRMSEA = TRUE,
# projection = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# test6 <- eqMI.main(model = model, structure = 'mean',
# sample.nobs = c(78, 174), sample.cov = list(Cov1, Cov2),
# sample.mean = list(M1, M2), meanstructure = TRUE,
# equivalence.test = TRUE, adjRMSEA = TRUE,
# projection = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# test7 <- eqMI.main(model = model, data = literacy.dat,
# group = "FRL", meanstructure = TRUE,
# equivalence.test = TRUE, adjRMSEA = TRUE,
# projection = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# test8 <- eqMI.main(model = model, data = literacy.dat,
# group = "FRL", meanstructure = TRUE,
# equivalence.test = TRUE, adjRMSEA = TRUE,
# projection = TRUE, bootstrap = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# test9 <- eqMI.main(model = model, data = literacy.dat,
# group = "FRL", meanstructure = TRUE,
# equivalence.test = TRUE, adjRMSEA = TRUE,
# projection = TRUE, bootstrap = FALSE,
# quite = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# test10 <- eqMI.main(model = model, data = literacy.dat,
# group = "FRL", meanstructure = TRUE,
# group.partial = c("Spelling=~Real_Words", "Blending~1"),
# equivalence.test = TRUE, adjRMSEA = TRUE,
# projection = TRUE)
## ---- echo=FALSE--------------------------------------------------------------
library(printr)
?eqMI.main
## ---- include=FALSE-----------------------------------------------------------
# For a complete view of the help page of function eqMI.main(), please install R package printr and type ?eqMI.main in R console:
#library(printr)
#?eqMI.main
#output: pdf_document
#devtools::build_vignettes()
#R CMD Rd2pdf "~/Box Sync/MacSync/Research/Frontier/equaltestMI"
#R CMD check --as-cran equaltestMI_0.6.0.tar.gz
#https://bookdown.org/yihui/rmarkdown-cookbook/package-vignette.html
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