Description Usage Arguments Value References See Also Examples
Compute bootstrap Standard Error of Equating (SEE).
1 2 3 4 5 |
data |
a data frame. |
fun |
a function to pass to bootstrap. The function must return
a concordance table with source test scores in first column
named "x", and equated scores in the second column named "yx"
as in |
clusters |
vector or list of vectors of cluster groupping variables. |
reps |
number of bootstrap repetitions (100 by default). |
x |
object to plot or print. |
type,col,lty,xlab,ylab |
arguments of the plot function. |
alpha |
plot lines opacity (range [0, 1]). |
... |
potentially further arguments passed from other methods. |
Returns Bias, SE and RMSE values for each score point and averaged SEE values coputed with mean or average weighted on score points probabilities.
Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. London: Chapman & Hall/CRC.
Field, C.A. & Welsh, A.H. (2007). Bootstrapping clustered data. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 69(3), 369-390.
Kolen, M.J. & Brennan, R.J. (2004). Test Equating, Scaling, and Linking: Methods and Practices. New York: Springer-Verlag.
Rena, S., Lai, H., Tong, W., Aminzadeh, M., Hou, X. & Lai, S. (2010). Nonparametric bootstrapping for hierarchical data. Journal of Applied Statistics, 37(9), 1487-1498.
von Davier, A.A., Holland, P.W. & Thayer, D.T. (2004). The Kernel Method of Test Equating. New York: Springer-Verlag.
Wang, C. (2011). An investigation of bootstrap methods for estimating the standard error of equating under the common-item nonequivalent groups design. doctoral PhD diss., University of Iowa. http://ir.uiowa.edu/etd/1188
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | data(Tests)
x <- Tests[Tests$Sample == "P", "x"]
y <- Tests[Tests$Sample == "P", "y"]
data <- data.frame(x=x, y=y)
# a function to be passed to bootstrap
myfun1 <- function(data) {
eq <- equi(smoothtab(data$x, data$y, presmoothing=TRUE))
return(eq$conc)
}
# note: the number of iterations is small
# only to run faster as an example
see(data, myfun1, reps=25)
## Bootstrap for NEAT-CE design
data(Tests)
myfun2 <- function(Tests) {
p <- Tests[Tests$Sample == "P", 1:2]
q <- Tests[Tests$Sample == "Q", 2:3]
eq <- equi(smoothtab(p), smoothtab(q))
return(eq$conc)
}
see(Tests, myfun2, reps=25)
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