TestGardener (version 3.3.6)

Ffuns_plot: Plot a selection of fit criterion F functions and their first two derivatives.

Description

These plots indicate whether an appropriate minimum of the fitting criterion was found. The value of index should be at the function minimum, the first derivative be close to zero there, and the second derivative should be positive. If these conditions are not met, it may be worthwhile to use function indexfun initialized with an approximate minimum value of score index index to re-estimate the value of index.

Usage

Ffuns_plot(evalarg, index, SfdList, chcemat, plotindex=1)

Value

A list vector is returned which is of the length of argument plotindex. Each member of the vector is a gg or ggplot object for the associated

plotindex value. Each plot can be displayed using the print command. The plots of item power are produced as a side value even if no output object is specified in the call to the function.

Arguments

evalarg

A vector containingg the sore index values to be evaluated.

index

The vector of of length N of score index values.

SfdList

The list vector of length n containing the estimated surprisal curves.

chcemat

The entire N by n matrix of choice indices.

plotindex

A subset of the integers 1:N.

Author

Juan Li and James Ramsay

Details

The curves are displayed in three vertically organized panels along with values of index and the values and first two derivative values of the fit criterion. If more than one index value is used, a press of the Enter or Return key moves to the next index value.

References

Ramsay, J. O., Li J. and Wiberg, M. (2020) Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45, 297-315.

Ramsay, J. O., Li J. and Wiberg, M. (2020) Better rating scale scores with information-based psychometrics. Psych, 2, 347-360.

See Also

index_fun, Ffun, DFfun

Examples

#  Example 1.  Display fit criterion values and derivatives for the 
#  short SweSAT multiple choice test with 24 items and 1000 examinees
chcemat   <- Quant_13B_problem_dataList$chcemat
index     <- Quant_13B_problem_parmList$index
SfdList   <- Quant_13B_problem_parmList$SfdList
plotindex <- 1:3
indfine   <- seq(0,100,len=101)
Ffuns_plot(indfine, index, SfdList, chcemat, plotindex)