README.md

In mirka-henninger/raschTreeEffectSize: Helper functions to use the Mantel-Haenszel effect size measure as a stopping criterion in Rasch trees

raschtreeMH

This compendium contains helper functions to use the Mantel-Haenszel odds ratio effect size measure in Rasch trees to evaluate the magnitude of DIF.

It can be installed like an R package using devtools:

devtools::install_github("mirka-henninger/raschtreeMH")
library(raschtreeMH)

It uses functions from the psychotree and partykit packages to fit the raschtree in the recursive partioning environment. The functions from the packages (in particular mob, mob_control, and graphics functions) are modified, to include the new stopping rule and to be able to color items in each end node by the Mantel-Haenszel odds ratio effect size measure of inner nodes. Additional helper functions are provided to compute the Mantel-Haenszel odds ratio from the raschtree object. As these functions are modified, it is important unload partykit and psychotree before the usage. This repository is currently under development and undergoes ongoing changes and improvement. Please report any bugs that you encounter.

data("SPISA", package = "psychotree")
RT <- raschtree(spisa ~ gender + age + semester, data = SPISA, 
                stopfun = stopfun_mantelhaenszel(purification = "iterative"))
RT_MH <- add_mantelhaenszel(RT, purification = "iterative")
RT_MH$info$mantelhaenszel
plot(RT_MH, color_by_node = 1)
plot(RT_MH, color_by_node = 3)

References

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Holland, P. W., & Thayer, D. T. (1985). An alternate definition of the ETS delta scale of item difficulty. 85, 85–64. https://doi.org/10.1002/j.2330-8516.1985.tb00128

Holland, P. W., & Thayer, D. T. (1986). Differential item functioning and the Mantel-Haenszel procedure. Program Statistics Research Technical Report No. 86-69, 1–24. https://doi.org/10.1002/j.2330-8516.1986.tb00186.x

Hothorn, T., & Zeileis, A. (2015). partykit: A modular toolkit for recursive partioning in {R}. Journal of Machine Learning Research, 16, 3905–3909. http://jmlr.org/papers/v16/hothorn15a.html

Magis, D., Béland, S., Tuerlinckx, F., & De Boeck, P. (2010). A general framework and an R package for the detection of dichotomous differential item functioning. Behavior Research Methods, 42, 847–862. https://doi.org/10.3758/BRM.42.3.847

Mantel, N. (1963). Chi-Square tests with one degree of freedom: Extensions of the Mantel-Haenszel procedure. Journal of the American Statistical Association, 58(303), 690–700. https://doi.org/10.1080/01621459.1963.10500879

Paek, I., & Holland, P. W. (2015). A note on statistiscal hypothesis testing based on log transformation of the Mantel-Haenszel common odds ratio for differential item functioning classification. Psychometrika, 80, 406–411. https://doi.org/10.1007/s11336-013-9394-5

Phillips, A., & Holland, P. W. (1987). Estimators of the variance of the Mantel-Haenszel log-odds-ratio estimate. Biometrics, 43, 425–431. https://doi.org/10.2307/2531824

Steinberg, L., & Thissen, D. (2006). Using effect sizes for research reporting: Examples using item response theory to analyze differential item functioning. Psychological Methods, 11(4), 402–415. https://doi.org/10.1037/1082-989X.11.4.402

Strobl, C., Kopf, J., & Zeileis, A. (2015). Rasch trees: A new method for detecting differential item functioning in the Rasch model. Psychometrika, 80, 289–316. https://doi.org/10.1007/s11336-013-9388-3

Zwick, R. (2012). A review of ETS differential item functioning assessment procedures: Flagging rules, minimum sample size requirements, and criterion refinement. In ETS Research Report Series. https://doi.org/10.1002/j.2333-8504.2012.tb02290.x

mirka-henninger/raschTreeEffectSize documentation built on Nov. 14, 2021, 11:15 p.m.