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Poisson Model with Three Binary Predictors: When are Saturated Designs Optimal?

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Stochastic Models, Statistics and Their Applications

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 122))

Abstract

In this paper, Poisson regression models with three binary predictors are considered. These models are applied to rule-based tasks in educational and psychological testing. To efficiently estimate the parameters of these models locally D-optimal designs will be derived. Eight out of all 70 possible saturated designs are proved to be locally D-optimal in the case of active effects. Two further saturated designs which are the classical fractional factorial designs turn out to be locally D-optimal for vanishing effects.

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References

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Acknowledgements

This work was partly supported by grant Ho1286-6 of the Deutsche Forschungsgemeinschaft.

Author information

Authors and Affiliations

  1. School of Business and Economics, Humboldt University, Unter den Linden 6, 10 099, Berlin, Germany

    Ulrike Graßhoff

  2. Institute of Psychology, University of Münster, Fliednerstr. 21, 48 149, Münster, Germany

    Heinz Holling

  3. Institute for Mathematical Stochastics, Otto-von-Guericke University, PF 4120, 39 016, Magdeburg, Germany

    Rainer Schwabe

Authors
  1. Ulrike Graßhoff
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  2. Heinz Holling
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  3. Rainer Schwabe
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Corresponding author

Correspondence to Heinz Holling .

Editor information

Editors and Affiliations

  1. Institute of Statistics, RWTH Aachen University, Aachen, Germany

    Ansgar Steland

  2. Dept. of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wrocław, Poland

    Ewaryst Rafajłowicz

  3. Inst. of Mathematics and Computer Science, Wrocław University of Technology, Wrocław, Poland

    Krzysztof Szajowski

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Graßhoff, U., Holling, H., Schwabe, R. (2015). Poisson Model with Three Binary Predictors: When are Saturated Designs Optimal?. In: Steland, A., Rafajłowicz, E., Szajowski, K. (eds) Stochastic Models, Statistics and Their Applications. Springer Proceedings in Mathematics & Statistics, vol 122. Springer, Cham. https://doi.org/10.1007/978-3-319-13881-7_9

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