### Abstract

Original language | Undefined |
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Title of host publication | Psychometrics in practice at RCEC |

Editors | Theodorus Johannes Hendrikus Maria Eggen, Bernard P. Veldkamp |

Publisher | RCEC |

Pages | 103-114 |

ISBN (Print) | 9789036533744 |

DOIs | |

Publication status | Published - 2012 |

### Publication series

Name | |
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Publisher | RCEC |

### Keywords

- Item Response Theory
- one-parameter logistic model
- finite mixture
- Markov chain Monte Carlo
- plausible values
- IR-80205
- Bayes estimates
- Gibbs sampler

### Cite this

*Psychometrics in practice at RCEC*(pp. 103-114). RCEC. https://doi.org/10.3990/3.9789036533744.ch8

}

*Psychometrics in practice at RCEC.*RCEC, pp. 103-114. https://doi.org/10.3990/3.9789036533744.ch8

**Don't Tie Yourself to an Onion: Don’t Tie Yourself to Assumptions of Normality.** / Marsman, Maarten; Maris, Gunter; Bechger, Timo.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

TY - CHAP

T1 - Don't Tie Yourself to an Onion: Don’t Tie Yourself to Assumptions of Normality

AU - Marsman, Maarten

AU - Maris, Gunter

AU - Bechger, Timo

PY - 2012

Y1 - 2012

N2 - A structural measurement model (Adams, Wilson, & Wu, 1997) consists of an item response theory model for responses conditional on ability and a structural model that describes the distribution of ability in the population. As a rule, ability is assumed to be normally distributed in the population. However, there are situations where there is reason to assume that the distribution of ability is nonnormal. In this paper, we show that nonnormal ability distributions are easily modeled in a Bayesian framework

AB - A structural measurement model (Adams, Wilson, & Wu, 1997) consists of an item response theory model for responses conditional on ability and a structural model that describes the distribution of ability in the population. As a rule, ability is assumed to be normally distributed in the population. However, there are situations where there is reason to assume that the distribution of ability is nonnormal. In this paper, we show that nonnormal ability distributions are easily modeled in a Bayesian framework

KW - Item Response Theory

KW - one-parameter logistic model

KW - finite mixture

KW - Markov chain Monte Carlo

KW - plausible values

KW - IR-80205

KW - Bayes estimates

KW - Gibbs sampler

U2 - 10.3990/3.9789036533744.ch8

DO - 10.3990/3.9789036533744.ch8

M3 - Chapter

SN - 9789036533744

SP - 103

EP - 114

BT - Psychometrics in practice at RCEC

A2 - Eggen, Theodorus Johannes Hendrikus Maria

A2 - Veldkamp, Bernard P.

PB - RCEC

ER -