Akzeptanz und Ablehnung beim Übertritt in die Sekundarstufe I

Rösselet, Stephan; Neuenschwander, Markus

doi:10.1007/978-3-658-16981-7_6

Cited by 2 publications

(2 citation statements)

References 22 publications

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“…To our knowledge, there are only a few simulation studies that investigate the performance of Haberman linking [97,102,103]. In contrast to the IA method, HL has only been scarcely applied [104][105][106][107][108][109][110][111]. The linking of multiple groups using other linking functions has been treated in [102,[112][113][114].…”

Section: Estimation and Applicationsmentioning

confidence: 99%

Lp Loss Functions in Invariance Alignment and Haberman Linking with Few or Many Groups

Robitzsch

2020

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The comparison of group means in latent variable models plays a vital role in empirical research in the social sciences. The present article discusses an extension of invariance alignment and Haberman linking by choosing the robust power loss function ρ(x)=|x|p(p>0). This power loss function with power values p smaller than one is particularly suited for item responses that are generated under partial invariance. For a general class of linking functions, asymptotic normality of estimates is shown. Moreover, the theory of M-estimation is applied for obtaining linking errors (i.e., inference with respect to a population of items) for this class of linking functions. In a simulation study, it is shown that invariance alignment and Haberman linking have comparable performance, and in some conditions, the newly proposed robust Haberman linking outperforms invariance alignment. In three examples, the influence of the choice of a particular linking function on the estimation of group means is demonstrated. It is concluded that the choice of the loss function in linking is related to structural assumptions about the pattern of noninvariance in item parameters.

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Section: Estimation and Applicationsmentioning

confidence: 99%

Lp Loss Functions in Invariance Alignment and Haberman Linking with Few or Many Groups

Robitzsch

2020

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“…The linking of multiple groups using other linking functions has been treated in [84,[87][88][89]. In contrast to the IA method, HL has only been scarcely applied [90][91][92][93][94][95][96][97][98].…”

Section: Haberman Linkingmentioning

confidence: 99%

$L_p$ Loss Functions in Invariance Alignment and Haberman Linking

Robitzsch¹

2020

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The comparison of group means in latent variable models plays a vital role in empirical research in the social sciences. The present article discusses extensions of invariance alignment and Haberman linking concerning the choice of linking functions for comparisons of many groups. Robust linking functions are proposed for invariance alignment and robust Haberman linking that are particularly suited to item response data under partial invariance. In a simulation study, it is shown that both linking approaches have comparable performance, and in some conditions, the newly proposed robust Haberman linking outperforms invariance alignment.

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Akzeptanz und Ablehnung beim Übertritt in die Sekundarstufe I

Abstract: Zusammenfassung Mit dem Übertritt in die Sekundarstufe

Cited by 2 publications

References 22 publications

Lp Loss Functions in Invariance Alignment and Haberman Linking with Few or Many Groups

Lp Loss Functions in Invariance Alignment and Haberman Linking with Few or Many Groups

$L_p$ Loss Functions in Invariance Alignment and Haberman Linking

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