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Tilburg University

Contributions to bias adjusted stepwise latent class modeling Bakk, Zsuzsa

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Publication date: 2015 Link to publication

Citation for published version (APA): Bakk, Z. (2015). Contributions to bias adjusted stepwise latent class modeling Ridderkerk: Ridderprint

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CONTRIBUTIONS TO BIAS ADJUSTED STEPWISE LATENT CLASS MODELING

Zsuzsa Bakk

CONTRIBUTIONS TO BIAS ADJUSTED STEPWISE LATENT CLASS MODELING

Zsuzsa Bakk Tilburg University

CONTRIBUTIONS TO BIAS ADJUSTED STEPWISE LATENT CLASS MODELING

c 2015 Z. Bakk All Rights Reserved.  Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage and retrieval system, without written permission of the author. This research is funded by The Netherlands Organization for Scientific Research (NWO [VICI grant number 453-10-002]). Printing was financially supported by Tilburg University. ISBN: Printed by:

XXX Ridderprint BV, Ridderkerk, the Netherlands

CONTRIBUTIONS TO BIAS ADJUSTED STEPWISE LATENT CLASS MODELING

PROEFSCHRIFT ter verkrijging van de graad van doctor aan Tilburg University op gezag van de rector magnificus, prof.dr. E.H.L. Aarts, in het openbaar te verdedigen ten overstaan van een door het college voor promoties aangewezen commissie in de aula van de Universiteit op vrijdag 16 oktober 2015 om 14.15 uur

door Zsuzsa Bakk geboren op 16 mei 1982 te Targu Secuiesc, Roemeni¨e

Promotor: Copromotor:

prof.dr. J. K. Vermunt dr. D.L. Oberski

Overige leden van de Promotiecommissie:

prof. F. Bassi dr. M.A. Croon dr. J.P.T.M. Gelissen prof.dr. P.G.M. van der Heijden prof.dr. J. Kuha

Contents 1 Introduction 1.1 Latent class modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Bias adjusted stepwise LC models . . . . . . . . . . . . . . . . . . . . . 1.3 Outline of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Estimating the association between latent class membership variables using bias adjusted three-step approaches 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Latent class modeling and classification . . . . . . . . . . . 2.2.1 The basic latent class model . . . . . . . . . . . . . 2.2.2 Obtaining latent class predictions . . . . . . . . . . . 2.2.3 Quantifying the classification errors . . . . . . . . . . 2.3 LCA with external variables: traditional approaches . . . . . 2.3.1 One-step approach . . . . . . . . . . . . . . . . . . 2.3.2 The standard three-step approach . . . . . . . . . . 2.4 Generalization of existing correction methods . . . . . . . . 2.4.1 The three-step ML approach . . . . . . . . . . . . . 2.4.2 The Bolck-Croon-Hagenaars (BCH) approach . . . . 2.4.3 The modified BCH approach . . . . . . . . . . . . . 2.4.4 ML adjustment with multiple latent variables . . . . 2.5 Simulation study . . . . . . . . . . . .