Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Jacques A. Hagenaars"'
Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis contributed essays to this volume, each presenting
Publikováno v:
Grundlagen-Methoden-Anwendungen in den Sozialwissenschaften ISBN: 9783658156282
Der Vergleich von Koeffizienten aus logistischen Regressionsmodellen zwischen verschiedenen Stichproben oder zwischen verschachtelten Gleichungen innerhalb einer Stichprobe ist aufgrund der Skalierungsproblematik der Koeffizienten bzw. der Aggregieru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16fd4220c592f34fb1cb5887cc300c56
https://doi.org/10.1007/978-3-658-15629-9_1
https://doi.org/10.1007/978-3-658-15629-9_1
Publikováno v:
Psychological Methods, 20(4), 422-443. AMER PSYCHOLOGICAL ASSOC
A latent class multitrait-multimethod (MTMM) model is proposed to estimate random and systematic measurement error in categorical survey questions while making fewer assumptions than have been made so far in such evaluations, allowing for possible ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d510df20fd1daad7da98a2a3fce713e7
https://doi.org/10.1037/a0039783
https://doi.org/10.1037/a0039783
Autor:
Jacques A. Hagenaars
Publikováno v:
Lebensbedingungen in Deutschland in der Längsschnittperspektive ISBN: 9783658192051
The main advantage of panel analysis is that changes can be investigated at the individual level. However, the observed individual changes result not only from underlying, true changes but also from random fluctuations. The problem is that these rand
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61a1db73090305e15078a55455bdc575
https://doi.org/10.1007/978-3-658-19206-8_14
https://doi.org/10.1007/978-3-658-19206-8_14
Publikováno v:
Sociological Methodology, 43(1), 1-41. Wiley-Blackwell
Very often the data collected by social scientists involve dependent observations, without, however, the investigators having any substantive interest in the nature of the dependencies. Although these dependencies are not important for the answers to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a004b90749fa0a4599210757db113a05
https://doi.org/10.1177/0081175013488999
https://doi.org/10.1177/0081175013488999
Autor:
Jacques A. Hagenaars
Publikováno v:
Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 11(4), 126-141. Hogrefe & Huber Publishers
The “General Linear Reality” view of the social world endorsed by analysis models assuming (underlying) continuous variables that are normally distributed is still prevailing in most of social and behavioral research. In this article both assumpt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b6f59af48a52ae5cfeae1aa761b61dc
https://research.tilburguniversity.edu/en/publications/8f286d47-0a00-4b95-a925-83efc6d8b6e3
https://research.tilburguniversity.edu/en/publications/8f286d47-0a00-4b95-a925-83efc6d8b6e3
Autor:
Jan J. V. Busschbach, Helene Andrea, Jacques A. Hagenaars, Anna Bartak, Marieke Dingena Spreeuwenberg, Jos Twisk, Theo Stijnen, Marcel A. Croon
Publikováno v:
Medical Care, 48(2), 166-174. Lippincott Williams & Wilkins
Medical Care, 48(2), 166-174. Lippincott Williams and Wilkins
Spreeuwenberg, M D, Bartak, A, Croon, M A, Hagenaars, J A, Busschbach, J J V, Andrea, H, Twisk, J W R & Stijnen, T 2010, ' The multiple propensity score as control for bias in the comparison of more than two treatment arms: an introduction from a case study in mental health ', Medical Care, vol. 48, no. 2, pp. 166-174 . https://doi.org/10.1097/MLR.0b013e3181c1328f
Medical Care, 48(2), 166-174
Medical Care, 48(2), 166-174. Lippincott Williams and Wilkins
Spreeuwenberg, M D, Bartak, A, Croon, M A, Hagenaars, J A, Busschbach, J J V, Andrea, H, Twisk, J W R & Stijnen, T 2010, ' The multiple propensity score as control for bias in the comparison of more than two treatment arms: an introduction from a case study in mental health ', Medical Care, vol. 48, no. 2, pp. 166-174 . https://doi.org/10.1097/MLR.0b013e3181c1328f
Medical Care, 48(2), 166-174
Background and Objective: The propensity score method (PS) has proven to be an effective tool to reduce bias in nonrandomized studies, especially when the number of (potential) confounders is large and dimensionality problems arise. The PS method int
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::125e46e00c905fca77fedeb879f04f9c
https://hdl.handle.net/1765/27375
https://hdl.handle.net/1765/27375
Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators
Publikováno v:
Political Analysis. 12:3-27
We study the properties of a three-step approach to estimating the parameters of a latent structure model for categorical data and propose a simple correction for a common source of bias. Such models have a measurement part (essentially the latent cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90ac59d666780de9a9f46235b51016ed
https://doi.org/10.1093/pan/mph001
https://doi.org/10.1093/pan/mph001
Publikováno v:
Applied Latent Class Analysis. :433-438
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d5e473f2d866b95024b7e2dacfd28b9
https://doi.org/10.1017/cbo9780511499531.017
https://doi.org/10.1017/cbo9780511499531.017
Publikováno v:
Sociological Methods & Research. 29:230-268
Conclusions about changes in categorical characteristics based on observed panel data can be incorrect when (even a small amount of) measurement error is present. Random measurement errors, referred to as independent classification errors, usually le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2a8ca73a23e3a0bc716da116ebadedb
https://doi.org/10.1177/0049124100029002003
https://doi.org/10.1177/0049124100029002003