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Latent Class Analysis

2016
Διπλωματική εργασία - Πάντειο Πανεπιστήμιο. Τμήμα Οικονομικής και Περιφερειακής Ανάπτυξης, ΠΜΣ, κατεύθυνση Εφηρμοσμένων Οικονομικών και Διοίκησης ...
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Latent class analysis of diagnostic agreement

Statistics in Medicine, 1990
AbstractWe describe methods based on latent class analysis for analysis and interpretation of agreement on dichotomous diagnostic ratings. This approach formulates agreement in terms of parameters directly related to diagnostic accuracy and leads to many practical applications, such as estimation of the accuracy of individual ratings and the extent to ...
J S, Uebersax, W M, Grove
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Latent class analysis in medical research

Statistical Methods in Medical Research, 1996
In the introduction we give a brief characterization of the usual measures for indicating the quality of diagnostic procedures (sensitivity, specificity and predictive value) and we refer to their relationship to parameters of the latent class model. Different variants of latent class analysis (LCA) for dichotomous data are described in the following:
A K, Formann, T, Kohlmann
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Linear Logistic Latent Class Analysis

Biometrical Journal, 1982
AbstractIn the present paper the linear logistic extension of latent class analysis is described. Thereby it is assumed that the item latent probabilities as well as the class sizes can be attributed to some explanatory variables. The basic equations of the model state the decomposition of the log‐odds of the item latent probabilities and of the class ...
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Latent-Class-Analysis

2008
Personen unterscheiden sich hinsichtlich einer Vielzahl von Eigenschaften, zum Beispiel ihres Geschlechts, ihrer Korpergrose, oder ihres Temperaments: Manche Menschen sind eher extravertiert, andere eher introvertiert. Solche Personvariablen sind zum einen entweder direkt beobachtbar (Geschlecht, Korpergrose) oder nur indirekt uber Indikatorvariablen ...
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Latent Class Analysis

2021
Douglas D. Gunzler   +2 more
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Latent Class Analysis and Model Selection

2006
This paper discusses model selection for latent class (LC) models. A large experimental design is set that allows the comparison of the performance of different information criteria for these models, some compared for the first time. Furthermore, the level of separation of latent classes is controlled using a new procedure.
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