scholarly journals A combined latent class and trait model for the analysis and visualization of discrete data

2001 ◽  
Vol 23 (8) ◽  
pp. 859-872 ◽  
Author(s):  
A. Kaban ◽  
M. Girolami
Keyword(s):  
Latent Class ◽  
Discrete Data ◽  
Trait Model

scholarly journals Clustering criteria for discrete data and latent class models

1991 ◽  
Vol 8 (2) ◽  
pp. 157-176 ◽  
Author(s):  
Gilles Celeux ◽  
Gérard Govaert
Keyword(s):  
Latent Class ◽  
Discrete Data ◽  
Latent Class Models ◽  
Class Models

Integrated Fractional white Noise as an Alternative to Multifractional Brownian Motion

2007 ◽  
Vol 44 (02) ◽  
pp. 393-408 ◽  
Author(s):  
Allan Sly
Keyword(s):  
Stochastic Process ◽  
Brownian Motion ◽  
White Noise ◽  
Gaussian Process ◽  
Discrete Data ◽  
Hölder Exponent ◽  
Scaling Properties ◽  
Multifractional Brownian Motion ◽  
Local Properties

Multifractional Brownian motion is a Gaussian process which has changing scaling properties generated by varying the local Hölder exponent. We show that multifractional Brownian motion is very sensitive to changes in the selected Hölder exponent and has extreme changes in magnitude. We suggest an alternative stochastic process, called integrated fractional white noise, which retains the important local properties but avoids the undesirable oscillations in magnitude. We also show how the Hölder exponent can be estimated locally from discrete data in this model.

Zur Anwendung der CES-D bei älteren Menschen: Dimensionsstruktur und Meßartefakte

Diagnostica ◽  
2000 ◽  
Vol 46 (1) ◽  
pp. 29-37 ◽  
Author(s):  
Herbert Matschinger ◽  
Astrid Schork ◽  
Steffi G. Riedel-Heller ◽  
Matthias C. Angermeyer
Keyword(s):  
Mental State ◽  
Latent Class ◽  
Mini Mental State Examination ◽  
Depression Scale ◽  
Epidemiological Studies ◽  
Partial Credit ◽  
Examination Score ◽  
State Examination

Zusammenfassung. Beim Einsatz der Center for Epidemiological Studies Depression Scale (CES-D) stellt sich das Problem der Dimensionalität des Instruments, dessen Lösung durch die Konfundierung eines Teilkonstruktes (“Wohlbefinden”) mit Besonderheiten der Itemformulierung Schwierigkeiten bereitet, da Antwortartefakte zu erwarten sind. Dimensionsstruktur und Eignung der CES-D zur Erfassung der Depression bei älteren Menschen wurden an einer Stichprobe von 663 über 75-jährigen Teilnehmern der “Leipziger Langzeitstudie in der Altenbevölkerung” untersucht. Da sich die Annahme der Gültigkeit eines partial-credit-Rasch-Modells sowohl für die Gesamtstichprobe als auch für eine Teilpopulation als zu restriktiv erwies, wurde ein 3- bzw. 4-Klassen-latent-class-Modell für geordnete Kategorien berechnet und die 4-Klassen-Lösung als den Daten angemessen interpretiert: Drei Klassen zeigten sich im Sinne des Konstrukts “Depression” geordnet, eine Klasse enthielt jene Respondenten, deren Antwortmuster auf ein Antwortartefakt hinwiesen. In dieser Befragtenklasse wird der Depressionsgrad offensichtlich überschätzt. Zusammenhänge mit Alter und Mini-Mental-State-Examination-Score werden dargestellt. Nach unseren Ergebnissen muß die CES-D in einer Altenbevölkerung mit Vorsicht eingesetzt werden, der Summenscore sollte nicht verwendet werden.

New Evidence on the Construct Validity of the ASI-3 and the Dimensional Conceptualization of Trait Anxiety Sensitivity From IRT Modeling

2017 ◽  
Vol 33 (3) ◽  
pp. 181-189 ◽  
Author(s):  
Christoph J. Kemper ◽  
Michael Hock
Keyword(s):  
Construct Validity ◽  
Anxiety Sensitivity ◽  
Latent Class ◽  
Dimensional Structure ◽  
Sensitivity Index ◽  
Response Scale ◽  
Established Risk Factor ◽  
Irt Models ◽  
Level Data ◽  
Extreme Response

Abstract. Anxiety Sensitivity (AS) denotes the tendency to fear anxiety-related sensations. Trait AS is an established risk factor for anxiety pathology. The Anxiety Sensitivity Index-3 (ASI-3) is a widely used measure of AS and its three most robust dimensions with well-established construct validity. At present, the dimensional conceptualization of AS, and thus, the construct validity of the ASI-3 is challenged. A latent class structure with two distinct and qualitatively different forms, an adaptive form (normative AS) and a maladaptive form (AS taxon, predisposing for anxiety pathology) was postulated. Item Response Theory (IRT) models were applied to item-level data of the ASI-3 in an attempt to replicate previous findings in a large nonclinical sample (N = 2,603) and to examine possible interpretations for the latent discontinuity observed. Two latent classes with a pattern of distinct responses to ASI-3 items were found. However, classes were indicative of participant’s differential use of the response scale (midpoint and extreme response style) rather than differing in AS content (adaptive and maladaptive AS forms). A dimensional structure of AS and the construct validity of the ASI-3 was supported.

The Solution Strategy as an Indicator of the Developmental Stage of Preschool Children’s Mental-Rotation Ability

2010 ◽  
Vol 31 (2) ◽  
pp. 95-100 ◽  
Author(s):  
Claudia Quaiser-Pohl ◽  
Anna M. Rohe ◽  
Tobias Amberger
Keyword(s):  
Preschool Children ◽  
Mental Rotation ◽  
Latent Class ◽  
Preschool Age ◽  
Stage Model ◽  
Solution Strategy ◽  
Thinking Aloud ◽  
Transition Analysis ◽  
Solution Strategies ◽  
Close Relationship

The solution strategies of preschool children solving mental-rotation tasks were analyzed in two studies. In the first study n = 111 preschool children had to demonstrate their solution strategy in the Picture Rotation Test (PRT) items by thinking aloud; seven different strategies were identified. In the second study these strategies were confirmed by latent class analysis (LCA) with the PRT data of n = 565 preschool children. In addition, a close relationship was found between the solution strategy and children’s age. Results point to a stage model for the development of mental-rotation ability as measured by the PRT, going from inappropriate strategies like guessing or comparing details, to semiappropriate approaches like choosing the stimulus with the smallest angle discrepancy, to a holistic or analytic strategy. A latent transition analysis (LTA) revealed that the ability to mentally rotate objects can be influenced by training in the preschool age.

Identifying Patterns in Complex Field Data

2017 ◽  
Vol 225 (3) ◽  
pp. 268-284 ◽  
Author(s):  
Andrew J. White ◽  
Dieter Kleinböhl ◽  
Thomas Lang ◽  
Alfons O. Hamm ◽  
Alexander L. Gerlach ◽  
...  
Keyword(s):  
Heart Rate ◽  
Panic Disorder ◽  
Latent Class ◽  
Treatment Protocol ◽  
Situational Factors ◽  
Self Report ◽  
Complex Field ◽  
Cluster Assignment ◽  
Experimental Conditions ◽  
Conventional Analysis

Abstract. Ambulatory assessment methods are well suited to examine how patients with panic disorder and agoraphobia (PD/A) undertake situational exposure. But under complex field conditions of a complex treatment protocol, the variability of data can be so high that conventional analytic approaches based on group averages inadequately describe individual variability. To understand how fear responses change throughout exposure, we aimed to demonstrate the incremental value of sorting HR responses (an index of fear) prior to applying averaging procedures. As part of their panic treatment, 85 patients with PD/A completed a total of 233 bus exposure exercises. Heart rate (HR), global positioning system (GPS) location, and self-report data were collected. Patients were randomized to one of two active treatment conditions (standard exposure or fear-augmented exposure) and completed multiple exposures in four consecutive exposure sessions. We used latent class cluster analysis (CA) to cluster heart rate (HR) responses collected at the start of bus exposure exercises (5 min long, centered on bus boarding). Intra-individual patterns of assignment across exposure repetitions were examined to explore the relative influence of individual and situational factors on HR responses. The association between response types and panic disorder symptoms was determined by examining how clusters were related to self-reported anxiety, concordance between HR and self-report measures, and bodily symptom tolerance. These analyses were contrasted with a conventional analysis based on averages across experimental conditions. HR responses were sorted according to form and level criteria and yielded nine clusters, seven of which were interpretable. Cluster assignment was not stable across sessions or treatment condition. Clusters characterized by a low absolute HR level that slowly decayed corresponded with low self-reported anxiety and greater self-rated tolerance of bodily symptoms. Inconsistent individual factors influenced HR responses less than situational factors. Applying clustering can help to extend the conventional analysis of highly variable data collected in the field. We discuss the merits of this approach and reasons for the non-stereotypical pattern of cluster assignment across exposures.

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