A latent class approach to dealing with respondent uncertainty in a stated choice survey for fare simplification on bus journeys

2013 ◽  
Vol 9 (6) ◽  
pp. 473-493 ◽  
Author(s):  
Stephane Hess ◽  
Jeremy Shires ◽  
Peter Bonsall
Keyword(s):  
Latent Class ◽  
Stated Choice ◽  
Respondent Uncertainty

scholarly journals Análisis econométrico de la heterogeneidad de las preferencias de los individuos: Aplicación a la valoración económica de la conservación del paisaje agrícola de montaña

2011 ◽  
Vol 8 (1) ◽  
pp. 103 ◽  
Author(s):  
Sergio Colombo ◽  
Nick Hanley
Keyword(s):  
Latent Class ◽  
Random Parameter ◽  
Choice Models ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Stated Choice ◽  
Empirical Application ◽  
Random Parameter Logit ◽  
Class Models

The need to account for respondents’ preference heterogeneity in stated choice models has motivated researchers to apply random parameter logit and latent class models. In this paper we compare these three alternative ways of incorporating preference heterogeneity in stated choice models and evaluate how the choice of model affects welfare estimates in a given empirical application. Finally, we discuss what criteria to follow to decide which approach is most appropriate.

scholarly journals The Influence of Urban Park Attributes on User Preferences: Evaluation of Virtual Parks in an Online Stated-Choice Experiment

2020 ◽  
Vol 18 (1) ◽  
pp. 212
Author(s):  
Esther van Vliet ◽  
Gamze Dane ◽  
Minou Weijs-Perrée ◽  
Eveline van Leeuwen ◽  
Mayke van Dinter ◽  
...  
Keyword(s):  
Choice Experiment ◽  
Latent Class ◽  
Social Activity ◽  
Urban Parks ◽  
Well Being ◽  
User Preferences ◽  
Preference Heterogeneity ◽  
Urban Park ◽  
Stated Choice ◽  
Stated Choice Experiment

Urban green areas, such as parks, are becoming increasingly important in densifying cities. Urban parks encourage physical and social activity, recreation and relaxation, and thus eventually promote people’s well-being. The aim of the current study is to examine which urban park attributes influence the preferences of park users, in order to offer recommendations regarding how urban parks of quality can be designed. To elicit the preferences of park visitors we designed an online stated-choice experiment. Seven park attributes, in particular the number and composition of trees and the presence of benches, side paths, a playground, litter, and flowers, were manipulated in a virtual park. In an online stated-choice task, videos of these park alternatives were presented and the preferences of 697 participants were measured. It is found that especially the number of trees and the presence of flowerbeds, particularly with a diversity of flowers, influenced participants’ preferences. The presence of many benches and a playground were valued as well, but to a lesser extent. The presence of litter was found to be less troublesome than expected. Alternatives with all trees placed in one cluster were disliked. Moreover, significant standard deviations were found for the presence of side paths, a playground, and the absence of litter, which indicates that preference heterogeneity for these attributes exist. In a latent class analysis, two groups were identified, namely a Nature-loving group, who mainly valued the trees and the flowers, and an Amenity-appreciating group, who valued almost all attributes. It can be concluded that natural elements and a variety of flower species are important in an urban park, while facilities are evaluated differently by different groups of people. These findings may support park designers and policymakers in decision-making. Moreover, it illustrates the usefulness of creating a virtual park in environmental preference research.

scholarly journals Congestion management in protected areas: accounting for respondents’ inattention and preference heterogeneity in stated choice data

2018 ◽  
Vol 46 (5) ◽  
pp. 834-861 ◽  
Author(s):  
Mara Thiene ◽  
Cristiano Franceschinis ◽  
Riccardo Scarpa
Keyword(s):  
Protected Areas ◽  
Latent Class ◽  
Congestion Management ◽  
Model Fit ◽  
Destination Choice ◽  
Preference Heterogeneity ◽  
Stated Choice ◽  
Random Parameters ◽  
Choice Data ◽  
Traditional Approaches

Abstract Congestion levels in protected areas can be predicted by destination choice models estimated from choice data. There is growing evidence of subjects’ inattention to attributes in choice experiments. We estimate an attribute non-attendance latent class–random parameters model (LC–RPL) that jointly handles inattention and preference heterogeneity. We use data from a choice experiment designed to elicit visitors’ preferences towards sustainable management of a protected area in the Italian Alps. Results show that the LC–RPL model produces improvements in model fit and reductions in the implied rate of inattention, as compared to traditional approaches. Implications of results for park management authorities are discussed.

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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