A comparison of the mixed logit and latent class methods for crash severity analysis

2014 ◽  
Vol 3-4 ◽  
pp. 11-27 ◽  
Author(s):  
Donald Mathew Cerwick ◽  
Konstantina Gkritza ◽  
Mohammad Saad Shaheed ◽  
Zachary Hans
Keyword(s):  
Latent Class ◽  
Mixed Logit ◽  
Crash Severity ◽  
Latent Class Methods

Preferences Toward COVID-19 Diagnostic Testing Features: Results From a National Cross-Sectional Survey

2021 ◽  
pp. 089011712110340
Author(s):  
Bhagyashree Katare ◽  
Shuoli Zhao ◽  
Joel Cuffey ◽  
Maria I. Marshall ◽  
Corinne Valdivia
Keyword(s):  
Logit Model ◽  
Nasal Swab ◽  
Latent Class ◽  
Diagnostic Testing ◽  
Mixed Logit ◽  
Monetary Incentive ◽  
Monetary Incentives ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Nationally Representative

Purpose: Describe preferences toward COVID-19 testing features (method, location, hypothetical monetary incentive) and simulate the effect of monetary incentives on willingness to test. Design: Online cross-sectional survey administered in July 2020. Subjects: 1,505 nationally representative U.S. respondents. Measures: Choice of preferred COVID-19 testing options in discrete choice experiment. Options differed by method (nasal-swab, saliva), location (hospital/clinic, drive-through, at-home), and monetary incentive ($0, $10, $20). Analysis: Latent class conditional logit model to classify preferences, mixed logit model to simulate incentive effectiveness. Results: Preferences were categorized into 4 groups: 34% (n = 517) considered testing comfort (saliva versus nasal swab) most important, 27% (n = 408) were willing to trade comfort for monetary incentives, 19% (n = 287) would only test at convenient locations, 20% (n = 293) avoided testing altogether. Relative to no monetary incentives, incentives of $100 increased the percent of testing avoiders (16%) and convenience seekers (70%) that were willing to test. Conclusion: Preferences toward different COVID-19 testing features vary, highlighting the need to match testing features with individuals to monitor the spread of COVID-19.

Attribute Non-Attendance and Consumer Preferences for Online Food Products in Germany

2020 ◽  
Vol 69 (1) ◽  
pp. 31-48
Author(s):  
P. Christoph Richartz ◽  
Lukas Kornher ◽  
Awudu Abdulai
Keyword(s):  
Latent Class ◽  
Consumer Preferences ◽  
Mixed Logit ◽  
Meat Products ◽  
Food Product ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Significant Heterogeneity ◽  
Processing Strategies ◽  
Class Models

In this article, we apply a choice experiment meth-od to examine consumers’ preferences for online food product attributes, using survey data for German consumers for meat products. We use both mixed logit and latent class models to analyze preference heterogeneity and sources of heterogeneity, as well as endogenous attribute attendance models to account for consumers’ attribute processing strategies. The empirical results reveal significant heterogeneity in preferences for online meat attributes among consumers. We also find that consumers’ willingness to pay estimates are highly influenced by their attribute processing strategies.

Exploring Differences in Preference Heterogeneity Representation and Their Influence in Product Family Design

2011 ◽  
Author(s):  
Eric Sullivan ◽  
Scott Ferguson ◽  
Joseph Donndelinger
Keyword(s):  
Logit Model ◽  
Latent Class ◽  
Latent Class Model ◽  
Mixed Logit ◽  
Multinomial Logit Model ◽  
Hierarchical Bayes ◽  
Product Line ◽  
Combinatorial Design ◽  
Preference Heterogeneity ◽  
Target Market

When using conjoint studies for market-based design, two model types can be fit to represent the heterogeneity present in a target market, discrete or continuous. In this paper, data from a choice-based conjoint study with 2275 respondents is analyzed for a 19-attribute combinatorial design problem with over 1 billion possible product configurations. Customer preferences are inferred from the choice task data using both representations of heterogeneity. The hierarchical Bayes mixed logit model exemplifies the continuous representation of heterogeneity, while the latent class multinomial logit model corresponds to the discrete representation. Product line solutions are generated by each of these model forms and are then explored to determine why differences are observed in both product solutions and market share estimates. These results reveal some potential limitations of the Latent Class model in the masking of preference heterogeneity. Finally, the ramifications of these results on the market-based design process are discussed.

Smallholder preferences and willingness-to-pay measures for microcredit

2018 ◽  
Vol 10 (3) ◽  
pp. 462-481 ◽  
Author(s):  
Zhao Ding ◽  
Awudu Abdulai
Keyword(s):  
Willingness To Pay ◽  
Interest Rates ◽  
Latent Class ◽  
Smallholder Farmers ◽  
Mixed Logit ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Content Type ◽  
Lower Interest Rate ◽  
Class Models

Purpose The purpose of this paper is to examine smallholders’ preferences and willingness to pay for microcredit products with varying attribute combinations, in order to contribute to the debate on the optimal design of rural microcredit. Design/methodology/approach Data used in this study are based on a discrete choice experiment from 552 randomly selected respondents. Mixed logit and latent class models are estimated to examine the choice probability and sources of preference heterogeneity. Endogenous attribute attendance models are applied to account for attribute non-attendance (ANA) phenomenon, focusing on separate non-attendance probability as well as joint non-attendance probability. Findings The results demonstrate that preference heterogeneity and ANA exist in the smallholder farmers’ microcredit choices. Averagely, smallholder farmers prefer longer credit period, smaller credit size, lower transaction costs and lower interest rate. Guarantor collateral method and installment repayment positively affect their preferences as well. Moreover, respondents are found to be willing to pay more for the attributes they consider important. The microcredit providers are able to attract new customers under the current interest rates, if the combination of attributes is appropriately adjusted. Originality/value This study contributes to the debate by assessing the preference trade-off of different microcredit attributes more comprehensively than in previous analyses, by taking preference heterogeneity and ANA into account.

scholarly journals Evaluating and optimizing the use of diagnostics during epidemics: Application to the 2017 plague outbreak in Madagascar

2021 ◽  
Author(s):  
Quirine Bosch ◽  
Voahangy Andrianaivoarimanana ◽  
Beza Ramasindrazana ◽  
Guillain Mikaty ◽  
Rado JL Rakotonanahary ◽  
...  
Keyword(s):  
Yersinia Pestis ◽  
Test Performance ◽  
Diagnostic Tests ◽  
Latent Class ◽  
Clinical Presentation ◽  
Analytical Framework ◽  
Rural Settings ◽  
Latent Class Methods ◽  
Diagnostic Outcomes ◽  
Case Classification

During outbreaks, the lack of diagnostic “gold standard” can mask the true burden of infection in the population and hamper the allocation of resources required for control. Here, we present an analytical framework to evaluate and optimize the use of diagnostics when multiple yet imperfect diagnostic tests are available. We apply it to laboratory results of 2,136 samples, analyzed with three diagnostic tests (based on up to seven diagnostic outcomes), collected during the 2017 pneumonic (PP) and bubonic plague (BP) outbreak in Madagascar, which was unprecedented both in the number of notified cases, clinical presentation, and spatial distribution. The extent of this outbreaks has however remained unclear due to non-optimal assays. Using latent class methods, we estimate that 7%-15% of notified cases were Yersinia pestis-infected. Overreporting was highest during the peak of the outbreak and lowest in the rural settings endemic to Yersinia pestis. Molecular biology methods offered the best compromise between sensitivity and specificity. The specificity of the rapid diagnostic test was relatively low (PP: 82%, BP: 85%), particularly for use in contexts with large quantities of misclassified cases. Comparison with data from a subsequent seasonal Yersinia pestis outbreak in 2018 reveal better test performance (BP: specificity 99%, sensitivity: 91%), indicating that factors related to the response to a large, explosive outbreak may well have affected test performance. We used our framework to optimize the case classification and derive consolidated epidemic trends. Our approach may help reduce uncertainties in other outbreaks where diagnostics are imperfect.

scholarly journals Decisión de localización del hogar en España. Modelo de clases latentes vs. modelo mixto.

2019 ◽  
Vol 37 (3) ◽  
pp. 214
Author(s):  
Anastasia Hernández Alemán
Keyword(s):  
Latent Class ◽  
Choice Model ◽  
Latent Class Model ◽  
Mixed Logit ◽  
Noise Pollution ◽  
Individual Characteristics ◽  
Mixed Logit Models ◽  
Or Groups ◽  
Household Preference ◽  
Unobservable Heterogeneity

In this work the unobservable heterogeneity respect to the choice of household’s residential location is analyzed, considering three alternatives: urban area, interurban area and rural area. It is employed latent class choice model to represent this behavior and the results are compared with the multinomial and mixed logit models. The more flexible structure of the latent class model allows us more deeply into the analysis of unobservable heterogeneity with respect to the more limited analysis of the randomness of the parameters of the mixed logit model. The empirical results indicate two classes or groups of households with differentiated behaviors regarding to the decision of location and associated to different lifestyles. Thus, certain attributes of the location of the dwelling, such as noise, pollution or delinquency, have an effect on household preference in a different way according to the class of belonging. Also, individual characteristics of the household’s head, such as age, gender or educational level, have a different impact on the preference for location according to the class of belonging. The results allow us to distinguish two lifestyles associated with each class or group of preference: suburban and urban.

scholarly journals Drivers and Barriers Influencing the Willingness to Adopt Technologies for Variable Rate Application of Fertiliser in Lower Austria

Agronomy ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1965
Author(s):  
Julia Blasch ◽  
Francesco Vuolo ◽  
Laura Essl ◽  
Bianca van der Kroon
Keyword(s):  
Choice Experiment ◽  
Latent Class ◽  
Mixed Logit ◽  
Farming System ◽  
Farm Size ◽  
Variable Rate ◽  
Variable Rate Application ◽  
Willingness To Adopt ◽  
Technological Level ◽  
Latent Class Logit

Even though a broad range of technologies for variable rate application of nitrogen fertiliser is available, there are hardly any documented cases of their use in Austria. In this study, the drivers and barriers of adoption have been investigated. A survey of 242 farmers in Lower Austria was conducted. The survey covered the farmers’ economic situation, concerns, and expectations regarding the future of their farms and their interest in precision farming technologies. A choice experiment was included in the survey to elicit farmers’ preferences for different features of variable rate application technologies. A series of multinomial logit, mixed logit and latent class logit models were run to analyze the choice experiment. Most farmers were interested in variable rate application, whereas technology costs, yield and environmental improvements were found to be important drivers of adoption. Also, farm size, farming system, technological level and network activities seem to play an important role in the uptake of variable rate application technologies.

scholarly journals Integrated Model of Joint Residence-Workplace Location Choice and Commute Behavior Using Latent Class and Mixed Logit Methods

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Pengpeng Jiao ◽  
Meiqi Liu ◽  
Jin Guo
Keyword(s):  
Latent Class ◽  
Choice Model ◽  
Location Choice ◽  
Rapid Development ◽  
Latent Class Model ◽  
Mixed Logit ◽  
Integrated Model ◽  
Model Framework ◽  
Class Model ◽  
Residence Location

With the rapid development of urbanization and motorization, urban commute trips are becoming increasingly serious due to the unbalanced distribution of residence and workplace land-use types in most Chinese cities. To explore the inherent interrelations among residence location, workplace, and commute trip, an integrated model framework of joint residence-workplace location choice and commute behavior is put forward based on the personal trip survey data of Beijing in 2005. First, to extract households’ different choice characteristics, this paper presents a latent class model, clusters all households into several groups, and analyzes the conditional probability of each group. Second, the paper integrates the residence location and workplace together as the joint choice alternative, employs the socioeconomic factors, individual attributes, household attributes, and trip characteristics as explanatory variables, and formulates the joint residence-workplace location choice model using mixed logit method. Estimations of the latent class model show that four latent groups fit the data best. Further results of the joint residence-workplace location choice model indicate that there exist significantly different choice characteristics in each latent group. Generally, the integrated model framework outperforms traditional location choice methods.

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