Journal of Business and Economic Statistics, ISSN 0735-0015, 2019, pp. 1 - 26
Journal Article
Analytic Methods in Accident Research, ISSN 2213-6657, 09/2016, Volume 11, pp. 1 - 16
Highway accidents are complex events that involve a variety of human responses to external stimuli, as well as complex interactions between the vehicle,...
Statistical and econometric methods | Unobserved heterogeneity | Accident analysis | Accident severity | Statistical methods | Highway safety | Accident likelihood | DRIVER-INJURY SEVERITY | MULTINOMIAL LOGIT | MIXED LOGIT | TRANSPORTATION | ORDERED RESPONSE MODEL | SPATIAL-ANALYSIS | SEAT-BELT USE | SINGLE-VEHICLE CRASHES | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | LATENT CLASS ANALYSIS | FINITE-MIXTURE | RANDOM-PARAMETERS
Statistical and econometric methods | Unobserved heterogeneity | Accident analysis | Accident severity | Statistical methods | Highway safety | Accident likelihood | DRIVER-INJURY SEVERITY | MULTINOMIAL LOGIT | MIXED LOGIT | TRANSPORTATION | ORDERED RESPONSE MODEL | SPATIAL-ANALYSIS | SEAT-BELT USE | SINGLE-VEHICLE CRASHES | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | LATENT CLASS ANALYSIS | FINITE-MIXTURE | RANDOM-PARAMETERS
Journal Article
Journal of Business Research, ISSN 0148-2963, 05/2014, Volume 67, Issue 5, pp. 974 - 982
Multiple facets of perceived value perceptions drive loyalty intentions. However, this value–loyalty link is not uniform for all customers. In fact, the...
Finite mixture modeling | Customer segmentation | Perceived value | Unobserved heterogeneity | SATISFACTION | QUALITY | SERVICE | BUSINESS | MODEL | SCALE | EMPIRICAL BAYES | PERCEPTIONS
Finite mixture modeling | Customer segmentation | Perceived value | Unobserved heterogeneity | SATISFACTION | QUALITY | SERVICE | BUSINESS | MODEL | SCALE | EMPIRICAL BAYES | PERCEPTIONS
Journal Article
International Journal of Hospitality Management, ISSN 0278-4319, 04/2019, Volume 78, pp. 131 - 141
This research examines the relationships between affective and cognitive antecedents and consequences of satisfaction under a market heterogeneity approach. It...
Heterogeneity | Co-creation | Service experience | Segmentation | Consumer behaviour | CONSUMPTION EMOTIONS | PHYSICAL-ENVIRONMENT | CONSUMER SATISFACTION | CUSTOMER SATISFACTION | BEHAVIORAL INTENTIONS | STRUCTURAL EQUATION MODELS | TREATING UNOBSERVED HETEROGENEITY | HOSPITALITY, LEISURE, SPORT & TOURISM | TOURISTS EMOTIONAL EXPERIENCES | Consumer behavior | Museums
Heterogeneity | Co-creation | Service experience | Segmentation | Consumer behaviour | CONSUMPTION EMOTIONS | PHYSICAL-ENVIRONMENT | CONSUMER SATISFACTION | CUSTOMER SATISFACTION | BEHAVIORAL INTENTIONS | STRUCTURAL EQUATION MODELS | TREATING UNOBSERVED HETEROGENEITY | HOSPITALITY, LEISURE, SPORT & TOURISM | TOURISTS EMOTIONAL EXPERIENCES | Consumer behavior | Museums
Journal Article
MIS Quarterly, ISSN 0276-7783, 9/2013, Volume 37, Issue 3, pp. 665 - 694
A large proportion of information systems research is concerned with developing and testing models pertaining to complex cognition, behaviors, and outcomes of...
Research Essay | Validity | Prediction-oriented segmentation | Structural equation modeling | Partial least squares | Formative measures | Unobserved heterogeneity | MEASUREMENT INVARIANCE | MANAGEMENT | structural equation modeling | FORMATIVE MEASUREMENT | MULTIPLE-REGRESSION | COMPUTER SCIENCE, INFORMATION SYSTEMS | RESPONSE-BASED SEGMENTATION | BAYESIAN-ANALYSIS | prediction-oriented segmentation | formative measures | MEASUREMENT ERROR | INFORMATION SCIENCE & LIBRARY SCIENCE | FINITE-MIXTURE | validity | INFORMATION-SYSTEMS | partial least squares | TECHNOLOGY ACCEPTANCE MODEL | TASK INTERDEPENDENCE | Research | Methods | Information systems
Research Essay | Validity | Prediction-oriented segmentation | Structural equation modeling | Partial least squares | Formative measures | Unobserved heterogeneity | MEASUREMENT INVARIANCE | MANAGEMENT | structural equation modeling | FORMATIVE MEASUREMENT | MULTIPLE-REGRESSION | COMPUTER SCIENCE, INFORMATION SYSTEMS | RESPONSE-BASED SEGMENTATION | BAYESIAN-ANALYSIS | prediction-oriented segmentation | formative measures | MEASUREMENT ERROR | INFORMATION SCIENCE & LIBRARY SCIENCE | FINITE-MIXTURE | validity | INFORMATION-SYSTEMS | partial least squares | TECHNOLOGY ACCEPTANCE MODEL | TASK INTERDEPENDENCE | Research | Methods | Information systems
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Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach
Accident Analysis and Prevention, ISSN 0001-4575, 01/2017, Volume 98, pp. 330 - 337
This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying...
Spatial heterogeneity | Conditional autoregressive prior | Bayesian inference | Crash frequency | Unobserved heterogeneity | TRAFFIC CRASHES | TRANSPORTATION | HIERARCHICAL-MODELS | PREDICTION MODELS | LEVEL | ERGONOMICS | SAFETY PERFORMANCE | ROAD NETWORK | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | SENSITIVITY-ANALYSIS | WEIGHTED POISSON REGRESSION | SOCIAL SCIENCES, INTERDISCIPLINARY | RANDOM PARAMETER | INJURY CRASHES | Safety - statistics & numerical data | Spatial Regression | Humans | Accidents, Traffic - statistics & numerical data | Bayes Theorem | Environment Design | Models, Statistical | Florida
Spatial heterogeneity | Conditional autoregressive prior | Bayesian inference | Crash frequency | Unobserved heterogeneity | TRAFFIC CRASHES | TRANSPORTATION | HIERARCHICAL-MODELS | PREDICTION MODELS | LEVEL | ERGONOMICS | SAFETY PERFORMANCE | ROAD NETWORK | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | SENSITIVITY-ANALYSIS | WEIGHTED POISSON REGRESSION | SOCIAL SCIENCES, INTERDISCIPLINARY | RANDOM PARAMETER | INJURY CRASHES | Safety - statistics & numerical data | Spatial Regression | Humans | Accidents, Traffic - statistics & numerical data | Bayes Theorem | Environment Design | Models, Statistical | Florida
Journal Article
The European Journal of Health Economics, ISSN 1618-7598, 11/2018, Volume 19, Issue 8, pp. 1137 - 1148
Labour absenteeism may be detrimental to firms and society because of the economic costs, organizational problems and production cuts that it involves....
Health Economics | Public Health | Public Finance | Political Economy/Economic Policy | Unobserved heterogeneity | J01 | Health Care Management | Absenteeism | J22 | Pharmacoeconomics and Health Outcomes | Medicine & Public Health | Sick leave | Finite mixture model | SICKNESS ABSENCE | INCENTIVES | MODEL | DEMAND | EMPLOYEES | HEALTH POLICY & SERVICES | ECONOMICS | HEALTH | DURATION | Age Factors | Occupational Health | Humans | Middle Aged | Occupations - statistics & numerical data | Sick Leave - statistics & numerical data | Male | Mental Health | Models, Economic | Socioeconomic Factors | Spain | Young Adult | Health Surveys | Adolescent | Sex Factors | Adult | Female | Health Status | Employers | Analysis | Economic models
Health Economics | Public Health | Public Finance | Political Economy/Economic Policy | Unobserved heterogeneity | J01 | Health Care Management | Absenteeism | J22 | Pharmacoeconomics and Health Outcomes | Medicine & Public Health | Sick leave | Finite mixture model | SICKNESS ABSENCE | INCENTIVES | MODEL | DEMAND | EMPLOYEES | HEALTH POLICY & SERVICES | ECONOMICS | HEALTH | DURATION | Age Factors | Occupational Health | Humans | Middle Aged | Occupations - statistics & numerical data | Sick Leave - statistics & numerical data | Male | Mental Health | Models, Economic | Socioeconomic Factors | Spain | Young Adult | Health Surveys | Adolescent | Sex Factors | Adult | Female | Health Status | Employers | Analysis | Economic models
Journal Article
Journal of Econometrics, ISSN 0304-4076, 11/2019
Journal Article
Journal of Travel Research, ISSN 0047-2875, 7/2016, Volume 55, Issue 6, pp. 774 - 788
Despite the growing complexity of structural equation model (SEM) applications in tourism, it is surprising that most applications have estimated these models...
SEM | unobserved heterogeneity | finite mixture model | Bayesian | DISTANCE | QUALITY | COMPONENTS | BAYESIAN-ANALYSIS | RESIDENTS | SATISFACTION | COMMUNITY | STRUCTURAL EQUATION MODELS | FINITE-MIXTURE | HOSPITALITY, LEISURE, SPORT & TOURISM | UNKNOWN NUMBER | Usage | Brand equity | Structural equation modeling | Travel research | Analysis
SEM | unobserved heterogeneity | finite mixture model | Bayesian | DISTANCE | QUALITY | COMPONENTS | BAYESIAN-ANALYSIS | RESIDENTS | SATISFACTION | COMMUNITY | STRUCTURAL EQUATION MODELS | FINITE-MIXTURE | HOSPITALITY, LEISURE, SPORT & TOURISM | UNKNOWN NUMBER | Usage | Brand equity | Structural equation modeling | Travel research | Analysis
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Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures
JOURNAL OF ECONOMETRICS, ISSN 0304-4076, 08/2019, Volume 211, Issue 2, pp. 483 - 506
We propose a method to predict rational counterfactual demand responses from repeated cross-sections. We derive bounds on the distribution of counterfactual...
WARP | CONFIDENCE-INTERVALS | Unobserved heterogeneity | Endogenous expenditures | RESTRICTIONS | INFERENCE | IDENTIFICATION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | Counterfactual demand | NONPARAMETRIC-ESTIMATION | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS | PREFERENCE | CONSUMERS | CONSUMPTION | Marketing research | Consumer spending | Consumption | Elasticity | Consumer behavior
WARP | CONFIDENCE-INTERVALS | Unobserved heterogeneity | Endogenous expenditures | RESTRICTIONS | INFERENCE | IDENTIFICATION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | Counterfactual demand | NONPARAMETRIC-ESTIMATION | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS | PREFERENCE | CONSUMERS | CONSUMPTION | Marketing research | Consumer spending | Consumption | Elasticity | Consumer behavior
Journal Article
Lifetime Data Analysis, ISSN 1380-7870, 10/2019, Volume 25, Issue 4, pp. 712 - 738
Consider lifetimes originating at a series of calendar times $$ t_{1} ,t_{2} , \ldots $$ t 1 , t 2 , … . At a certain time $$ t_{0} $$ t 0 a cross-sectional...
Survival analysis | Statistics for Business, Management, Economics, Finance, Insurance | Statistics for Life Sciences, Medicine, Health Sciences | Operations Research/Decision Theory | Unobserved heterogeneity | Quality Control, Reliability, Safety and Risk | Attenuation | Survivor selection | Statistics, general | Statistics | Current duration
Survival analysis | Statistics for Business, Management, Economics, Finance, Insurance | Statistics for Life Sciences, Medicine, Health Sciences | Operations Research/Decision Theory | Unobserved heterogeneity | Quality Control, Reliability, Safety and Risk | Attenuation | Survivor selection | Statistics, general | Statistics | Current duration
Journal Article
The Review of Economic Studies, ISSN 0034-6527, 1/2011, Volume 78, Issue 1, pp. 293 - 327
In many procurement auctions, the bidders' unobserved costs depend both on a common shock and on idiosyncratic private information. Assuming a multiplicative...
Procurement | Cost estimation models | Cost estimates | Auctions | Cost allocation | Eigenfunctions | Random variables | Estimators | Consistent estimators | Cost functions | Highway procurement | Unobserved auction heterogeneity | First-price auctions | PRIVATE VALUES | CONDITIONAL-INDEPENDENCE | EMPIRICAL-MODELS | COMPETITION | 1ST-PRICE AUCTIONS | PROCUREMENT | ECONOMICS | NONPARAMETRIC DECONVOLUTION
Procurement | Cost estimation models | Cost estimates | Auctions | Cost allocation | Eigenfunctions | Random variables | Estimators | Consistent estimators | Cost functions | Highway procurement | Unobserved auction heterogeneity | First-price auctions | PRIVATE VALUES | CONDITIONAL-INDEPENDENCE | EMPIRICAL-MODELS | COMPETITION | 1ST-PRICE AUCTIONS | PROCUREMENT | ECONOMICS | NONPARAMETRIC DECONVOLUTION
Journal Article
The Stata Journal, ISSN 1536-867X, 12/2018, Volume 18, Issue 4, pp. 844 - 862
Dynamic random-effects probit models are increasingly applied in many disciplines to study dynamics of persistence in dichotomous outcomes. Despite the...
Xtpdyn | Dynamic panel models | Probat | Unobserved heterogeneity | Dynamic randomeffects probit | State dependence | St0543 | state dependence | probat | INITIAL CONDITIONS | st0543 | unobserved heterogeneity | xtpdyn | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | dynamic panel models | dynamic random-effects probit
Xtpdyn | Dynamic panel models | Probat | Unobserved heterogeneity | Dynamic randomeffects probit | State dependence | St0543 | state dependence | probat | INITIAL CONDITIONS | st0543 | unobserved heterogeneity | xtpdyn | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | dynamic panel models | dynamic random-effects probit
Journal Article
Statistics in Medicine, ISSN 0277-6715, 01/2019, Volume 38, Issue 2, pp. 269 - 288
Survival analysis is used in the medical field to identify the effect of predictive variables on time to a specific event. Generally, not all variation of...
correlated frailty | competing risks | unobserved heterogeneity | EM algorithm | multicenter | SURVIVAL | REGRESSION | MEDICINE, RESEARCH & EXPERIMENTAL | MEDICAL INFORMATICS | STATISTICS & PROBABILITY | DEATH | TABLES | SUBDISTRIBUTION | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | PROPORTIONAL HAZARDS MODEL | MATHEMATICAL & COMPUTATIONAL BIOLOGY | Models | Investigations | Algorithms
correlated frailty | competing risks | unobserved heterogeneity | EM algorithm | multicenter | SURVIVAL | REGRESSION | MEDICINE, RESEARCH & EXPERIMENTAL | MEDICAL INFORMATICS | STATISTICS & PROBABILITY | DEATH | TABLES | SUBDISTRIBUTION | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | PROPORTIONAL HAZARDS MODEL | MATHEMATICAL & COMPUTATIONAL BIOLOGY | Models | Investigations | Algorithms
Journal Article
Quantitative Economics, ISSN 1759-7323, 11/2016, Volume 7, Issue 3, pp. 781 - 820
We study the treatment effect of grade retention using a panel of French junior high‐school students, taking unobserved heterogeneity and the endogeneity of...
treatment effects | finite mixtures of normal distributions | Secondary education | unobserved heterogeneity | C23 | class‐size effects | C36 | C38 | grade retention | class-size effects | HIGH-SCHOOL | CHOICES | IDENTIFICATION | CLASS SIZE | DISTRIBUTIONS | NONCOGNITIVE SKILL FORMATION | POLICY | STUDENT-ACHIEVEMENT | MODELS | ECONOMICS | TECHNOLOGY | Retention | Economic models | School dropouts
treatment effects | finite mixtures of normal distributions | Secondary education | unobserved heterogeneity | C23 | class‐size effects | C36 | C38 | grade retention | class-size effects | HIGH-SCHOOL | CHOICES | IDENTIFICATION | CLASS SIZE | DISTRIBUTIONS | NONCOGNITIVE SKILL FORMATION | POLICY | STUDENT-ACHIEVEMENT | MODELS | ECONOMICS | TECHNOLOGY | Retention | Economic models | School dropouts
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Identifying and treating unobserved heterogeneity with FIMIX-PLS: Part II – A case study
European Business Review, ISSN 0955-534X, 03/2016, Volume 28, Issue 2, pp. 208 - 224
Journal Article
Journal of Econometrics, ISSN 0304-4076, 09/2015, Volume 188, Issue 1, pp. 236 - 249
The data generating process (DGP) for generic dynamic panel data consists of a law of state dynamics , a selection or attrition rule , and an initial condition...
Heterogeneity | Initial conditions problem | Dynamic panel data | Selection | NONPARAMETRIC IDENTIFICATION | INITIAL CONDITIONS | ATTRITION | DISCRETE-CHOICE MODELS | CROSS-SECTION | PROPORTIONAL HAZARD MODEL | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | TIME MODELS | SOCIAL SCIENCES, MATHEMATICAL METHODS | UNOBSERVED HETEROGENEITY | ECONOMICS | MOMENT RESTRICTIONS | DURATION
Heterogeneity | Initial conditions problem | Dynamic panel data | Selection | NONPARAMETRIC IDENTIFICATION | INITIAL CONDITIONS | ATTRITION | DISCRETE-CHOICE MODELS | CROSS-SECTION | PROPORTIONAL HAZARD MODEL | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | TIME MODELS | SOCIAL SCIENCES, MATHEMATICAL METHODS | UNOBSERVED HETEROGENEITY | ECONOMICS | MOMENT RESTRICTIONS | DURATION
Journal Article