Articles de revues : « Tobit models »

1

Brockwell, A. E., et N. H. Chan. « Long-memory dynamic Tobit models ». Journal of Forecasting 25, n^o 5 (août 2006) : 351–67. http://dx.doi.org/10.1002/for.992.

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Bauer, Thomas K., et Mathias Sinning. « Blinder–Oaxaca decomposition for Tobit models ». Applied Economics 42, n^o 12 (mai 2010) : 1569–75. http://dx.doi.org/10.1080/00036840701721612.

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Smith, Douglas A., et Robert Brame. « Tobit Models in Social Science Research ». Sociological Methods & ; Research 31, n^o 3 (février 2003) : 364–88. http://dx.doi.org/10.1177/0049124102239080.

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Sigelman, Lee, et Langche Zeng. « Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models ». Political Analysis 8, n^o 2 (16 décembre 1999) : 167–82. http://dx.doi.org/10.1093/oxfordjournals.pan.a029811.

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Political scientists are making increasing use of the Tobit and Heckit models. This paper addresses some common problems in the application and interpretation of these models. Through numerical experiments and reanalysis of data from a study by Romer and Snyder (1994), we illustrate the consequences of using the standard Tobit model, which assumes a censoring point at zero, when the zeros are not due to censoring mechanisms or when actual censoring is not at zero. In the latter case, we also show that Greene's (1981) well-known results on the direction and size of the bias of the OLS estimator in the standard Tobit model do not necessarily hold. Because the Heckit model is often used as an alternative to Tobit, we examine its assumptions and discuss the proper interpretation of the Heckit/Tobit estimation results using Grier and co-workers' (1994) Heckit model of campaign contribution data. Sensitivity analyses of the Heckit estimation results suggest some conclusions rather different from those reached by Grier et al.

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Lee, Lung-fei. « Estimation of dynamic and ARCH Tobit models ». Journal of Econometrics 92, n^o 2 (octobre 1999) : 355–90. http://dx.doi.org/10.1016/s0304-4076(98)00095-5.

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Wei, Steven X. « A bayesian approach to dynamic tobit models ». Econometric Reviews 18, n^o 4 (janvier 1999) : 417–39. http://dx.doi.org/10.1080/07474939908800353.

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Kliber, Paweł, et Artur Stefański. « Econometric Models in Resident Value of Investment ». Oeconomia Copernicana 4, n^o 3 (30 septembre 2013) : 49–63. http://dx.doi.org/10.12775/oec.2013.022.

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The aim of the study is to analyze what is the impact of: analyze period, resident value estimation method, discount rate and economic sector of the investor on the level of resident value to initial value of investment ratio. In the article, basing on 43 investments made by investors form MSP sector whose purpose was to purchase truck car of capacity to 3,5t, four econometric models were prepared: logit, probit, tobit, and logit-tobit to explain the dependence described in the aim of the study. All models are statistically important. In all models only one independent variable is always statistically important – analyze period. The longer analyze period is, the smaller resident value to initial value of investment ratio is. In order to compare models: MSE, RMSE, MAE, MAPE ratios were used. The best adaptation to data was observed when logit-tobit model is used

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Guo, Yanyong, Zhibin Li et Tarek Sayed. « Analysis of Crash Rates at Freeway Diverge Areas using Bayesian Tobit Modeling Framework ». Transportation Research Record : Journal of the Transportation Research Board 2673, n^o 4 (21 mars 2019) : 652–62. http://dx.doi.org/10.1177/0361198119837219.

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The goal of this study is to evaluate the impact of various risk factors on crash rates at freeway diverge areas. Crash rates data for a three-year period from 367 freeway diverge areas were used for analysis. Four candidate Tobit models were developed and compared under the Bayesian framework: a traditional Tobit model; a random parameters Tobit (RP-Tobit) model; a grouped random parameters Tobit (GRP-Tobit) model; and a random intercept Tobit (RI-Tobit). The results showed that the RP-Tobit model performs best with highest value of Rd2 as well as lowest Mean Absolute Deviance (MAD) and Deviance Information Criteria (DIC), indicating the importance of accounting for unobserved heterogeneity to improve the model fit. Both the GRP-Tobit and the RI-Tobit models provide better performance than the traditional Tobit model. The model results showed that crash rates at freeway diverge areas were positively associated with mainline annual average daily traffic (AADT) and negatively associated with ramp AADT, indicating the different mechanisms of the impact of traffic volume on crash rates at freeway diverge areas. Lane-balanced design and high speed limits at freeway diverge areas have a negative effect on crash rates. The number of lanes on mainline and ramp length have significant heterogeneous effects on crash rates across observations. The RP-Tobit model provides a more comprehensive understanding of the heterogeneous effects of risk factors on crash rates across observations.

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Powell, James L. « Symmetrically Trimmed Least Squares Estimation for Tobit Models ». Econometrica 54, n^o 6 (novembre 1986) : 1435. http://dx.doi.org/10.2307/1914308.

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Flood, Lennart, et Urban Gråsjö. « A Monte Carlo simulation study of Tobit models ». Applied Economics Letters 8, n^o 9 (septembre 2001) : 581–84. http://dx.doi.org/10.1080/13504850010027581.

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Lee, Seung Ju, Yun Hwan Kim et Byung Ho Park. « Developing the Pedestrian Accident Models Using Tobit Model ». Journal of the Korean Society of Road Engineers 16, n^o 3 (16 juin 2014) : 101–7. http://dx.doi.org/10.7855/ijhe.2014.16.3.101.

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Zhao, Kaifeng, et Heng Lian. « Bayesian Tobit quantile regression with single-index models ». Journal of Statistical Computation and Simulation 85, n^o 6 (2 janvier 2014) : 1247–63. http://dx.doi.org/10.1080/00949655.2013.873041.

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Barros, Michelli, Manuel Galea, Víctor Leiva et Manoel Santos-Neto. « Generalized Tobit models : diagnostics and application in econometrics ». Journal of Applied Statistics 45, n^o 1 (27 décembre 2016) : 145–67. http://dx.doi.org/10.1080/02664763.2016.1268572.

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Kooreman, Peter. « Alternative specification tests for Tobit and related models ». Economics Letters 21, n^o 1 (janvier 1986) : 31–33. http://dx.doi.org/10.1016/0165-1765(86)90116-3.

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Sánchez-Peñalver, Alfonso. « Estimation methods in the presence of corner solutions ». Stata Journal : Promoting communications on statistics and Stata 19, n^o 1 (mars 2019) : 87–111. http://dx.doi.org/10.1177/1536867x19830893.

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In this article, I introduce a new command, nehurdle, that collects maximum likelihood estimators for linear, exponential, homoskedastic, and heteroskedastic tobit; truncated hurdle; and type II tobit models that involve explained variables with corner solutions. I review what a corner solution is as well as the assumptions of the mentioned models.

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Aguero-Valverde, Jonathan. « Bayesian Hierarchical Tobit Models : an application to travel distance analysis ». Revista Ingeniería 27, n^o 1 (18 mai 2017) : 97. http://dx.doi.org/10.15517/jte.v27i1.27196.

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El objetivo de los modelos de distancia de viaje es entender el comportamiento de viajede los usuarios, de forma tal que se puedan implementar políticas para reducir la distancia de viaje y, con esto, externalidades del transporte tales como contaminación del aire, congestión y accidentes. Los modelos Bayesianos Jerárquicos ofrecen una metodología flexible para analizar el comportamiento de viaje al permitir el estudio tanto de las decisiones de corto plazo de la actividad y las selecciones de viaje así como las decisiones de largo plazo como la localización de la vivienda y el lugar de trabajo. Como la distancia de viaje está censurada en cero para una proporción importante de los datos, los parámetros obtenidos por medio de regresiones lineales convencionales están sesgados. Estimaciones no sesgadas de los parámetros pueden ser obtenidas usando modelos Tobit. El propósito de este artículo es demostrar la aplicación de modelos Tobit Bayesianos jerárquicos al análisis de la distancia de viaje, considerando la naturaleza multinivel y censurada de los datos.Los resultados muestran que el modelo Tobit Bayesiano jerárquico tiene un desempeñosignificativamente mejor que el modelo no jerárquico al medir la bondad de ajuste la Devianza t el Criterio de Información de la Devianza. Más aún, la varianza es estadísticamente muy significativa tanto para el nivel individual como para el nivel de ubicación, lo cual demuestra laimportancia de usar una metodología multinivel.

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Huang, Hailin, Jizi Shangguan, Yuanzhang Li et Hua Liang. « Bi-level variable selection in high-dimensional Tobit models ». Statistics and Its Interface 13, n^o 2 (2020) : 151–56. http://dx.doi.org/10.4310/sii.2020.v13.n2.a1.

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Yang, Chao, Lung-fei Lee et Xi Qu. « Tobit models with social interactions : Complete vs incomplete information ». Regional Science and Urban Economics 73 (novembre 2018) : 30–50. http://dx.doi.org/10.1016/j.regsciurbeco.2018.07.007.

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Honoré, Bo E., Ekaterini Kyriazidou et J. L. Powell. « Estimation of tobit-type models with individual specific effects ». Econometric Reviews 19, n^o 3 (janvier 2000) : 341–66. http://dx.doi.org/10.1080/07474930008800476.

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Zuehlke, Thomas W. « Use of quadratic terms in Type 2 Tobit models ». Applied Economics 49, n^o 17 (27 août 2016) : 1706–14. http://dx.doi.org/10.1080/00036846.2016.1223831.

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Bradic, Jelena, et Jiaqi Guo. « Generalized M-estimators for high-dimensional Tobit I models ». Electronic Journal of Statistics 13, n^o 1 (2019) : 582–645. http://dx.doi.org/10.1214/18-ejs1463.

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Brown, Judith E., et Peter K. Dunn. « Comparisons of Tobit, Linear, and Poisson-Gamma Regression Models ». Sociological Methods & ; Research 40, n^o 3 (29 juillet 2011) : 511–35. http://dx.doi.org/10.1177/0049124111415370.

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Holden, Darryl. « Testing for heteroskedasticity in the tobit and probit models ». Journal of Applied Statistics 38, n^o 4 (avril 2011) : 735–44. http://dx.doi.org/10.1080/02664760903563684.

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Dagne, Getachew A. « Piecewise Growth Mixture Tobit Models : Application to AIDS Studies ». Journal of Biopharmaceutical Statistics 25, n^o 6 (28 janvier 2015) : 1339–52. http://dx.doi.org/10.1080/10543406.2014.1002363.

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Dagne, Getachew A. « Bayesian segmental growth mixture Tobit models with skew distributions ». Computational Statistics 31, n^o 1 (5 septembre 2015) : 121–37. http://dx.doi.org/10.1007/s00180-015-0620-8.

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Sigrist, Fabio, et Christoph Hirnschall. « Grabit : Gradient tree-boosted Tobit models for default prediction ». Journal of Banking & ; Finance 102 (mai 2019) : 177–92. http://dx.doi.org/10.1016/j.jbankfin.2019.03.004.

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Wang, Wei, et Michael E. Griswold. « Natural interpretations in Tobit regression models using marginal estimation methods ». Statistical Methods in Medical Research 26, n^o 6 (1 septembre 2015) : 2622–32. http://dx.doi.org/10.1177/0962280215602716.

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The Tobit model, also known as a censored regression model to account for left- and/or right-censoring in the dependent variable, has been used in many areas of applications, including dental health, medical research and economics. The reported Tobit model coefficient allows estimation and inference of an exposure effect on the latent dependent variable. However, this model does not directly provide overall exposure effects estimation on the original outcome scale. We propose a direct-marginalization approach using a reparameterized link function to model exposure and covariate effects directly on the truncated dependent variable mean. We also discuss an alternative average-predicted-value, post-estimation approach which uses model-predicted values for each person in a designated reference group under different exposure statuses to estimate covariate-adjusted overall exposure effects. Simulation studies were conducted to show the unbiasedness and robustness properties for both approaches under various scenarios. Robustness appears to diminish when covariates with substantial effects are imbalanced between exposure groups; we outline an approach for model choice based on information criterion fit statistics. The methods are applied to the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort study to assess associations between obesity and cognitive function in the non-Hispanic white participants.

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Lee, Seung Ju, Jin Kang Lim et Byung Ho Park. « Developing the Pedestrian Accident Models of Intersections using Tobit Model ». Journal of the Korean Society of Safety 29, n^o 5 (31 octobre 2014) : 154–59. http://dx.doi.org/10.14346/jkosos.2014.29.5.154.

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Xiao, L. Q., B. Hou, Z. F. Wang et Y. H. Wu. « Random weighting approximation for Tobit regression models with longitudinal data ». Computational Statistics & ; Data Analysis 79 (novembre 2014) : 235–47. http://dx.doi.org/10.1016/j.csda.2014.05.020.

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Sayers, Adrian, Michael R. Whitehouse, Andrew Judge, Alex J. MacGregor, Ashley W. Blom et Yoav Ben-Shlomo. « Analysis of change in patient-reported outcome measures with floor and ceiling effects using the multilevel Tobit model : a simulation study and an example from a National Joint Register using body mass index and the Oxford Hip Score ». BMJ Open 10, n^o 8 (août 2020) : e033646. http://dx.doi.org/10.1136/bmjopen-2019-033646.

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ObjectivesThis study has three objectives. (1) Investigate the association between body mass index (BMI) and the efficacy of primary hip replacement using a patient-reported outcome measure (PROMs) with a measurement floor and ceiling, (2) Explore the performance of different estimation methods to estimate change in PROMs score following surgery using a simulation study and real word data where data has measurement floors and ceilings and (3) Lastly, develop guidance for practising researchers on the analysis of PROMs in the presence of floor and ceiling effects.DesignSimulation study and prospective national medical device register.SettingNational Register of Joint Replacement and Medical Devices.MethodsUsing a Monte Carlo simulation study and data from a national joint replacement register (162 513 patients with pre- and post-surgery PROMs), we investigate simple approaches for the analysis of outcomes with floor and ceiling effects that are measured at two occasions: linear and Tobit regression (baseline adjusted analysis of covariance, change-score analysis, post-score analysis) in addition to linear and multilevel Tobit models.Primary outcomeThe primary outcome of interest is change in PROMs from pre-surgery to 6 months post-surgery.ResultsAnalysis of data with floor and ceiling effects with models that fail to account for these features induce substantial bias. Single-level Tobit models only correct for floor or ceiling effects when the exposure of interest is not associated with the baseline score. In observational data scenarios, only multilevel Tobit models are capable of providing unbiased inferences.ConclusionsInferences from pre- post-studies that fail to account for floor and ceiling effects may induce spurious associations with substantial risk of bias. Multilevel Tobit models indicate the efficacy of total hip replacement is independent of BMI. Restricting access to total hip replacement based on a patients BMI can not be supported by the data.

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Humphreys, Brad. « NEW EVIDENCE ON CONSUMER SPENDING ON GAMBLING ». Journal of Gambling Business and Economics 4, n^o 2 (2 janvier 2013) : 79–100. http://dx.doi.org/10.5750/jgbe.v4i2.557.

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Characteristics of households who participate in gambling markets in the US, and the determinants of household expenditure on gambling, are investigated using data from the Consumer Expenditure Survey (CEX). I estimate empirical models of participation in gambling markets and gambling expenditure using Tobit and double hurdle estimators. A likelihood ratio test rejects Tobit in favor of the double hurdle model. The double hurdle model estimates show that key explanatory variables affect participation and expenditure with different signs. Tobit, which is widely used in the literature, forces the signs to be identical, calling into question empirical regularities reported in this literature.

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Harrison, R. Wes, Timothy Stringer et Witoon Prinyawiwatkul. « An Analysis of Consumer Preferences for Value-Added Seafood Products Derived from Crawfish ». Agricultural and Resource Economics Review 31, n^o 2 (octobre 2002) : 157–70. http://dx.doi.org/10.1017/s106828050000397x.

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Conjoint analysis is used to evaluate consumer preferences for three consumer-ready products derived from crawfish. Utility functions are estimated using two-limit tobit and ordered probit models. The results show women prefer a baked nugget or popper type product, whereas 35- to 44-year-old men prefer a microwavable nugget or patty type product. The results also show little difference between part-worth estimates or predicted rankings for the tobit and ordered probit models, implying the results are not sensitive to assumptions regarding the ordinal and cardinal nature of respondent preferences.

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Song, Weixing, et Yi Zhang. « Empirical L2-distance lack-of-fit tests for Tobit regression models ». Journal of Multivariate Analysis 111 (octobre 2012) : 380–96. http://dx.doi.org/10.1016/j.jmva.2012.04.015.

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Amaral, Pedro V., et Luc Anselin. « Finite sample properties of Moran'sItest for spatial autocorrelation in tobit models ». Papers in Regional Science 93, n^o 4 (14 mai 2013) : 773–81. http://dx.doi.org/10.1111/pirs.12034.

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Xu, Xuecai, et Željko Šarić. « Investigation into Interactions between Accident Consequences and Traffic Signs : A Bayesian Bivariate Tobit Quantile Regression Approach ». Journal of Advanced Transportation 2018 (1 août 2018) : 1–10. http://dx.doi.org/10.1155/2018/5032497.

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This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia and explore the correlation between accident severity levels and heterogeneity attributed to unobserved factors. The data from 460 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the correlation and heterogeneity, Bayesian bivariate Tobit quantile regression models were proposed, in which the bivariate framework addressed the correlation of residuals with Bayesian approach, while the Tobit quantile regression model accommodated the heterogeneity due to unobserved factors. By comparing the Bayesian bivariate Tobit quantile and mean regression models, the proposed quantile models showed priority to mean model. Results revealed that (1) low visibility and the number of invalid traffic signs per km increased the accident rate of material damage, death, or injury; (2) average speed limit exhibited a close relation with accident rate; and (3) the number of mandatory signs was more likely to reduce the accident rate of material damage, while the number of warning signs was significant for accident rate of death or injury.

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Harrison, R. Wes, Jeffrey Gillespie et Deacue Fields. « Analysis of Cardinal and Ordinal Assumptions in Conjoint Analysis ». Agricultural and Resource Economics Review 34, n^o 2 (octobre 2005) : 238–52. http://dx.doi.org/10.1017/s106828050000839x.

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Of twenty-three agricultural economics conjoint analyses conducted between 1990 and 2001, seventeen used interval-rating scales, with estimation procedures varying widely. This study tests cardinality assumptions in conjoint analysis when interval-rating scales are used, and tests whether the ordered probit or two-limit tobit model is the most valid. Results indicate that cardinality assumptions are invalid, but estimates of the underlying utility scale for the two models do not differ. Thus, while the ordered probit model is theoretically more appealing, the two-limit tobit model may be more useful in practice, especially in cases with limited degrees of freedom, such as with individual-level conjoint models.

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Pérez-Reyes, Raúl, et Beatriz Tovar. « Peruvian Electrical Distribution Firms’ Efficiency Revisited : A Two-Stage Data Envelopment Analysis ». Sustainability 13, n^o 18 (8 septembre 2021) : 10066. http://dx.doi.org/10.3390/su131810066.

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The extent to which the structural reform of the Peruvian electricity market in the 1990s has improved the technical efficiency levels of the distribution companies and whether some firm specific explanatory variables had influenced upon the efficiency was analysed for first time using a second stage Tobit model to study the influence of some firm specific explanatory variables on efficiency. Some authors have argued that the use of Tobit regression is inappropriate in the second stage of DEA and have suggested using other recently developed options. Due to this, it might be worth revisiting this issue and adding those other alternative models to check whether the conclusions obtained with the Tobit model could be upheld. The nine alternative models estimated allow us to confirm that the incentives generated by the reform process led to the firms becoming more efficient. Moreover, private management and the ratio of low voltage sales to medium voltage sales for each company positively affect efficiency, whereas investment per customer is negatively correlated to it.

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Song, Weixing, et Weixin Yao. « A lack-of-fit test in Tobit errors-in-variables regression models ». Statistics & ; Probability Letters 81, n^o 12 (décembre 2011) : 1792–801. http://dx.doi.org/10.1016/j.spl.2011.07.015.

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Zhou, X. C., et X. S. Liu. « The Monte Carlo EM method for estimating multivariate tobit latent variable models ». Journal of Statistical Computation and Simulation 79, n^o 9 (septembre 2009) : 1095–107. http://dx.doi.org/10.1080/00949650802137170.

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Dagne, Getachew A., et Yangxin Huang. « Bayesian Two-Part Tobit Models with Left-Censoring, Skewness, and Nonignorable Missingness ». Journal of Biopharmaceutical Statistics 25, n^o 4 (6 juin 2014) : 714–30. http://dx.doi.org/10.1080/10543406.2014.920860.

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Dagne, Getachew A. « Joint bent-cable Tobit models for longitudinal and time-to-event data ». Journal of Biopharmaceutical Statistics 28, n^o 3 (8 mai 2017) : 385–401. http://dx.doi.org/10.1080/10543406.2017.1321006.

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Honoré, Bo E. « Orthogonality conditions for Tobit models with fixed effects and lagged dependent variables ». Journal of Econometrics 59, n^o 1-2 (septembre 1993) : 35–61. http://dx.doi.org/10.1016/0304-4076(93)90038-7.

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Honoré, Bo E., Ekaterini Kyriazidou et Christopher Udry. « Estimation of Type 3 Tobit models using symmetric trimming and pairwise comparisons ». Journal of Econometrics 76, n^o 1-2 (janvier 1997) : 107–28. http://dx.doi.org/10.1016/0304-4076(95)01784-4.

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Chen, Tao, et Gautam Tripathi. « A simple consistent test of conditional symmetry in symmetrically trimmed tobit models ». Journal of Econometrics 198, n^o 1 (mai 2017) : 29–40. http://dx.doi.org/10.1016/j.jeconom.2016.12.003.

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Li, Tong, et Xiaoyong Zheng. « Semiparametric Bayesian inference for dynamic Tobit panel data models with unobserved heterogeneity ». Journal of Applied Econometrics 23, n^o 6 (septembre 2008) : 699–728. http://dx.doi.org/10.1002/jae.1017.

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Dagne, Getachew A. « Joint two-part Tobit models for longitudinal and time-to-event data ». Statistics in Medicine 36, n^o 26 (10 août 2017) : 4214–29. http://dx.doi.org/10.1002/sim.7429.

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Drukker, David M. « Bootstrapping a Conditional Moments Test for Normality after Tobit Estimation ». Stata Journal : Promoting communications on statistics and Stata 2, n^o 2 (juin 2002) : 125–39. http://dx.doi.org/10.1177/1536867x0200200202.

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Categorical and limited dependent variable models are routinely estimated via maximum likelihood. It is well-known that the ML estimates of the parameters are inconsistent if the distribution or the skedastic component is misspecified. When conditional moment tests were first developed by Newey (1985) and Tauchen (1985), they appeared to offer a wide range of easy-to-compute specification tests for categorical and limited dependent variable models estimated by maximum likelihood. However, subsequent studies found that using the asymptotic critical values produced severe size distortions. This paper presents simulation evidence that the standard conditional moment test for normality after tobit estimation has essentially no size distortion and reasonable power when the critical values are obtained via a parametric bootstrap.

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NIIMI, YOKO, et BARRY REILLY. « GENDER DIFFERENCES IN REMITTANCE BEHAVIOR : EVIDENCE FROM VIETNAM ». Singapore Economic Review 56, n^o 02 (juin 2011) : 215–37. http://dx.doi.org/10.1142/s0217590811004237.

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This paper investigates the role of gender in remittance behavior among migrants using the 2004 Vietnam Migration Survey data. The gender dimension to remittance behavior has not featured strongly in the existing literature and our findings thus contain novel appeal. In addition, we use estimates from both homoscedastic and heteroscedastic tobit models to decompose the raw gender difference in remittances into treatment and endowment components. We find little evidence that gender differences in remittances are attributable to behavioral differences between men and women, and this finding is invariant to whether the homoscedastic or heteroscedastic tobit is used in estimation.

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Dagne, Getachew A. « Bayesian two-part bent-cable Tobit models with skew distributions : Application to AIDS studies ». Statistical Methods in Medical Research 27, n^o 12 (31 mai 2017) : 3696–708. http://dx.doi.org/10.1177/0962280217710679.

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This paper presents a new development of a bent-cable two-part Tobit model to identify both phasic patterns and mixture of advancing (to AIDS) and non-advancing patients of HIV. In identification of such phasic patterns, estimation of a transition period for the development of drug resistance to antiretroviral (ARV) drug or therapy is carried out using longitudinal data that have a gradual change from a declining phase to an increasing phase. In addition to phasic changes, there are also problems of skewness and left-censoring in the response variable because of a lower limit of detection. A relatively large percentage of data below limit of detection are recorded more than expected under an assumed skew-distribution. To properly accommodate these features, we present an extension of the random effects bent-cable Tobit model that incorporates a mixture of true undetectable observations and those values from a skew-normal distribution for a response with left-censoring, skewness and phasic patterns. The proposed methods are illustrated using real data from an AIDS clinical study.

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Pullenayegum, Eleanor M., Jean-Eric Tarride, Feng Xie et Daria O’Reilly. « Calculating Utility Decrements Associated With an Adverse Event ». Medical Decision Making 31, n^o 6 (6 janvier 2011) : 790–99. http://dx.doi.org/10.1177/0272989x10393284.

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Background: When calculating the decreases in health utility associated with adverse events, often a number ofrespondents achieve the upper utility bound of 1. “Marginal” Tobit or CLAD coefficients have been used to account for this. These are calculated by using a Tobit or a CLAD model to estimate the decrease in a latent unbounded variable associated with the event or condition, then to multiply by the proportion of respondents falling below 1 in order to transform back to the utility scale. Objective & Methods: Starting with the Tobit model, we show mathematically that this procedure is not valid, when calculating decreases in utility associated with binary events. We then generalize the result to the CLAD model. A selection of published studies is used to illustrate the bias in the marginal Tobit decrements. Results: The degree of bias is more severe the greater the decrease in utility associated with the event, and the larger the proportion of individuals at the upper ceiling.In the examples studied, the degree of bias was often greater than 10%. We provide the correct formula for calculating the utility decrement. Conclusions: The marginal Tobit and CLAD coefficients should not be used as estimates of a utility decrement corresponding to an adverse event or health condition unless the coefficients are small in absolute value, or if the proportion of individuals at the upper utility bound is small. In other settings, the corrected formula or alternative regression methods (e.g. linear models of mean utility) should be considered.

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