IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v128y2018icp104-115.html
   My bibliography  Save this article

Inference on zero inflated ordinal models with semiparametric link

Author

Listed:
  • Das, Ujjwal
  • Das, Kalyan

Abstract

In socioeconomics or in Biological studies, observations on individuals are often observed longitudinally on a Likert-type scale with substantially large proportion of zeros. This leads to a special case of mixture structured data where extra-variation occurs. Obviously the standard ordinal data analysis fails to provide appropriate statistical inference. We propose a suitable zero inflated semiparametric ordinal model that takes into account the non linear link between the ordinal response and a covariate. A sieve maximum likelihood estimator(MLE) is proposed for the regression parameter of interest. We also propose a test for the zero proportion in this semiparametric model. A simulation study has been carried out to investigate the performance of the estimator as well as the test. We illustrate the methodology using data from a survey on Tuberculosis patients in and around Kolkata, India.

Suggested Citation

  • Das, Ujjwal & Das, Kalyan, 2018. "Inference on zero inflated ordinal models with semiparametric link," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 104-115.
    • Handle: RePEc:eee:csdana:v:128:y:2018:i:c:p:104-115
    DOI: 10.1016/j.csda.2018.06.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947318301622
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2018.06.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kalyan Das & Angshuman Sarkar, 2014. "Robust inference for generalized partially linear mixed models that account for censored responses and missing covariates -- an application to Arctic data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2418-2436, November.
    2. Gurmu, Shiferaw & Trivedi, Pravin K, 1996. "Excess Zeros in Count Models for Recreational Trips," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 469-477, October.
    3. Jansakul, N. & Hinde, J. P., 2002. "Score Tests for Zero-Inflated Poisson Models," Computational Statistics & Data Analysis, Elsevier, vol. 40(1), pages 75-96, July.
    4. Harris, Mark N. & Zhao, Xueyan, 2007. "A zero-inflated ordered probit model, with an application to modelling tobacco consumption," Journal of Econometrics, Elsevier, vol. 141(2), pages 1073-1099, December.
    5. Li, Chin-Shang & Taylor, Jeremy M. G. & Sy, Judy P., 2001. "Identifiability of cure models," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 389-395, October.
    6. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521142373.
    7. He, Xuming & Xue, Hongqi & Shi, Ning-Zhong, 2010. "Sieve maximum likelihood estimation for doubly semiparametric zero-inflated Poisson models," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2026-2038, October.
    8. John Mullahy, 1997. "Instrumental-Variable Estimation Of Count Data Models: Applications To Models Of Cigarette Smoking Behavior," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 586-593, November.
    9. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204.
    10. Daniel B. Hall, 2000. "Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study," Biometrics, The International Biometric Society, vol. 56(4), pages 1030-1039, December.
    11. K. F. Lam & Hongqi Xue & Yin Bun Cheung, 2006. "Semiparametric Analysis of Zero-Inflated Count Data," Biometrics, The International Biometric Society, vol. 62(4), pages 996-1003, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ujjwal Das & Kalyan Das, 2021. "Selection of influential variables in ordinal data with preponderance of zeros," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(1), pages 66-87, February.
    2. Cristian Roner & Claudia Di Caterina & Davide Ferrari, 2021. "Exponential Tilting for Zero-inflated Interval Regression with Applications to Cyber Security Survey Data," BEMPS - Bozen Economics & Management Paper Series BEMPS85, Faculty of Economics and Management at the Free University of Bozen.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David Dale & Andrei Sirchenko, 2021. "Estimation of nested and zero-inflated ordered probit models," Stata Journal, StataCorp LP, vol. 21(1), pages 3-38, March.
    2. Cristian Roner & Claudia Di Caterina & Davide Ferrari, 2021. "Exponential Tilting for Zero-inflated Interval Regression with Applications to Cyber Security Survey Data," BEMPS - Bozen Economics & Management Paper Series BEMPS85, Faculty of Economics and Management at the Free University of Bozen.
    3. He, Xuming & Xue, Hongqi & Shi, Ning-Zhong, 2010. "Sieve maximum likelihood estimation for doubly semiparametric zero-inflated Poisson models," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2026-2038, October.
    4. William H Greene & Mark N Harris & Preety Srivastava & Xueyan Zhao, 2013. "Econometric Modelling of Social Bads," Bankwest Curtin Economics Centre Working Paper series WP1305, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.
    5. William Greene & Mark N. Harris & Preety Srivastava & Xueyan Zhao, 2018. "Misreporting and econometric modelling of zeros in survey data on social bads: An application to cannabis consumption," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 372-389, February.
    6. Chinh Ho & Corinne Mulley & Chi-Hong Tsai & Stephen Ison & Sue Wiblin, 2017. "Area-wide travel plans—targeting strategies for greater participation in green travel initiatives: a case study of Rouse Hill Town Centre, NSW Australia," Transportation, Springer, vol. 44(2), pages 325-352, March.
    7. Greene, William & Harris, Mark N. & Knott, Rachel & Rice, Nigel, 2023. "Reporting heterogeneity in modeling self-assessed survey outcomes," Economic Modelling, Elsevier, vol. 124(C).
    8. Hossain, Sanjana & Loa, Patrick & Ong, Felita & Habib, Khandker Nurul, 2022. "The determinants of commute mode usage frequency of post-secondary students in the Greater Toronto and Hamilton Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 164-185.
    9. David ARISTEI & Manuela Gallo, 2012. "The Drivers of Household Over-Indebtedness and Delinquency on Mortgage Loans: Evidence from Italian Microdata," Quaderni del Dipartimento di Economia, Finanza e Statistica 105/2012, Università di Perugia, Dipartimento Economia.
    10. Benjamin E. Bagozzi, 2016. "The baseline-inflated multinomial logit model for international relations research," Conflict Management and Peace Science, Peace Science Society (International), vol. 33(2), pages 174-197, April.
    11. Sarah Brown & Mark N. Harris & Christopher Spencer, 2020. "Modelling Category Inflation with Multiple Inflation Processes: Estimation, Specification and Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1342-1361, December.
    12. An, Wookhyun & Alarcón, Silverio, 2021. "Rural tourism preferences in Spain: Best-worst choices," Annals of Tourism Research, Elsevier, vol. 89(C).
    13. Stefan Boes, 2013. "Nonparametric analysis of treatment effects in ordered response models," Empirical Economics, Springer, vol. 44(1), pages 81-109, February.
    14. William H. Greene & Mark N. Harris & Rachel J. Knott & Nigel Rice, 2021. "Specification and testing of hierarchical ordered response models with anchoring vignettes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 31-64, January.
    15. Hanna Dudek & Joanna Landmesser, 2012. "Income satisfaction and relative deprivation," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(2), pages 321-334, June.
    16. Andrew Powell & Pilar Tavella, 2012. "Capital Inflow Surges in Emerging Economies: How Worried Should LAC Be?," Research Department Publications 4782, Inter-American Development Bank, Research Department.
    17. Kaili Wang & Sanjana Hossain & Khandker Nurul Habib, 2022. "A hybrid data fusion methodology for household travel surveys to reduce proxy biases and under-representation of specific sub-group of population," Transportation, Springer, vol. 49(6), pages 1801-1836, December.
    18. Ghimire, Ramesh & Green, Gary T. & Paudel, Krishna P. & Poudyal, Neelam C. & Cordell, H. Ken, 2017. "Visitors' Preferences for Freshwater Amenity Characteristics: Implications from the U.S. Household Survey," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(1), pages 1-24, January.
    19. Chappell, Henry W. & McGregor, Rob Roy, 2018. "Committee decision-making at Sweden's Riksbank," European Journal of Political Economy, Elsevier, vol. 53(C), pages 120-133.
    20. Päivi Karhunen & Svetlana Ledyaeva, 2021. "Is Chain Affiliation a Strategic Asset or Constraint in Emerging Economies? Competitive Strategies and Performance in the Russian Hotel Industry," Management International Review, Springer, vol. 61(3), pages 403-427, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:128:y:2018:i:c:p:104-115. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.