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Daniela Marella

Personal Details

First Name:Daniela
Middle Name:
Last Name:Marella
Suffix:
RePEc Short-ID:pma3396
[This author has chosen not to make the email address public]

Affiliation

Dipartimento di Scienze Sociali ed Economiche
"Sapienza" Università di Roma

Roma, Italy
http://www.diss.uniroma1.it/
RePEc:edi:dtrosit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Daniela Marella, 2018. "Pc Complex: Pc Algorithm For Complex Survey Data," Departmental Working Papers of Economics - University 'Roma Tre' 0240, Department of Economics - University Roma Tre.
  2. Pier Luigi Conti & Daniela Marella & Andrea Neri, 2015. "Statistical matching and uncertainty analysis in combining household income and expenditure data," Temi di discussione (Economic working papers) 1018, Bank of Italy, Economic Research and International Relations Area.
  3. Daniela Marella & Mauro Mezzini & Paola Vicard, 2015. "Improving Discretization Exploiting Dependence Structure," Departmental Working Papers of Economics - University 'Roma Tre' 0199, Department of Economics - University Roma Tre.
  4. Daniela Marella & Paola Vicard, 2012. "Object-oriented bayesian networks for modelling the respondent measurement error," Departmental Working Papers of Economics - University 'Roma Tre' 0167, Department of Economics - University Roma Tre.

Articles

  1. Daniela Marella & Danny Pfeffermann, 2023. "Accounting for Non‐ignorable Sampling and Non‐response in Statistical Matching," International Statistical Review, International Statistical Institute, vol. 91(2), pages 269-293, August.
  2. Marella Daniela, 2023. "Adjusting for Selection Bias in Nonprobability Samples by Empirical Likelihood Approach," Journal of Official Statistics, Sciendo, vol. 39(2), pages 151-172, June.
  3. Daniela Marella & Paola Vicard, 2022. "Bayesian network structural learning from complex survey data: a resampling based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 981-1013, October.
  4. Giuseppe Bove & Pier Luigi Conti & Daniela Marella, 2021. "A measure of interrater absolute agreement for ordinal categorical data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 927-945, September.
  5. Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale, 2020. "On the estimation of the Lorenz curve under complex sampling designs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 1-24, March.
  6. Pier Luigi Conti & Daniela Marella & Andrea Neri, 2017. "Statistical matching and uncertainty analysis in combining household income and expenditure data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 485-505, August.
  7. Pier Luigi Conti & Daniela Marella & Mauro Scanu, 2017. "How far from identifiability? A systematic overview of the statistical matching problem in a non parametric framework," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(2), pages 967-994, January.
  8. Pier Luigi Conti & Daniela Marella & Mauro Scanu, 2016. "Statistical Matching Analysis for Complex Survey Data With Applications," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1715-1725, October.
  9. Pier Luigi Conti & Daniela Marella, 2015. "Inference for Quantiles of a Finite Population: Asymptotic versus Resampling Results," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 545-561, June.
  10. Marella, Daniela & Scanu, Mauro & Luigi Conti, Pier, 2008. "On the matching noise of some nonparametric imputation procedures," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1593-1600, September.
  11. Conti, Pier Luigi & Marella, Daniela & Scanu, Mauro, 2008. "Evaluation of matching noise for imputation techniques based on nonparametric local linear regression estimators," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 354-365, December.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Daniela Marella, 2018. "Pc Complex: Pc Algorithm For Complex Survey Data," Departmental Working Papers of Economics - University 'Roma Tre' 0240, Department of Economics - University Roma Tre.

    Cited by:

    1. Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale, 2020. "On the estimation of the Lorenz curve under complex sampling designs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 1-24, March.

  2. Pier Luigi Conti & Daniela Marella & Andrea Neri, 2015. "Statistical matching and uncertainty analysis in combining household income and expenditure data," Temi di discussione (Economic working papers) 1018, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Claramunt González, Juan & van Delden, Arnout & de Waal, Ton, 2023. "Assessment of the effect of constraints in a new multivariate mixed method for statistical matching," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    2. Elena Dalla Chiara & Martina Menon & Federico Perali, 2015. "An Integrated Data Base to Measure Living Standards," Working Papers 28/2015, University of Verona, Department of Economics.
    3. Francesco D. d’Ovidio & Paola Perchinunno & Laura Antonucci, 2021. "Data Integration Techniques for the Identification of Poverty Profiles," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 515-531, August.
    4. Andrea Cutillo & Mauro Scanu, 2020. "A Mixed Approach for Data Fusion of HBS and SILC," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(2), pages 411-437, July.
    5. Lamarche, Pierre, 2017. "Estimating consumption in the HFCS: Experimental results on the first wave of the HFCS," Statistics Paper Series 22, European Central Bank.
    6. Daniela Marella & Danny Pfeffermann, 2023. "Accounting for Non‐ignorable Sampling and Non‐response in Statistical Matching," International Statistical Review, International Statistical Institute, vol. 91(2), pages 269-293, August.
    7. Ton de Waal & Arnout van Delden & Sander Scholtus, 2020. "Multi‐source Statistics: Basic Situations and Methods," International Statistical Review, International Statistical Institute, vol. 88(1), pages 203-228, April.
    8. Leonardo Ciambezi & Alessandro Pietropaoli, 2024. "Relative price shocks and inequality: evidence from Italy," Questioni di Economia e Finanza (Occasional Papers) 883, Bank of Italy, Economic Research and International Relations Area.
    9. Perchinunno, Paola & Mongelli, Lucia & d’Ovidio, Francesco D., 2020. "Statistical matching techniques in order to plan interventions on socioeconomic weakness: An Italian case," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).

Articles

  1. Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale, 2020. "On the estimation of the Lorenz curve under complex sampling designs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 1-24, March.

    Cited by:

    1. Daniela Marella & Paola Vicard, 2022. "Bayesian network structural learning from complex survey data: a resampling based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 981-1013, October.

  2. Pier Luigi Conti & Daniela Marella & Andrea Neri, 2017. "Statistical matching and uncertainty analysis in combining household income and expenditure data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 485-505, August.
    See citations under working paper version above.
  3. Pier Luigi Conti & Daniela Marella & Mauro Scanu, 2017. "How far from identifiability? A systematic overview of the statistical matching problem in a non parametric framework," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(2), pages 967-994, January.

    Cited by:

    1. Endres Eva & Fink Paul & Augustin Thomas, 2019. "Imprecise Imputation: A Nonparametric Micro Approach Reflecting the Natural Uncertainty of Statistical Matching with Categorical Data," Journal of Official Statistics, Sciendo, vol. 35(3), pages 599-624, September.
    2. D'Alberto, Riccardo & Zavalloni, Matteo & Raggi, Meri & Viaggi, Davide, 2021. "A Statistical Matching approach to reproduce the heterogeneity of willingness to pay in benefit transfer," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).

  4. Pier Luigi Conti & Daniela Marella & Mauro Scanu, 2016. "Statistical Matching Analysis for Complex Survey Data With Applications," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1715-1725, October.

    Cited by:

    1. Claramunt González, Juan & van Delden, Arnout & de Waal, Ton, 2023. "Assessment of the effect of constraints in a new multivariate mixed method for statistical matching," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    2. Ahfock, Daniel & Pyne, Saumyadipta & McLachlan, Geoffrey J., 2022. "Statistical file-matching of non-Gaussian data: A game theoretic approach," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    3. Elena Dalla Chiara & Martina Menon & Federico Perali, 2015. "An Integrated Data Base to Measure Living Standards," Working Papers 28/2015, University of Verona, Department of Economics.
    4. Francesco D. d’Ovidio & Paola Perchinunno & Laura Antonucci, 2021. "Data Integration Techniques for the Identification of Poverty Profiles," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 515-531, August.
    5. Gessendorfer Jonathan & Beste Jonas & Drechsler Jörg & Sakshaug Joseph W., 2018. "Statistical Matching as a Supplement to Record Linkage: A Valuable Method to Tackle Nonconsent Bias?," Journal of Official Statistics, Sciendo, vol. 34(4), pages 909-933, December.
    6. Andrea Cutillo & Mauro Scanu, 2020. "A Mixed Approach for Data Fusion of HBS and SILC," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(2), pages 411-437, July.
    7. Daniela Marella & Danny Pfeffermann, 2023. "Accounting for Non‐ignorable Sampling and Non‐response in Statistical Matching," International Statistical Review, International Statistical Institute, vol. 91(2), pages 269-293, August.
    8. Zahra Rezaei Ghahroodi, 2023. "Statistical matching of sample survey data: application to integrate Iranian time use and labour force surveys," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 1023-1051, September.
    9. Perchinunno, Paola & Mongelli, Lucia & d’Ovidio, Francesco D., 2020. "Statistical matching techniques in order to plan interventions on socioeconomic weakness: An Italian case," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).

  5. Pier Luigi Conti & Daniela Marella, 2015. "Inference for Quantiles of a Finite Population: Asymptotic versus Resampling Results," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 545-561, June.

    Cited by:

    1. Daniela Marella & Paola Vicard, 2022. "Bayesian network structural learning from complex survey data: a resampling based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 981-1013, October.
    2. Pier Luigi Conti & Fulvia Mecatti, 2022. "Resampling under Complex Sampling Designs: Roots, Development and the Way Forward," Stats, MDPI, vol. 5(1), pages 1-12, March.
    3. Daniela Marella, 2018. "Pc Complex: Pc Algorithm For Complex Survey Data," Departmental Working Papers of Economics - University 'Roma Tre' 0240, Department of Economics - University Roma Tre.
    4. M. D. Jiménez-Gamero & J. L. Moreno-Rebollo & J. A. Mayor-Gallego, 2018. "On the estimation of the characteristic function in finite populations with applications," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 95-121, March.
    5. Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale, 2020. "On the estimation of the Lorenz curve under complex sampling designs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 1-24, March.
    6. Omer Ozturk & Narayanaswamy Balakrishnan & Olena Kravchuk, 2023. "Order Statistics Based on a Combined Simple Random Sample from a Finite Population and Applications to Inference," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 77-101, February.

  6. Marella, Daniela & Scanu, Mauro & Luigi Conti, Pier, 2008. "On the matching noise of some nonparametric imputation procedures," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1593-1600, September.

    Cited by:

    1. Ahfock, Daniel & Pyne, Saumyadipta & McLachlan, Geoffrey J., 2022. "Statistical file-matching of non-Gaussian data: A game theoretic approach," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    2. Conti, Pier Luigi & Marella, Daniela & Scanu, Mauro, 2008. "Evaluation of matching noise for imputation techniques based on nonparametric local linear regression estimators," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 354-365, December.
    3. Cristina Bernini & Silvia Emili & Federica Galli, 2021. "Does urbanization matter in the expenditure‐happiness nexus?," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1403-1428, December.
    4. Zahra Rezaei Ghahroodi, 2023. "Statistical matching of sample survey data: application to integrate Iranian time use and labour force surveys," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 1023-1051, September.

  7. Conti, Pier Luigi & Marella, Daniela & Scanu, Mauro, 2008. "Evaluation of matching noise for imputation techniques based on nonparametric local linear regression estimators," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 354-365, December.

    Cited by:

    1. Claramunt González, Juan & van Delden, Arnout & de Waal, Ton, 2023. "Assessment of the effect of constraints in a new multivariate mixed method for statistical matching," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    2. Ahfock, Daniel & Pyne, Saumyadipta & McLachlan, Geoffrey J., 2022. "Statistical file-matching of non-Gaussian data: A game theoretic approach," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    3. Endres Eva & Fink Paul & Augustin Thomas, 2019. "Imprecise Imputation: A Nonparametric Micro Approach Reflecting the Natural Uncertainty of Statistical Matching with Categorical Data," Journal of Official Statistics, Sciendo, vol. 35(3), pages 599-624, September.
    4. Nicklas Pettersson, 2013. "Bias reduction of finite population imputation by kernel methods," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(1), pages 139-160, March.
    5. Riccardo D’Alberto & Matteo Zavalloni & Meri Raggi & Davide Viaggi, 2018. "AES Impact Evaluation With Integrated Farm Data: Combining Statistical Matching and Propensity Score Matching," Sustainability, MDPI, vol. 10(11), pages 1-24, November.
    6. D'Alberto, R. & Raggi, M., 2018. "Statistical Matching in agricultural economics: how to integrate different farm data sources," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277101, International Association of Agricultural Economists.
    7. Zhang Li-Chun, 2015. "On Proxy Variables and Categorical Data Fusion," Journal of Official Statistics, Sciendo, vol. 31(4), pages 783-807, December.
    8. Antonio D’Ambrosio & Massimo Aria & Roberta Siciliano, 2012. "Accurate Tree-based Missing Data Imputation and Data Fusion within the Statistical Learning Paradigm," Journal of Classification, Springer;The Classification Society, vol. 29(2), pages 227-258, July.
    9. Zahra Rezaei Ghahroodi, 2023. "Statistical matching of sample survey data: application to integrate Iranian time use and labour force surveys," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 1023-1051, September.

More information

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Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (4) 2012-11-11 2015-02-05 2015-07-25 2018-08-20
  2. NEP-CMP: Computational Economics (1) 2018-08-20
  3. NEP-ORE: Operations Research (1) 2018-08-20

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