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Books on the topic 'Microsimulation'

To see the other types of publications on this topic, follow the link: Microsimulation.

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

Troitzsch, Klaus G., Ulrich Mueller, G. Nigel Gilbert, and Jim E. Doran, eds. Social Science Microsimulation. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03261-9.

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2

G, Troitzsch Klaus, ed. Social science microsimulation. Berlin: Springer, 1996.

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3

O'Donoghue, Cathal. Farm-Level Microsimulation Modelling. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63979-6.

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4

Bélanger, Alain, and Patrick Sabourin. Microsimulation and Population Dynamics. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-44663-9.

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5

Asghar, Zaidi M., Harding Ann 1958-, and Williamson Paul, eds. New frontiers in microsimulation modelling. Farnham, England: Ashgate, 2009.

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6

Marois, Guillaume, and Samir KC. Microsimulation Population Projections with SAS. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79111-7.

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7

International Microsimulation Association. Inaugural meeting. New frontiers in microsimulation modelling. Farnham, England: Ashgate, 2009.

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8

Perese, Kevin. Mate matching for microsimulation models. Washington, DC: Congressional Budget Office, 2002.

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9

van Tongeren, Frank W. Microsimulation Modelling of the Corporate Firm. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-52068-6.

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10

O'Donoghue, Cathal, Dimitris Ballas, Graham Clarke, Stephen Hynes, and Karyn Morrissey, eds. Spatial Microsimulation for Rural Policy Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-30026-4.

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11

Callan, Tim. Income tax reform: A microsimulation approach. Dublin: Economic and Social Research Institute, 1990.

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12

Anil, Gupta, and Kapur Vishnu, eds. Microsimulation in government policy and forecasting. Amsterdam: Elsevier, 2000.

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13

Harding, Ann. Dynamic microsimulation models: Problems and prospects. London: Welfare State Programme, Suntory-International Centre for Economics and Related Disciplines, London School of Economics, 1990.

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14

F, Gentleman Jane, Robertson D, and Monica Tomiak, eds. Smoothing procedures for simulated longitudinal microdata. [Ottawa, Ont.]: Statistics Canada, 1990.

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15

Tanton, Robert, and Kimberley Edwards, eds. Spatial Microsimulation: A Reference Guide for Users. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-4623-7.

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16

Introduction to molecular-microsimulation of colloidal dispersions. Amsterdam: Elsevier, 2003.

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17

D'Souza, R. M. M. Microsimulation modelling: Allowing for the entitlement effect. [London]: Analytical Services Division, Department of Social Security, 1990.

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18

H, Lewis Gordon, Michel Richard C, Urban Institute, and Conference on Software Systems and Income Transfer Policy (1987 : Urban Institute), eds. Microsimulation techniques for tax and transfer analysis. Washington, D.C: Urban Institute Press, 1990.

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19

Ruth, Hancock, Sutherland H, and Suntory-Toyota International Centre for Economics and Related Disciplines., eds. Microsimulation models for public policy analysis: New frontiers. (London): (Suntory-Toyota International Centre for Economics and Related Disciplines), 1992.

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20

John, Landt, ed. Reweighting a base population for a microsimulation model. Canberra: National Centre for Social and Economic Modelling, Faculty of Management, University of Canberra, 1995.

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21

Herwig, Immervoll, ed. Welfare reform in European countries: A microsimulation analysis. Bonn, Germany: IZA, 2005.

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22

Lavinia, Mitton, Sutherland H, and Weeks Melvyn J, eds. Microsimulation modelling for policy analysis: Challenges and innovations. Cambridge, U.K: Cambridge University Press, 2000.

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23

IARIW Special Conference on Microsimulation and Public Policy (1993 Canberra, A.C.T.). Microsimulation and public policy: Selected papers from the IARIW Special Conference on Microsimulation and Public Policy, Canberra, 5-9 December, 1993. Amsterdam: Elsevier, 1996.

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24

Callan, Tim. Income tax and welfare reforms: Microsimulation modelling and analysis. Dublin: Economic and Social Research Institute, 1991.

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25

Mohammed, Basheer. Operational analysis of high-occupancy vehicle lanes using microsimulation. Ottawa: National Library of Canada, 2001.

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26

Antcliff, Susan. An introduction to DYNAMOD: A dynamic population microsimulation model. Canberra City, ACT: National Centre for Social and Economic Modelling, Faculty of Management, University of Canberra, 1993.

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27

Look, Horace Wai Fung. Accident risk assessment using microsimulation for dynamic route guidance. Ottawa: National Library of Canada, 2001.

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28

Lina, Walker, and United States. Congressional Budget Office, eds. Econometric flexibility in microsimulation: An age-centered regression approach. Washington, D.C: Congressional Budget Office, 2007.

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29

Basu, Sanjay. Microsimulation. Edited by Sanjay Basu. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190667924.003.0008.

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In previous chapters, the author used Markov models to estimate the burden of disease and the potential impact of interventions. One of the key limitations to Markov models is that they don’t take into account a person’s unique individual characteristics: Markov models are designed to efficiently simulate the average outcome for an entire population. For many public health and healthcare system problems, however, we need to consider heterogeneity within a population, or differences in risk and differences in benefit from our programs. For that purpose, microsimulation models, which take into account unique characteristics of individuals and the correlations between these characteristics, can be more useful. This chapter details the construction and use of microsimulation models, using examples related to diabetes prevention and treatment.

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30

O'Donoghue, Cathal. Practical Microsimulation Modelling. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198852872.001.0001.

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The purpose of this book is to bring together for the first time a description, with examples, of the main methods used in microsimulation modelling, used in the field of income-distribution analysis. The book provides a practical complement to the Handbook of Microsimulation Modelling, published in 2014. It is structured to develop and use the different types of models used in the field, with a focus on household-targeted policy. The book aims to fill a gap in the literature in providing a greater degree of codified knowledge through a practical guide to developing and using microsimulation models. At present, the training of researchers and analysts that use and develop microsimulation modelling is done on a relatively ad-hoc basis through occasional training programmes and lecture series, built around lecture notes. This book would enable a more formalized and organized approach. Each chapter addresses a separate modelling approach in a similar, consistent way, describing in practical terms the key methodological skills for each approach: · It provides some policy context to each modelling approach so as to understand the modelling choices made and structures developed. · As a very data-intensive modelling approach, each chapter describes key data analysis and data-preparation methods. · As a modelling approach that is used extensively for deciding policy, often involving huge budgets, validation is key. Each chapter describes an approach to validating the model. · Depending upon the policy context, the analysis is assessed in different ways. Each chapter contains a section devoted to measurement issues and tabulating output from the models. · Last, each chapter contains an example simulation of a policy analysis using the chapter’s methodological approach.

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31

Troitzsch, K. G. Social Science Microsimulation. Springer, 2010.

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32

O'Donoghue, Cathal. Practical Microsimulation Modelling. Oxford University Press, 2021.

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33

Spiegelman, Clifford, Eun Sug Park, and Laurence R. Rilett. Transportation Statistics and Microsimulation. Taylor & Francis Group, 2016.

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34

Lovelace, Robin, Morgane Dumont, Richard Ellison, and Maja Založnik. Spatial Microsimulation with R. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315381640.

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35

O’Donoghue, Cathal, ed. Handbook of Microsimulation Modelling. Emerald Group Publishing Limited, 2014. http://dx.doi.org/10.1108/s0573-85552014293.

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36

Spiegelman, Clifford, Eun Sug Park, and Laurence R. Rilett. Transportation Statistics and Microsimulation. Chapman and Hall/CRC, 2016. http://dx.doi.org/10.1201/9781439894545.

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37

Dekkers, Gijs. New Pathways in Microsimulation. Routledge, 2016. http://dx.doi.org/10.4324/9781315598024.

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38

New Pathways in Microsimulation. Taylor & Francis Group, 2014.

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39

Handbook of Microsimulation Modelling. Emerald Publishing Limited, 2014.

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40

Keegan, Marcia, and Gijs Dekkers. New Pathways in Microsimulation. Taylor & Francis Group, 2016.

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41

Spiegelman, Clifford, Eun Sug Park, and Laurence R. Rilett. Transportation Statistics and Microsimulation. Taylor & Francis Group, 2011.

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42

Spiegelman, Clifford, Eun Sug Park, and Laurence R. Rilett. Transportation Statistics and Microsimulation. Taylor & Francis Group, 2016.

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43

Lovelace, Robin, and Morgane Dumont. Spatial Microsimulation with R. Taylor & Francis Group, 2017.

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44

Lovelace, Robin, and Morgane Dumont. Spatial Microsimulation with R. Taylor & Francis Group, 2016.

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45

Transportation Statistics and Microsimulation. Taylor & Francis Group, 2023.

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46

Spiegelman, Clifford, Eun Sug Park, and Laurence R. Rilett. Transportation Statistics and Microsimulation. Taylor & Francis Group, 2016.

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47

Transportation Statistics And Microsimulation. CRC Press, 2010.

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48

O'Donoghue, Cathal. Farm-Level Microsimulation Modelling. Palgrave Macmillan, 2019.

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49

Lovelace, Robin. Spatial Microsimulation with R. Taylor & Francis Group, 2017.

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50

O'Donoghue, Cathal. Farm-Level Microsimulation Modelling. Palgrave Macmillan, 2017.

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