Advances in political methodology
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[2017]
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| 245 | 1 | 0 | |a Advances in political methodology |c edited by Robert J. Franzese, Jr. ( Professor of Political Science, University of Michigan, Michigan, USA and Fellow and 15th President, Society of Political Methodology, Washington University in St. Louis, Missouri, USA) |
| 264 | 1 | |a Cheltenham, UK ; Northampton, MA, USA |b Edward Elgar Publishing |c [2017] | |
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| adam_text | Titel: Advances in political methodology
Autor: Franzese, Robert J
Jahr: 2017
Contents
Acknowledgements
Introduction Robert J. Franzese, Jr.
PART I ADVANCES IN BAYESIAN METHODS
1. Simon Jackman (2000), Estimation and Inference via Bayesian
Simulation: An Introduction to Markov Chain Monte Carlo ,
American Journal ofPolitical Science, 44 (2), April, 375-404
2. Joshua Clinton, Simon Jackman and Douglas Rivers (2004), The
Statistical Analysis of Roll Call Data , American Political Science
Review, 98 (2), May, 355-70
3. Richard Traunmüller, Andreas Murr and Jeff Gill (2015), Modeling
Latent Information in Voting Data with Dirichlet Process Priors ,
Political Analysis, 23 (1), Winter, 1-20
4. Yair Ghitza and Andrew Gelman (2013), Deep Interactions with
MRP: Election Turnout and Voting Patterns Among Small Electoral
Subgroups , American Journal ofPolitical Science, 57 (3), July,
762-76
5. Devin Caughey and Christopher Warshaw (2015), Dynamic
Estimation of Latent Opinión Using a Hierarchical Group-Level
IRT Model , Political Analysis, 23 (2), Spring, 197-211
PART II ADVANCES IN TIME-SERIES, TIME-SERIES-CROSS-SECTION/
PANEL, AND EVENT-HISTORY/DURATION MODELLING
6. Janet M. Box-Steffensmeier and Bradford S. Jones (1997), Time Is
of the Essence: Event History Models in Political Science ,
American Journal ofPolitical Science, 41 (4), October, 1414—61
7. Frederick J. Boehmke, Daniel S. Morey and Megan Shannon
(2006), Selection Bias and Continuous-Time Duration Models:
Consequences and a Proposed Solution , American Journal of
Political Science, 50 (1), January, 192-207
8. Jude C. Hays, Emily U. Schilling and Frederick J. Boehmke (2015),
Accounting for Right Censoring in Interdependent Duration
Analysis , Political Analysis, 23 (3) Summer, 400-414
9. Jude C. Hays and Robert J. Franzese, Jr. (2009), A Comparison of
the Small-Sample Properties of Several Estimators for Spatial-Lag
Count Models , paper submitted at the 2009 Summer Meeting of
The Society of Political Methodology, New Häven, CT, USA, July
23-25, i, 1-27
ix
xiii
3
33
49
69
84
101
149
165
180
Ví
Advances in Political Methodology
10. Patrick T. Brandt, Michael Colaresi and John R. Freeman (2008),
The Dynamics of Reciprocity, Accountability, and Credibility ,
Journal of Conflict Resolution, 52 (3), June, 343-74 208
11. Patrick T. Brandt, John R. Freeman and Philip A. Schrodt (2011),
Real Time, Time Series Forecasting of Inter- and Intra-State
Political Conflict , Conflict Management and Peace Science, 28 (1),
February, 41-64 240
12. Daniel Stegmueller (2013), Modeling Dynamic Preferences: A
Bayesian Robust Dynamic Latent Ordered Probit Model , Political
Analysis, 21 (3), Summer, 314—33 264
13. Xun Pang (2014), Varying Responses to Common Shocks and
Complex Cross-Sectional Dependence: Dynamic Multilevel
Modeling with Multifactor Error Structures for Time-Series Cross-
Sectional Data , Political Analysis, 22 (4), Autumn, 464-96 284
14. Robert J. Franzese, Jr. and Jude C. Hays (2008), Empirical Models
of Spatial Interdependence , in Janet M. Box-Steffensmeier, Henry
E. Brady and David Collier (eds), Oxford Handbook of Political
Methodology, Oxford, UK: Oxford University Press, Part VII,
Chapter 25,570-604 317
15. Robert J. Franzese, Jr., Jude C. Hays and Scott J. Cook (2016),
Spatial- and Spatiotemporal-Autoregressive Probit Models of
Interdependent Binary Outcomes , Political Science Research and
Methods, 4 (1), January, 151-73 352
PART III ADVANCES IN NETWORK ANALYSIS
16. B .A. Desmarais and S J. Cranmer (2012), Statistical Mechanics of
Networks: Estimation and Uncertainty , Physica A: Statistical
Mechanics and its Applications, 391 (4), February, 1865-76 377
17. Bruce A. Desmarais and Skyler J. Cranmer (2012), Micro-Level
Interpretation of Exponential Random Graph Models with
Application to Estuary Networks , Policy Studies Journal, 40 (3),
August, 402-34 389
18. Bruce A. Desmarais, Jeffrey J. Harden and Frederick J. Boehmke
(2015), Persistent Policy Pathways: Inferring Diffusion Networks
in the American States , American Political Science Review, 109
(2), May, 392-406 422
19. Jeff Gill and John R. Freeman (2013), Dynamic Elicited Priors for
Updating Covert Networks , Network Science ,1(1), April, 68-94 437
20. Jude C. Hays, Aya Kachi and Robert J. Franzese, Jr. (2010), A
Spatial Model Incorporating Dynamic, Endogenous Network
Interdependence: A Political Science Application , Statistical
Methodology ,7(3), May, 406-28 464
Advances in Political Methodology
vii
21. Robert J. Franzese, Jr., Jude C. Hays and Aya Kachi (2012),
Modeling History Dependence in Network-Behavior Coevolution ,
Political Analysis, 20 (2), Spring, 175-90 487
PART IV ADVANCES IN TEXT-ANALYTIC, CLASSIFICATION AND BIG¬
DATA METHODS
22. Phillip A. Schrodt and David Van Brackle (2013), Automated
Coding of Political Event Data , in V.S. Subrahmanian (ed.),
Handbook of Computational Approaches to Counterterrorism,
Chapter 2, New York, USA: Springer, 23-49 505
23. Justin Grimmer and Gary King (2011), General Purpose Computer-
Assisted Clustering and Conceptualization , Proceedings ofthe
National Academy of Sciences, 108 (7), February, 2643-50 532
24. Vito D Orazio, Steven T. Landis, Glenn Palmer and Philip Schrodt
(2014), Separating the Wheat from the Chaff: Applications of
Automated Document Classification Using Support Vector
Machines , Political Analysis, 22 (2), Spring, 224-42 540
25. Justin Grimmer and Brandon M. Stewart (2013), Text as Data: The
Promise and Pitfalls of Automatic Content Analysis Methods for
Political Texts , Political Analysis, 21 (3), Summer, 267-97 559
26. Martin Elff (2013), A Dynamic State-Space Model of Coded
Political Texts , Political Analysis, 21 (2), Spring, 217-32 590
27. Christopher Lucas, Richard A. Nielson, Margaret E. Roberts,
Brandon M. Stewart, Alex Storer and Dustin Tingley (2015),
Computer-assisted Text Analysis for Comparative Politics ,
Political Analysis, 23 (2), Spring, 254—77 606
PART V ADVANCES IN NONPARAMETRIC AND DESIGN-BASED
INFERENCE METHODS
28. Jasjeet S. Sekhon (2008), The Neyman-Rubin Model of Causal
Inference and Estimation via Matching Methods , in Janet M. Box-
Steffensmeier, Henry E. Brady and David Collier (eds), Oxford
Handbook of Political Methodology, Part IV, Chapter 11, Oxford,
UK: Oxford University Press, 271-99 633
29. Jasjeet S. Sekhon and Rocío Titiunik (2012), When Natural
Experiments Are Neither Natural Nor Experiments , American
Political Science Review, 106 (1), February, 35-57 662
30. Peter M. Aronow and Allison Carnegie (2013), Beyond LATE:
Estimation of the Average Treatment Effect with an Instrumental
Variable , Political Analysis, 21 (4), Autumn, 492-506 685
viii
Advances in Political Methodology
31. Kosuke Imai, Luke Keele, Dustin Tingley and Teppei Yamamoto
(2011), Unpacking the Black Box of Causality: Learning about
Casual Mechanisms from Experimental and Observational Studies ,
American Political Science Review, 105 (4), November, 765-89 700
32. Kosuke Imai and Marc Ratkovic (2013), Estimating Treatment
Effect Heterogeneity in Randomized Program Evaluation , Annais
of Applied Statistics, 7 (1), 443-70 725
33. Luke Keele and Rocío Titiunik (2016), Natural Experiments Based
on Geography , Political Science Research and Methods, 4 (1),
January, 65-95 753
34. Luke Keele, Rocío Titiunik and José R. Zubizarreta (2015),
Enhancing a Geographie Regression Discontinuity Design
Through Matching to Estimate the Effect of Ballot Initiatives on
Voter Tumout Journal ofthe Royal Statistical Society: Statistics in
Society, Series A, 178 (1), 223-39 784
Contents
Acknowledgements ix
Introduction Robert J. Franzese, Jr. xiii
PART I ADVANCES IN BAYESIAN METHODS
1. Simon Jackman (2000), ‘Estimation and Inference via Bayesian
Simulation: An Introduction to Markov Chain Monte Carlo’,
American Journal of Political Science, 44 (2), April, 375-404 3
2. Joshua Clinton, Simon Jackman and Douglas Rivers (2004), The
Statistical Analysis of Roll Call Data’, American Political Science
Review, 98 (2), May, 355-70 33
3. Richard Traunmuller, Andreas Murr and Jeff Gill (2015), ‘Modeling
Latent Information in Voting Data with Dirichlet Process Priors’,
Political Analysis, 23 (1), Winter, 1-20 49
4. Yair Ghitza and Andrew Gelman (2013), ‘Deep Interactions with
MRP: Election Turnout and Voting Patterns Among Small Electoral
Subgroups’, American Journal of Political Science, 57 (3), July,
762-76 69
5. Devin Caughey and Christopher Warshaw (2015), ‘Dynamic
Estimation of Latent Opinion Using a Hierarchical Group-Level
IRT Model ’, Political Analysis, 23 (2), Spring, 197-211 84
PART II ADVANCES IN TIME-SERIES, TIME-SERIES-CROSS-SECTION/
PANEL, AND EVENT-HISTORY /DURATION MODELLING
6. Janet M. Box-Steffensmeier and Bradford S. Jones (1997), ‘Time Is
of the Essence: Event History Models in Political Science’,
American Journal of Political Science, 41 (4), October, 1414—61 101
7. Frederick J. Boehmke, Daniel S. Morey and Megan Shannon
(2006), ‘Selection Bias and Continuous-Time Duration Models:
Consequences and a Proposed Solution’, American Journal of
Political Science, 50 (1), January, 192-207 149
8. Jude C. Hays, Emily U. Schilling and Frederick J. Boehmke (2015),
‘Accounting for Right Censoring in Interdependent Duration
Analysis’, Political Analysis, 23 (3) Summer, 400-414 165
9. Jude C. Hays and Robert J. Franzese, Jr. (2009), ‘A Comparison of
the Small-Sample Properties of Several Estimators for Spatial-Lag
Count Models’, paper submitted at the 2009 Summer Meeting of
The Society of Political Methodology, New Haven, CT, USA, July
23-25,i, 1-27
180
Advances in Political Methodology
PART III
10. Patrick T. Brandt, Michael Colaresi and John R. Freeman (2008),
‘The Dynamics of Reciprocity, Accountability, and Credibility’,
Journal of Conflict Resolution, 52 (3), June, 343 74
11. Patrick T. Brandt, John R. Freeman and Philip A. Schrodt (2011 h
‘Real Time, Time Series Forecasting of inter- and Intra-State
Political Conflict’, Conflict Management and Peace Scion c, 28(1),
February, 41-64
12. Daniel Stegmueller (2013), ‘Modeling Dynamic Preferences: A
Bayesian Robust Dynamic Latent Ordered Probit Model’, Political
Analysis, 21 (3), Summer, 314-33
13. Xun Pang (2014), ‘Varying Responses to Common Shocks and
Complex Cross-Sectional Dependence: Dynamic Multilevel
Modeling with Multifactor Error Structures for l ime Series Cross-
Sectional Data’, Political Analysis, 22 (4), Autumn, 464 06
14. Robert J. Franzese, Jr. and Jude C. Hays (2008), ‘Empirical Models
of Spatial Interdependence’, in Janet M. Box-Steffensmeier. Henry
E. Brady and David Collier (eds), Oxford Hand hook of Political
Methodology, Oxford, UK: Oxford University Press, Part VII,
Chapter 25, 570-604
15. Robert J. Franzese, Jr., Jude C. Hays and Scott J. Cook (2016),
‘Spatial- and Spatiotemporal-Autoregressive Probit Models of
Interdependent Binary Outcomes’, Political Science Research and
Methods, 4 (1), January, 151-73
ADVANCES IN NETWORK ANALYSIS
16. B.A. Desmarais and S.J. Cranmer (2012), ‘Statistical Mechanics of
Networks: Estimation and Uncertainty’, Physica A: Statistical
Mechanics and its Applications, 391 (4), February, 1865-76
17. Bruce A. Desmarais and Skyler J. Cranmer (2012), ‘Micro-Level
Interpretation of Exponential Random Graph Models with
Application to Estuary Networks’, Policy Studies Journal, 40 (3).
August, 402-34
18. Bruce A. Desmarais, Jeffrey J. Harden and Frederick J. Boehmke
(2015), ‘Persistent Policy Pathways: Inferring Diffusion Networks
in the American States’, American Political Science Review, 109
(2), May, 392-406
19. Jeff Gill and John R. Freeman (2013), ‘Dynamic Elicited Priors for
Updating Covert Networks’, Network Science, 1 (1), April, 68-94
20. Jude C. Hays, Aya Kachi and Robert J. Franzese, Jr. (2010), ‘A
Spatial Model Incorporating Dynamic, Endogenous Network
Interdependence: A Political Science Application’, Statistical
Methodology, 7 (3), May, 406-28
208
240
264
284
317
352
377
389
422
437
464
Advances in Political Methodology
vii
21. Robert J. Franzese, Jr., Jude C. Hays and Aya Kachi (2012),
‘Modeling History Dependence in Network-Behavior Coevolution’,
Political Analysis, 20 (2), Spring, 175-90 487
PART IV ADVANCES IN TEXT-ANALYTIC, CLASSIFICATION AND BIG-
DATA METHODS
22. Phillip A. Schrodt and David Van Brackle (2013), ‘Automated
Coding of Political Event Data’, in V.S. Subrahmanian (ed.),
Handbook of Computational Approaches to Counterterrorism,
Chapter 2, New York, USA: Springer, 23-49 505
23. Justin Grimmer and Gary King (2011), ‘General Purpose Computer-
Assisted Clustering and Conceptualization’, Proceedings of the
National Academy of Sciences, 108 (7), February, 2643-50 532
24. Vito D’Orazio, Steven T. Landis, Glenn Palmer and Philip Schrodt
(2014), ‘Separating the Wheat from the Chaff: Applications of
Automated Document Classification Using Support Vector
Machines’, Political Analysis, 22 (2), Spring, 224-42 540
25. Justin Grimmer and Brandon M. Stewart (2013), ‘Text as Data: The
Promise and Pitfalls of Automatic Content Analysis Methods for
Political Texts’, Political Analysis, 21 (3), Summer, 267-97 559
26. Martin Elff (2013), ‘A Dynamic State-Space Model of Coded
Political Texts’, Political Analysis, 21 (2), Spring, 217-32 590
27. Christopher Lucas, Richard A. Nielson, Margaret E. Roberts,
Brandon M. Stewart, Alex Storer and Dustin Tingley (2015),
‘Computer-assisted Text Analysis for Comparative Politics’,
Political Analysis, 23 (2), Spring, 254-77 606
PART V ADVANCES IN NONPARAMETRIC AND DESIGN-BASED
INFERENCE METHODS
28. Jasjeet S. Sekhon (2008), ‘The Neyman-Rubin Model of Causal
Inference and Estimation via Matching Methods’, in Janet M. Box-
Steffensmeier, Henry E. Brady and David Collier (eds), Oxford
Handbook of Political Methodology, Part IV, Chapter 11, Oxford,
UK: Oxford University Press, 271-99 633
29. Jasjeet S. Sekhon and Rocio Titiunik (2012), ‘When Natural
Experiments Are Neither Natural Nor Experiments’, American
Political Science Review, 106 (1), February, 35-57 662
30. Peter M. Aronow and Allison Carnegie (2013), ‘Beyond LATE:
Estimation of the Average Treatment Effect with an Instrumental
Variable’, Political Analysis, 21 (4), Autumn, 492-506 685
Advances in Political Methodology
viii
31. Kosuke Imai, Luke Keele, Dustin Tingley and Teppei Yamamoto
(2011), ‘Unpacking the Black Box of Causality: Learning about
Casual Mechanisms from Experimental and Observational Studios1.
American Political Science Review, 105 (4), November, 765 -SO
32. Kosuke Imai and Marc Ratkovie (2013), Estimating Treatment
Effect Heterogeneity in Randomized Program Evaluation’. Annals
of Applied Statistics, 7(1), 443-70
33. Luke Keele and Rocío Titiunik (2016), ‘Natural Experiments Based
on Geography’, Political Science Research and Methods, 4(1).
January, 65-95
34. Luke Keele, Rocío Titiunik and José R. /ubi/arreta (2015),
‘Enhancing a Geographic Regression Discontinuity Design
Through Matching to Estimate the Effect of Ballot Initiatives on
Voter Turnout’, Journal of the Royal Statistical Society: Statistics in
Society, Series A, 178 (I), 223-39
700
725
753
754
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| owner | DE-12 DE-473 DE-BY-UBG DE-355 DE-BY-UBR |
| owner_facet | DE-12 DE-473 DE-BY-UBG DE-355 DE-BY-UBR |
| physical | xix, 800 Seiten Illustrationen, Diagramme, Karten |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Edward Elgar Publishing |
| record_format | marc |
| series2 | Elgar research collection |
| spellingShingle | Advances in political methodology Politische Wissenschaft Politische Wissenschaft (DE-588)4076229-4 gnd Methode (DE-588)4038971-6 gnd |
| subject_GND | (DE-588)4076229-4 (DE-588)4038971-6 (DE-588)4143413-4 |
| title | Advances in political methodology |
| title_auth | Advances in political methodology |
| title_exact_search | Advances in political methodology |
| title_full | Advances in political methodology edited by Robert J. Franzese, Jr. ( Professor of Political Science, University of Michigan, Michigan, USA and Fellow and 15th President, Society of Political Methodology, Washington University in St. Louis, Missouri, USA) |
| title_fullStr | Advances in political methodology edited by Robert J. Franzese, Jr. ( Professor of Political Science, University of Michigan, Michigan, USA and Fellow and 15th President, Society of Political Methodology, Washington University in St. Louis, Missouri, USA) |
| title_full_unstemmed | Advances in political methodology edited by Robert J. Franzese, Jr. ( Professor of Political Science, University of Michigan, Michigan, USA and Fellow and 15th President, Society of Political Methodology, Washington University in St. Louis, Missouri, USA) |
| title_short | Advances in political methodology |
| title_sort | advances in political methodology |
| topic | Politische Wissenschaft Politische Wissenschaft (DE-588)4076229-4 gnd Methode (DE-588)4038971-6 gnd |
| topic_facet | Politische Wissenschaft Methode Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029749335&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029749335&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT franzeserobertj advancesinpoliticalmethodology |