메뉴 건너뛰기




Volumn 92, Issue 2, 2012, Pages 377-390

The generalized propensity score methodology for estimating unbiased journal impact factors

Author keywords

Causal inference; Generalized propensity score; Journal impact factor; Rubin Causal Model

Indexed keywords


EID: 84864290657     PISSN: 01389130     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11192-012-0670-4     Document Type: Article
Times cited : (16)

References (37)
  • 2
    • 44849130813 scopus 로고    scopus 로고
    • Citation counts for research evaluation: Standards of good practice for analyzing bibliometric data and presenting and interpreting results
    • Bornmann, L., Mutz, R., Neuhaus, C., & Daniel, H.-D. (2008). Citation counts for research evaluation: Standards of good practice for analyzing bibliometric data and presenting and interpreting results. Ethics in Science and Environmental Politics, 8, 93-102.
    • (2008) Ethics in Science and Environmental Politics , vol.8 , pp. 93-102
    • Bornmann, L.1    Mutz, R.2    Neuhaus, C.3    Daniel, H.-D.4
  • 3
    • 2342470468 scopus 로고
    • Some data on the distribution of journal publication types in the Science Citation Index Database
    • Braun, T., Glänzel, W., & Schubert, A. (1989). Some data on the distribution of journal publication types in the Science Citation Index Database. Scientometrics, 15, 325-330.
    • (1989) Scientometrics , vol.15 , pp. 325-330
    • Braun, T.1    Glänzel, W.2    Schubert, A.3
  • 4
    • 0014297593 scopus 로고
    • The effectiveness of adjustment by subclassification in removing bias in observational studies
    • Cochran, W. G. (1968). The effectiveness of adjustment by subclassification in removing bias in observational studies. Biometrics, 24(2), 295-313.
    • (1968) Biometrics , vol.24 , Issue.2 , pp. 295-313
    • Cochran, W.G.1
  • 6
    • 84858079671 scopus 로고    scopus 로고
    • Generalized propensity score for estimating the average treatment effect of multiple treatments
    • doi: 10. 1002/sim. 4168 (published online February 24, 2011
    • Feng, P., Zhou, X.-H., Zou, Q.-M., Fan, M.-Y., & Li, X.-S. (2011). Generalized propensity score for estimating the average treatment effect of multiple treatments. Statistics in Medicine. doi: 10. 1002/sim. 4168 (published online February 24, 2011).
    • (2011) Statistics in Medicine
    • Feng, P.1    Zhou, X.-H.2    Zou, Q.-M.3    Fan, M.-Y.4    Li, X.-S.5
  • 7
    • 37049230834 scopus 로고
    • Citation indexes to science: A new dimension in documentation through association of ideas
    • Garfield, E. (1955). Citation indexes to science: A new dimension in documentation through association of ideas. Science, 122, 108-111.
    • (1955) Science , vol.122 , pp. 108-111
    • Garfield, E.1
  • 9
    • 29944438252 scopus 로고    scopus 로고
    • The history and meaning of the Journal Impact Factor
    • Garfield, E. (2006). The history and meaning of the Journal Impact Factor. Journal of the American Medical Association, 295(1), 90-93.
    • (2006) Journal of the American Medical Association , vol.295 , Issue.1 , pp. 90-93
    • Garfield, E.1
  • 10
    • 19044365589 scopus 로고    scopus 로고
    • Journal impact measures in bibliometric research
    • Glänzel, W., & Moed, H. (2002). Journal impact measures in bibliometric research. Scientometrics, 53(2), 171-193.
    • (2002) Scientometrics , vol.53 , Issue.2 , pp. 171-193
    • Glänzel, W.1    Moed, H.2
  • 14
    • 4944223958 scopus 로고    scopus 로고
    • Causal inference with general treatment regimes: Generalizing the propensity score
    • Imai, K., & van Dyk, D. A. (2004). Causal inference with general treatment regimes: Generalizing the propensity score. Journal of the American Statistical Association, 99(467), 854-866.
    • (2004) Journal of the American Statistical Association , vol.99 , Issue.467 , pp. 854-866
    • Imai, K.1    van Dyk, D.A.2
  • 15
    • 0000724291 scopus 로고    scopus 로고
    • The role of propensity score in estimating dose-response functions
    • Imbens, G. (2000). The role of propensity score in estimating dose-response functions. Biometrika, 87(3), 706-710.
    • (2000) Biometrika , vol.87 , Issue.3 , pp. 706-710
    • Imbens, G.1
  • 16
    • 84858439011 scopus 로고    scopus 로고
    • Evaluating continuous training programmes by using the generalized propensity score
    • Kluve, J., Schneider, H., Uhlendorff, A., & Zhao, Z. (2012). Evaluating continuous training programmes by using the generalized propensity score. Journal of the Royal Statistical Society A, 175(Part 2), 1-31.
    • (2012) Journal of the Royal Statistical Society A , vol.175 , Issue.PART 2 , pp. 1-31
    • Kluve, J.1    Schneider, H.2    Uhlendorff, A.3    Zhao, Z.4
  • 17
    • 78951493273 scopus 로고    scopus 로고
    • How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science
    • Leydesdorff, L., & Bornmann, L. (2011). How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science. Journal of the American Society for Information Science and Technology, 62(2), 217-229.
    • (2011) Journal of the American Society for Information Science and Technology , vol.62 , Issue.2 , pp. 217-229
    • Leydesdorff, L.1    Bornmann, L.2
  • 18
    • 79959371997 scopus 로고    scopus 로고
    • Optimal nonbipartite matching and its statistical applications
    • Lu, B., Greevey, R., Xu, X., & Beck, C. (2011). Optimal nonbipartite matching and its statistical applications. American Statistician, 65(1), 21-30.
    • (2011) American Statistician , vol.65 , Issue.1 , pp. 21-30
    • Lu, B.1    Greevey, R.2    Xu, X.3    Beck, C.4
  • 19
    • 84982392424 scopus 로고
    • Improving the accuracy of the Institute for Scientific Information's Journal Impact Factor
    • Moed, H. F., & van Leeuwen, T. N. (1995). Improving the accuracy of the Institute for Scientific Information's Journal Impact Factor. Journal of the American Society of Information Science, 46, 461-467.
    • (1995) Journal of the American Society of Information Science , vol.46 , pp. 461-467
    • Moed, H.F.1    van Leeuwen, T.N.2
  • 20
    • 0001404478 scopus 로고    scopus 로고
    • Towards appropriate indicators of journal impact
    • Moed, H. F., van Leeuwen, T. N., & Reeduk, J. (1999). Towards appropriate indicators of journal impact. Scientometrics, 46(3), 575-589.
    • (1999) Scientometrics , vol.46 , Issue.3 , pp. 575-589
    • Moed, H.F.1    van Leeuwen, T.N.2    Reeduk, J.3
  • 21
    • 84857025038 scopus 로고    scopus 로고
    • Skewed citation distributions and bias factors: Solutions to two core problems with the journal impact factor
    • in press
    • Mutz, R., & Daniel, H.-D. (2012, in press). Skewed citation distributions and bias factors: Solutions to two core problems with the journal impact factor. Journal of Infometrics.
    • (2012) Journal of Infometrics
    • Mutz, R.1    Daniel, H.-D.2
  • 22
    • 58449136394 scopus 로고    scopus 로고
    • The publication and citation impact profile of Angewandte Chemie and the Journal of the American Chemical Society based on the sections of Chemical Abstracts: A case study on the limitations of the Journal Impact Factor
    • Neuhaus, C., Marx, W., & Daniel, H.-D. (2009). The publication and citation impact profile of Angewandte Chemie and the Journal of the American Chemical Society based on the sections of Chemical Abstracts: A case study on the limitations of the Journal Impact Factor. Journal of the American Society for Information Science and Technology, 60(1), 176-183.
    • (2009) Journal of the American Society for Information Science and Technology , vol.60 , Issue.1 , pp. 176-183
    • Neuhaus, C.1    Marx, W.2    Daniel, H.-D.3
  • 24
    • 84949193513 scopus 로고
    • Reducing bias in observational studies using subclassification on the propensity score
    • Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387), 516-524.
    • (1984) Journal of the American Statistical Association , vol.79 , Issue.387 , pp. 516-524
    • Rosenbaum, P.R.1    Rubin, D.B.2
  • 25
    • 58149417330 scopus 로고
    • Estimating causal effects of treatments in randomized and nonrandomized studies
    • Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688-701.
    • (1974) Journal of Educational Psychology , vol.66 , pp. 688-701
    • Rubin, D.B.1
  • 26
    • 0001599001 scopus 로고
    • Assignment to treatment group on the basis of a covariate
    • Rubin, D. B. (1977). Assignment to treatment group on the basis of a covariate. Journal of Educational Statistics, 2(1), 1-26.
    • (1977) Journal of Educational Statistics , vol.2 , Issue.1 , pp. 1-26
    • Rubin, D.B.1
  • 27
    • 10044230409 scopus 로고    scopus 로고
    • Teaching statistical inference for causal effects in experiments and observational studies
    • Rubin, D. B. (2004). Teaching statistical inference for causal effects in experiments and observational studies. Journal of Educational and Behavioral Statistics, 29(3), 343-367.
    • (2004) Journal of Educational and Behavioral Statistics , vol.29 , Issue.3 , pp. 343-367
    • Rubin, D.B.1
  • 28
    • 14944344423 scopus 로고    scopus 로고
    • Causal inference using potential outcomes: Design, modeling, decisions
    • Rubin, D. B. (2005). Causal inference using potential outcomes: Design, modeling, decisions. Journal of the American Statistical Association, 100(469), 322-331.
    • (2005) Journal of the American Statistical Association , vol.100 , Issue.469 , pp. 322-331
    • Rubin, D.B.1
  • 30
    • 33846253571 scopus 로고    scopus 로고
    • The design versus the analysis of observational studies for causal effects: Parallels with the design of randomized trials
    • Rubin, D. B. (2007). The design versus the analysis of observational studies for causal effects: Parallels with the design of randomized trials. Statistics in Medicine, 26, 20-36.
    • (2007) Statistics in Medicine , vol.26 , pp. 20-36
    • Rubin, D.B.1
  • 31
    • 0029959044 scopus 로고    scopus 로고
    • Matching using estimated propensity scores: Relating theory in practice
    • Rubin, D. B., & Thomas, N. (1996). Matching using estimated propensity scores: Relating theory in practice. Biometrics, 52, 249-264.
    • (1996) Biometrics , vol.52 , pp. 249-264
    • Rubin, D.B.1    Thomas, N.2
  • 32
    • 63549149056 scopus 로고    scopus 로고
    • SAS Institute Inc, Cary, NC: SAS Institute Inc
    • SAS Institute Inc. (2009). SAS/STAT 9. 2 user's guide. Cary, NC: SAS Institute Inc.
    • (2009) SAS/STAT 9.2 User's Guide
  • 33
    • 77449128579 scopus 로고    scopus 로고
    • The multiple propensity score as control for bias in the comparison of more than two treatment arms. An introduction from a case study in mental health
    • Spreeuwenberg, M. D., Bartak, A., Croon, M. A., Hagenaars, J. A., Bussbach, J. J. V., Andrea, H., et al. (2010). The multiple propensity score as control for bias in the comparison of more than two treatment arms. An introduction from a case study in mental health. Medical Care, 48(2), 166-174.
    • (2010) Medical Care , vol.48 , Issue.2 , pp. 166-174
    • Spreeuwenberg, M.D.1    Bartak, A.2    Croon, M.A.3    Hagenaars, J.A.4    Bussbach, J.J.V.5    Andrea, H.6
  • 35
    • 84863842264 scopus 로고    scopus 로고
    • Impact factor: Outdated artifact or stepping-stone to journal certification?
    • (accepted paper
    • Vanclay, J. K. (2012). Impact factor: Outdated artifact or stepping-stone to journal certification? Scientometrics (accepted paper).
    • (2012) Scientometrics
    • Vanclay, J.K.1
  • 36
    • 0034955507 scopus 로고    scopus 로고
    • The multiple propensity score for analysis of dose-response relationships in drug safety studies
    • Wang, J., Donnan, P. T., Steinke, D., & MacDonald, T. M. (2001). The multiple propensity score for analysis of dose-response relationships in drug safety studies. Pharmacoepidemiology and Drug Safety, 10, 105-111.
    • (2001) Pharmacoepidemiology and Drug Safety , vol.10 , pp. 105-111
    • Wang, J.1    Donnan, P.T.2    Steinke, D.3    Macdonald, T.M.4
  • 37
    • 15344348967 scopus 로고    scopus 로고
    • Using propensity score subclassification for multiple treatment doses to evaluate a national antidrug media campaign
    • Zanutto, E., Lu, B., & Hornik, R. (2005). Using propensity score subclassification for multiple treatment doses to evaluate a national antidrug media campaign. Journal of Educational and Behavioral Statistics, 30(1), 59-73.
    • (2005) Journal of Educational and Behavioral Statistics , vol.30 , Issue.1 , pp. 59-73
    • Zanutto, E.1    Lu, B.2    Hornik, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.