Ahlgren, P., & Waltman, L. (2014). The correlation between citation-based and expert-based assessments of publication channels: SNIP and SJR vs. Norwegian quality assessments. Journal of Informetrics,
8(4), 985–996.
Article
Google Scholar
Ajiferuke, I., & Famoye, F. (2015). Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models. Journal of Informetrics,
9(3), 499–513.
Article
Google Scholar
Bosquet, C., & Combes, P. P. (2013). Are academics who publish more also more cited? Individual determinants of publication and citation records. Scientometrics,
97(3), 831–857.
Article
Google Scholar
Brzezinski, M. (2015). Power laws in citation distributions: Evidence from Scopus. Scientometrics,
103(1), 213–228.
Article
Google Scholar
Chakraborty, T., Tammana, V., Ganguly, N., & Mukherjee, A. (2015). Understanding and modeling diverse scientific careers of researchers. Journal of Informetrics,
9(1), 69–78.
Article
Google Scholar
Clauset, A., Shalizi, C. R., & Newman, M. E. (2009). Power-law distributions in empirical data. SIAM Review,
51(4), 661–703.
MathSciNet
Article
MATH
Google Scholar
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Abingdon: Lawrence Erlbaum Associates.
MATH
Google Scholar
Cohen, J. (1992). A power primer. Psychological Bulletin,
112(1), 155–159. doi:10.1037/0033-2909.112.1.155.
Article
Google Scholar
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika,
16(3), 297–334.
Article
Google Scholar
Didegah, F., & Thelwall, M. (2013). Which factors help authors produce the highest impact research? Collaboration, journal and document properties. Journal of Informetrics,
7(4), 861–873.
Article
Google Scholar
Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge: Cambridge University Press.
Book
Google Scholar
Else, H. (2015). Research funding formula tweaked after REF 2014 results. https://www.timeshighereducation.com/news/research-funding-formula-tweaked-after-ref-2014-results/2018685.article.
Eom, Y. H., & Fortunato, S. (2011). Characterizing and modeling citation dynamics. PLoS ONE,
6(9), e24926.
Article
Google Scholar
Ettori, S. (2015). The physics inside the scaling relations for X-ray galaxy clusters: Gas clumpiness, gas mass fraction and slope of the pressure profile. Monthly Notices of the Royal Astronomical Society,
446(3), 2629–2639.
Article
Google Scholar
Finardi, U. (2013). Correlation between journal impact factor and citation performance: An experimental study. Journal of Informetrics,
7(2), 357–370.
Article
Google Scholar
Franceschet, M., & Costantini, A. (2011). The first Italian research assessment exercise: A bibliometric perspective. Journal of Informetrics,
5(2), 275–291.
Article
Google Scholar
Garanina, O. S., & Romanovsky, M. Y. (2015). Citation distribution of individual scientist: Approximations of stretch exponential distribution with power law tails. In A. A. Salah, Y. Tonta, A. A. Akdag Salah, C. Sugimoto, & U. Al (Eds.), Proceedings of ISSI 2015 (pp. 272–277). Turkey: Bogaziçi University Printhouse.
Google Scholar
Gillespie, C.S. (2015). Fitting heavy tailed distributions: the poweRlaw package. Journal of Statistical Software, 64(2), 1–16. http://www.jstatsoft.org/v64/i02/paper.
Hartley, J., & Sydes, M. (1997). Are structured abstracts easier to read than traditional ones? Journal of Research in Reading,
20(2), 122–136.
Article
Google Scholar
HEFCE. (2015). The metric tide: Correlation analysis of REF2014 scores and metrics. Supplementary Report II to the Independent review of the role of metrics in research assessment and management. Bristol: Hefce. http://www.hefce.ac.uk/pubs/rereports/Year/2015/metrictide/Title,104463,en.html.
Hemphill, J. F. (2003). Interpreting the magnitudes of correlation coefficients. American Psychologist,
58(1), 78–79.
Article
Google Scholar
Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America,
102(46), 16569–16572.
Article
Google Scholar
Hyland, K. (1999). Academic attribution: Citation and the construction of disciplinary knowledge. Applied Linguistics,
20(3), 341–367.
MathSciNet
Article
Google Scholar
Kostoff, R. (2007). The difference between highly and poorly cited medical articles in the journal Lancet. Scientometrics,
72, 513–520.
Article
Google Scholar
Kousha, K., & Thelwall, M. (2015). Web indicators for research evaluation, part 3: Books and non-standard outputs. El Profesional de la Información,
24(6), 724–736. doi:10.3145/epi.2015.nov.04.
Article
Google Scholar
Larivière, V., & Gingras, Y. (2010). On the relationship between interdisciplinarity and scientific impact. Journal of the American Society for Information Science and Technology,
61, 126–131.
Article
Google Scholar
Limpert, E., Stahel, W. A., & Abbt, M. (2001). Lognormal distribution across sciences: Key and clues. BioScience,
51(5), 341–351.
Article
Google Scholar
Lipsey, M.W., Puzio, K., Yun, C., Hebert, M.A., Steinka-Fry, K., Cole, M.W., et al. (2012). Translating the statistical representation of the effects of education interventions into more readily interpretable forms. Washington, DC: US Dept of Education, National Center for Special Education Research, Institute of Education Sciences, NCSER 2013-3000.
Liu, G., Qi, X. L., Robert, N., Dick, A. J., & Wright, G. A. (2012). Ultrasound-guided identification of cardiac imaging windows. Medical Physics,
39(6), 3009–3018.
Article
Google Scholar
Low, W. J., Thelwall, M., & Wilson, P. (2015). Stopped sum models for citation data. In A. A. Salah, Y. Tonta, A. A. AkdagSalah, C. Sugimoto, & U. Al (Eds.), Proceedings of ISSI 2015 Istanbul: 15th international society of scientometrics and informetrics conference (pp. 184–194). Istanbul: Bogaziçi University Printhouse.
Google Scholar
Mohammadi, E., & Thelwall, M. (2014). Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows. Journal of the American Society for Information Science and Technology,
65(8), 1627–1638.
Article
Google Scholar
Onodera, N., & Yoshikane, F. (2015). Factors affecting citation rates of research articles. Journal of the Association for Information Science and Technology,
66(4), 739–764.
Article
Google Scholar
Oppenheim, C. (2000). Do patent citations count? In B. Cronin & H. B. Atkins (Eds.), The web of knowledge: A festschrift in honor of Eugene Garfield (pp. 405–432). Metford: Information Today Inc. ASIS Monograph Series.
Google Scholar
Pennock, D. M., Flake, G. W., Lawrence, S., Glover, E. J., & Giles, C. L. (2002). Winners don’t take all: Characterizing the competition for links on the web. Proceedings of the National Academy of Sciences,
99(8), 5207–5211.
Article
MATH
Google Scholar
Persson, O., Glänzel, W., & Danell, R. (2004). Inflationary bibliometric values: The role of scientific collaboration and the need for relative indicators in evaluative studies. Scientometrics,
60(3), 421–432.
Article
Google Scholar
Radicchi, F., Fortunato, S., & Castellano, C. (2008). Universality of citation distributions: Toward an objective measure of scientific impact. Proceedings of the National Academy of Sciences,
105(45), 17268–17272.
Article
Google Scholar
Redner, S. (1998). How popular is your paper? An empirical study of the citation distribution. The European Physical Journal B-Condensed Matter and Complex Systems,
4(2), 131–134.
Article
Google Scholar
Sud, P., & Thelwall, M. (2014). Evaluating altmetrics. Scientometrics,
98(2), 1131–1143. doi:10.1007/s11192-013-1117-2.
Article
Google Scholar
Thelwall, M. (2006). Interpreting social science link analysis research: A theoretical framework. Journal of the American Society for Information Science and Technology,
57(1), 60–68.
Article
Google Scholar
Thelwall, M. (2016). The discretised lognormal and hooked power law distributions for complete citation data: Best options for modelling and regression. Journal of Informetrics,
10(2), 336–346. doi:10.1016/j.joi.2015.12.007.
Article
Google Scholar
Thelwall, M., & Fairclough, R. (2015). The influence of time and discipline on the magnitude of correlations between citation counts and quality scores. Journal of Informetrics,
9(3), 529–541. doi:10.1016/j.joi.2015.05.006.
Article
Google Scholar
Thelwall, M., & Kousha, K. (2015a). Web indicators for research evaluation, Part 1: Citations and links to academic articles from the web. El Profesional de la Información,
24(5), 587–606. doi:10.3145/epi.2015.sep.08.
Article
Google Scholar
Thelwall, M., & Kousha, K. (2015b). Web indicators for research evaluation, Part 2: Social media metrics. El Profesional de la Información,
24(5), 607–620. doi:10.3145/epi.2015.sep.09.
Article
Google Scholar
Thelwall, M., & Wilson, P. (2014). Distributions for cited articles from individual subjects and years. Journal of Informetrics,
8(4), 824–839.
Article
Google Scholar
Thelwall, M., & Wilson, P. (in press). Mendeley readership altmetrics for medical articles: An analysis of 45 fields. Journal of the Association for Information Science and Technology. doi:10.1002/asi.23501.
van Raan, A. (1998). The influence of international collaboration on the impact of research results: Some simple mathematical considerations concerning the role of self-citations. Scientometrics,
42(3), 423–428.
Article
Google Scholar
Wainer, J., & Vieira, P. (2013). Correlations between bibliometrics and peer evaluation for all disciplines: the evaluation of Brazilian scientists. Scientometrics,
96(2), 395–410.
Article
Google Scholar
Wilsdon, J., Allen, L., Belfiore, E., Campbell, P., Curry, S., Hill, S., et al. (2015). The metric tide: Report of the independent review of the role of metrics in research assessment and management. http://www.hefce.ac.uk/pubs/rereports/Year/2015/metrictide/Title,104463,en.html.