Fraser, H., Parker, T., Nakagawa, S., Barnett, A. & Fidler, F. (2018, accepted). The prevalence of Questionable Research Practices in Ecology and Evolution. PLoS ONE.

Hemming, V., Walshe, T., Burgman, M., Hanea, A. & Fidler, F. (2018). Eliciting improved quantitative judgements using the IDEA Protocol: A case study in natural resource management. PLoS ONE.

Fidler, F., Fraser, H., McCarthy, M. & Game, E. (2018, in press) Improving the transparency of statistical reporting in Conservation Letters. Conservation Letters.

Selinske, M., Garrard, G.E., Bekessy, S.A., Gordon, A., Kusmanoff, A. & Fidler, F. (2018). Revisiting the promise of conservation psychology. Conservation Biology

Fidler, F., Singelton Thorn, F., Barnett, A., Kambouris, S. & Kruger, A. (2018, in press). The epistemic importance of establishing the absence of effects. Advanced Methods and Practices in Psychology, 2.

Parker, T., Griffith, S., Bronstein, J., Fidler, F. et al (2018, in press) Empowering peer reviewers with checklists to improve transparency. Nature Ecology & Evolution.


Benjamin, D., Berger, J., Johannesson, M., Nosek, B., Wagenmakers, E., Berk, R. et al (inc Fidler, F.) (2017). Redefine Statistical Significance Nature Human Behaviour.

Fidler, F., Chee, Y.E., Wintle, B.C., Burgman, M., McCarthy, M. & Gordon, A. (2017). Meta-research for evaluating reproducibility in ecology and evolution. BioScience, 67, 282-289.

Chee, Y., Wintle, B. & Fidler, F. (2017). Understanding uptake of decision support in conservation and natural resource management. In Bunnefeld, E. Nicholson & E.J. Milner-Gulland (Eds) Decision-Making in Conservation and Natural Resource Management – Uniting Top-Down and Bottom-Up Approaches. Cambridge University Press.

De Little, S.C., Casas-Mulet, R., Patulny, L., Wand, J., Miller, K.A., Fidler, F. et al. (2017). Minimising biases in expert elicitations to inform environmental management: Case studies from environmental flow in Australia. Environmental modelling and software, 100, 146-158.

Kusmanoff, A., Fidler, F., Gordon, A., Bekessy, S.A. (2017) Decline of ‘biodiversity’ in conservation policy discourse in Australia. Environmental Science & Policy, 77, 160-165.


Parker, T.H., Forstmeier, W., Koricheva, J., Fidler, F., Hadfield, J.D., Chee, Y.E. (2016). Fraud not a primary cause of irreproducible results: A reply to Clark et al. Trends in Ecology & Evolution, 31, 900.

Parker, T.H., Forstmeier, W., Koricheva, J., Fidler, F., Hadfield, J.D., Chee, Y.E. et al. (2016). Transparency in ecology and evolution: real problems, real solutions. Trends in Ecology & Evolution, 31, 711-719.

Parker, T.H., Nakagawa, S., Gurevitch, J. & Improving Inference in Biology and Ecology Workshop (Fidler participant). Promoting transparency in evolutionary biology and ecology. Ecology Letters, 19, 726-728. 10.1111/ele.12610.

Kusmanoff, A.M., Hardy, M.J., Fidler, F., Maffey, G., Raymond, C., Reed, M.S. et al (2016). Framing the private land conservation conversation: Strategic framing of the benefits of conservation participation could increase landholder engagement. Environmental Science & Policy, 61, 124-128.

Hanae, A.,McBride, M., Burgman, M., Wintle, B., Fidler, F., Flander, L. et al. (2016). I_nvestigate D_iscuss E_stimate A_ggregate for structured expert judgement. International Journal of Forecasting, 33, 267-279. DOI:10.1016/j.iforecast.2016.02.008


Garrard, G., Fidler, F., Wintle, B.C., Chee, Yung En. & Bekessy, S.A. (2015). Beyond Advocacy: Making space for conservation scientists in public debate. Conservation Letters. DOI: 10.1111/conl.12193


Fidler, F. & Cumming, G. (2014). Yes, but don’t underestimate estimation. Psychological Science, 25, 1291-1292.

Fine, C. & Fidler, F. (2014). Sex and power: Why sex/gender neuroscience should motivate statistical reform. In J Clausen & N Levy (Eds), The Handbook of Neuroethics. Dordrecht: Springer Science & Business Media.


Abbott, J.D., Cumming, G., Fidler, F. & Lindell, A.K. (2013). The perception of positive and negative facial expressions in unilateral brain-damaged patients: A meta-analysis. Laterality: Asymmetries of Body, Brain and Cognition, 18, 437-459.

Wintle, B., Fidler, F., Vesk, P. & Moore, J. (2013). Improving visual estimation through active feedback. Methods in Ecology and Evolution, 4, 53-82.


Hicks, J.S., Burgman, M.A., Marewski, J.N., Fidler, F. & Gigerenzer, G. (2012). Decision making in a human population living sustainably. Conservation Biology, 26, 760-76.

Vaux, D.L., Fidler, F. & Cumming, G. (2012). Replicates and repeats—what is the difference and is it significant? A brief discussion of statistics and experimental design. EMBO reports, 13, 291-6.

McBride, M., Fidler, F. & Burgman, M. (2012). Evaluating the accuracy and calibration of expert predictions under uncertainty: Predicting the outcomes of ecological research. Diversity and Distributions, 18, 782-794.

Martin, T., Burgman, M., Fidler, F., Kuhnert, P., Low-Choy, S., McBride, M., Mengerson, K. (2012). Eliciting expert knowledge in conservation science. Conservation Biology, 26, 29-

Cumming, G., Fidler, F., Kalinowski, P., & Lai, J. (2012). The statistical recommendations of the American Psychological Association Publication Manual: Effect sizes, confidence intervals, and meta-analysis. Australian Journal of Psychology, 64, 138-146.

Fidler, F. & Cumming, G. (2012). Null Hypothesis Vs Effect Sizes. In Weiner, I. (Ed.) Handbook of Psychology, 2nd Ed. Wiley.

Lyon, A., Fidler, F. & Burgman, M. (2012). Judgement swapping improves group performance. Published proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) Fall Symposium on Machine Aggregation of Human Judgement.

Wintle, B., Moscaro, S., Fidler, F., McBride, M., Burgman, M., Flander, L., Saw, G., Twardy, C., Lyon, A. & Manning, B. (2012). The Intelligence Game: Assessing Delphi groups and structured question formats. Refereed Proceedings of the 2012 SECAU Security and Intelligence Congress.


Lai, J., Fidler, F. & Cumming, G. (2011). Subjective p intervals: Researchers underestimate the variability of p values over replication. Methodology, 8, 51-62.

Burgman, M., McBride, M., Ashton, R., Speirs-Bridge, A., Flander, L., Wintle, B., Fidler F, Rumpff, L. & Twardy C. (2011). Expert Status and Performance. PLoS One, 6, e22998.

Schwab, A., Abrahamson, E., Starbuck, W.H., & Fidler, F. (2011). Perspective—Researchers Should Make Thoughtful Assessments Instead of Null-Hypothesis Significance Tests. Organization Science, 22, 1105-1120.

Fidler, F. (2011). Ethics and Statistical Reform: Lessons from Medicine. In A. Panter & S. Sterba (Eds.) The ethics of quantitative methodology: A handbook for researchers. Taylor and Francis (Multivariate Application Book Series). Ch 17, pp. 445-462.

Fidler, F. & Cumming, G. (2011). From Hypothesis Testing to Estimation. In A. Panter & S. Sterba (Eds.) The ethics of quantitative methodology: A handbook for researchers. Taylor and Francis (Multivariate Application Book Series). Ch 11, pp. 293-312.


Kalinowski, P., Lai, J., Fidler, F. & Cumming, G. (2010). Qualitative Research: An essential part of Statistical Cognition. Statistics Education Research Journal, 9, 22-34.

Coulson, M., Healey, M., Fidler, F. & Cumming, G. (2010). Confidence Intervals permit, but don’t guarantee, better inference than statistical significance testing. Frontiers in Quantitative Psychology and Measurement, 1. doi: 10.3389/fpsyg.2010.00026.

Kalinowski, P. & Fidler, F. (2010). Interpreting ‘significance’: The difference between statistical and practical importance. Newborn and Infant Nursing Review, 10, 50-54.

Fidler, F. (2010). Statistical Significance, Result Worthiness and Evidence: What lessons are there for giftedness education in other disciplines? In B. Thompson & R. Subotnik (Eds.). Methodologies for conducting research on giftedness. Washington, USA: American Psychological Association. Ch 4, pp. 71-88.

Cumming, G., & Fidler, F. (2010). The new stats: Effect sizes and confidence intervals. In G. R. Hancock & R. O. Mueller (Eds.) The reviewers’ guide to quantitative methods in the social sciences. Ch 7, pp. 79-92. [commissioned for 2nd edition]

Fidler, F. (2010). The American Psychological Association Publication Manual Sixth Edition: Implications for teaching statistics. Data and context in statistics education: Towards an evidence-based society. Refereed Proceedings of ICOTS-8, Eighth International Conference on Teaching Statistics. Ljubljana, Slovenia.


Fidler, F. & Loftus, G. (2009). Why figures with error bars should replace p values: Some conceptual arguments and empirical demonstrations. Zeitschrift fuer Psychologie/Journal of Psychology, 217, 27-37.

Cumming, G. & Fidler, F. (2009). Confidence Intervals: Better answers to better questions. Zeitschrift fuer Psychologie/Journal of Psychology, 217, 15-26.

Speirs-Bridge, A., Fidler, F., McBride, M., Flander, L., Cumming, G. & Burgman, M. (2009). Reducing overconfidence in the interval judgements of experts. Risk Analysis, 30, 512 – 523.


Beyth-Marom, R., Fidler, F. & Cumming, G. (2008). Statistical Cognition: Towards evidence-based practice in statistics and statistics education. Statistics Education Research Journal, 7, 20-39.

Kalinowski, P., Fidler, F. & Cumming, G. (2008). Overcoming the inverse probability fallacy: A comparison of two teaching interventions. Methodology, 4, 152-158.

Faulkner, C., Fidler, F. & Cumming, G. (2008). The value of RCT evidence depends on the quality of statistical analysis. Behaviour Research and Therapy, 46, 270-281.

Walshe, T., Wintle, B., Fidler, F. & Burgman, M. (2007). Use of confidence intervals to demonstrate performance against forest management standards. Forest Ecology and Management, 247, 237-245.

Fidler, F., & Cumming, G. (2008). The new stats: Attitudes for the twenty-first century. In J.W. Osborne (Ed.). Best practice in quantitative methods (pp. 1-12). Ch 1, pp. 1-12.

Fidler, F., Faulkner, S., & Cumming, G. (2008). Analyzing and presenting outcomes: Focus on effect size estimates and confidence intervals. In A. M. Nezu & C. M. Nezu (Eds.) Evidence-based outcome research: A practical guide to conducting randomized controlled trials for psychosocial interventions. New York: OUP. Ch 15, pp. 315-334.


Wintle, B., Burgman, M. & Fidler, F. (2007). How fast should nanotechnology advance? Nature Nanotechnology, 2, 327.

Cumming, G., Fidler, F., & Vaux, D. L. (2007). Error bars in experimental biology. Journal of Cell Biology, 177, 7-11. [Reprinted in Journal of Experimental Medicine, 2007, 204, i11.]

Fidler, F. & Cumming, G. (2007). Lessons learned from statistical reform efforts in other disciplines. Special Issue: Statistical reform in school psychology (Thomas J. Kehle and Melissa A. Bray, Eds.) Psychology in the Schools, 44, 441-449.

Cumming, G., Fidler, F., Leonard, M., Kalinowski, P., Christiansen, A., Kleinig, A., Lo, J., McMenamin, N. & Wilson, S. (2007). Statistical reform in psychology: Is anything changing? Psychological Science, 18, 230-232.


Fidler, F., Burgman, M., Cumming, G. Buttrose, R. & Thomason. N. (2006). Impact of criticism of null hypothesis significance testing on statistical reporting practices in conservation biology. Conservation Biology, 20, 1539-1544.

Belia, S., Fidler, F., Williams, J. & Cumming, G. (2005). Researchers misunderstand confidence intervals and standard error bars. Psychological Methods, 10, 389-396.

Fidler, F., Thomason, N., Cumming, G., Finch, S. & Leeman, J. (2005). Still much to learn about confidence intervals. Reply to Rouder and Morey. Psychological Science, 16, 494-

Fidler, F., Cumming, G., Thomason, N., Pannuzzo, D., Smith, J., Fyffe, P., Edmonds, H., Harrington, C. & Schmitt, R. (2005). Toward improved statistical reporting in the Journal of Consulting and Clinical Psychology. Journal of Consulting and Clinical Psychology, 73, 136-143.

Fidler, F., Cumming, G., Burgman, M. & Thomason, N. (2004). Statistical reform in medicine, psychology and ecology. Journal of Socio Economics, 33, 615-630.

Fidler, F., Thomason, N., Cumming, G., Finch, S. & Leeman, J. (2004). Editors can lead researchers to confidence intervals but they can’t make them think: Statistical reform lessons from Medicine. Psychological Science, 15, 119-126.

Cumming, G., Williams, J., & Fidler, F. (2004). Replication, and researchers’ understanding of confidence intervals and standard error bars. Understanding Statistics, 3, 299-311.

Fidler, F. (2002). The 5th edition of the APA Publication Manual:  Why its statistics recommendations are so controversial. Educational and Psychological Measurement, 62, 749-770.

Fidler, F. & Thompson, B. (2001). Computing Correct Confidence Intervals for ANOVA fixed and random effect sizes. Educational and Psychological Measurement, 61, 575-604.


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