Biography
Professor Tom Stanley is a Meta-Analysis Professor in Deakin Business School. For 31 years, Tom taught many different courses in economics, statistics, and the humanities at Hendrix College, an elite, nationally recognized, undergraduate teaching university. In spite of his heavy teaching load of 6 or 7 different courses per year, his pioneering work on meta-analysis has received wide acclaim, with nearly all meta-analyses of economics research using the methods and the research framework developed and introduced in his papers. In particular, Stanley and Jarrell (Journal of Economic Surveys, 1989) was the first paper on meta-analysis in economics, introducing a new empirical review and assessment methodology, meta-regression analysis, specifically designed to evaluate econometric research findings. This paper along with meta-regression analysis, in general, was chosen by the editors of the Journal of Economic Survey in 2011 as one of the four most important developments in economics over the last quarter century. His paper, “Wheat from chaff: Meta-analysis as quantitative literature review,” published in the Journal of Economic Perspectives (a leading American Economic Association journal) in 2001, has become the standard reference in the field of meta-regression with 854 citations.
Tom has published dozens of papers, often along with Alfred Deakin Professor, Chris Doucouliagos, that develop new methods of meta-analysis and meta-regression and that apply these methods to a wide range of specific research fields within economics as well as health and psychology. Currently, he is developing and applying new approaches for ‘meta-science’ that investigate the credibility of large areas of research (e.g., economics and psychology) through meta-analysis surveys of many thousands of research papers (Ioannidis et al., 2017; Stanley et al., 2018). Aside from his active research programme, Stanley is a member of DeLMAR (Deakin Lab for the Meta-Analysis of Research), gives numerous workshops and presentations, and co-teaches a PhD class on meta-analysis, MMM909 Meta-Analysis Research Methods.
Read more on Tom's profileResearch interests
- Meta-Analysis
- Labour Economics
- Meta-Science
Affiliations
- Associate Editor, Journal of Economic Surveys.
- Founding Member and Convener, MAER-Net (Meta-Analysis of Economics Research-Network).
- Elected Member, SRSM (Society of Research Synthesis Methods).
Teaching interests
- Meta-Analysis
- Econometrics
- Economics
Awards
- Organized the 2016 MAER-Net Colloquium at Hendrix College, USA, 1-2 October 2016.
- Czech Science Foundation, 15-02411S, 'Development and Application of Meta-Regression Methods in Economics', 50,000 CZK each year, Czech Republic, 2015-2017.
- Czech National Bank, 'A Meta-Analysis of Empirical Evidence for the Calibration of the CNB’s Core Model', Czech Republic, 2014-2015.
- UK’s Department for International Development, $18,000 to mentor funded research teams on meta-analysis, 2013-2015.
- UK’s Department for International Development, $11,000 to mentor three funded research teams on meta-analysis, United Kingdom, 2011-2012.
- UK’s Department for International Development, $40,000 for a Workshop and Colloquium on meta-analysis, United Kingdom, 2010-2011.
- Organized the 2011 MAER-Net Colloquium at University of Cambridge, United Kingdom, 16-18 Sept 2011.
- Organized the 2010 MAER-Net Colloquium at Hendrix College, 1-2 October 2010.
- Environmental Protection Agency STAR (Science to Achieve Results) Grant #RD-832-421-01 $400,000 (with Randall Rosenberger), USA, 2005-2009.
- Anbar Electronic Intelligence Citation of Excellence, 1999.
- Distinguished Paper Award, Southwestern Society of Economists, 1992.
Publications
Power and bias in industrial relations research
A Doucouliagos, H Doucouliagos, T Stanley
(2024), Vol. 62, pp. 3-27, British Journal of Industrial Relations, C1
Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics
F Bartoš, M Maier, E Wagenmakers, F Nippold, H Doucouliagos, J Ioannidis, W Otte, M Sladekova, T Deresssa, S Bruns, D Fanelli, T Stanley
(2024), Research Synthesis Methods, C1
Meta-analyses of partial correlations are biased: Detection and solutions
T Stanley, H Doucouliagos, T Havranek
(2024), Vol. 15, pp. 313-325, Research Synthesis Methods, C1
Exploring open science practices in behavioural public policy research
Maximilian Maier, František Bartoš, Nichola Raihani, David Shanks, T Stanley, Eric-Jan Wagenmakers, Adam Harris
(2024), Vol. 11, pp. 1-8, Royal Society Open Science, London, Eng., C1
Estimating the extent of selective reporting: An application to economics
S Bruns, T Deressa, T Stanley, C Doucouliagos, J Ioannidis
(2024), Research Synthesis Methods, C1
T Stanley, J Ioannidis, M Maier, H Doucouliagos, W Otte, F Bartoš
(2023), Vol. 157, pp. 53-58, Journal of Clinical Epidemiology, C1
Correct standard errors can bias meta-analysis
T Stanley, H Doucouliagos
(2023), Vol. 14, pp. 515-519, Research Synthesis Methods, C1
The Significance of Data-Sharing Policy
Z Askarov, A Doucouliagos, H Doucouliagos, T Stanley
(2023), Vol. 21, pp. 1191-1226, Journal of the European Economic Association, C1-1
Meta-analyses in psychology often overestimate evidence for and size of effects
Frantisek Bartos, Maximilian Maier, David Shanks, T Stanley, Martina Sladekova, Eric-Jan Wagenmakers
(2023), Vol. 10, pp. 1-12, Royal Society Open Science, London, Eng., C1
Meta-analysis of social science research: A practitioner's guide
Z Irsova, H Doucouliagos, T Havranek, T Stanley
(2023), Journal of Economic Surveys, C1
Selective and (mis)leading economics journals: Meta-research evidence
Z Askarov, A Doucouliagos, H Doucouliagos, T Stanley
(2023), Journal of Economic Surveys, C1
Harnessing the Power of Excess Statistical Significance: Weighted and Iterative Least Squares
T Stanley, H Doucouliagos
(2022), Psychological Methods, Washington, D.C., C1
Frantisek Bartoš, Maximillian Maier, Eric-Jan Wagenmakers, H Doucouliagos, T Stanley
(2022), pp. 1-18, Research Synthesis Methods, London, Eng., C1
Beyond Random Effects: When Small-Study Findings Are More Heterogeneous
T Stanley, H Doucouliagos, J Ioannidis
(2022), Vol. 5, Advances in Methods and Practices in Psychological Science, C1
Detecting publication selection bias through excess statistical significance
T Stanley, H Doucouliagos, J Ioannidis, E Carter
(2021), Vol. 12, pp. 776-795, Research Synthesis Methods, Chichester, Eng., C1
Is Profit Sharing Productive? A Meta-Regression Analysis
H Doucouliagos, P Laroche, D Kruse, T Stanley
(2020), Vol. 58, pp. 364-395, British Journal of Industrial Relations, C1
REPORTING GUIDELINES FOR META-ANALYSIS IN ECONOMICS
T Havránek, T Stanley, H Doucouliagos, P Bom, J Geyer-Klingeberg, I Iwasaki, W Reed, K Rost, R van Aert
(2020), Vol. 34, pp. 469-475, Journal of Economic Surveys, C1
The Wages of Mothers' Labor: A Meta-Regression Analysis
M de Linde Leonard, T Stanley
(2020), Vol. 82, pp. 1534-1552, Journal of Marriage and Family, C1
Do house prices ride the wave of immigration?
M Larkin, Z Askarov, H Doucouliagos, C Dubelaar, M Klona, J Newton, T Stanley, A Vocino
(2019), Vol. 46, Journal of Housing Economics, C1
How credible is trade union research? Forty years of evidence on the monopoly-voice trade-off
C Doucouliagos, R Freeman, P Laroche, T Stanley
(2018), Vol. 71, pp. 287-305, ILR review, London, Eng., C1
Skating on thin evidence: Implications for public policy
H Doucouliagos, M Paldam, T Stanley
(2018), Vol. 54, pp. 16-25, European Journal of Political Economy, Ariel Univ, Ariel, ISRAEL, C1
DOES ICT GENERATE ECONOMIC GROWTH? A META-REGRESSION ANALYSIS
T Stanley, H Doucouliagos, P Steel
(2018), Vol. 32, pp. 705-726, Journal of Economic Surveys, C1
What meta-analyses reveal about the replicability of psychological research
T Stanley, Evan Carter, Hristos Doucouliagos
(2018), Vol. 144, pp. 1325-1346, Psychological bulletin, Washinton, D.C., C1
Where does profit sharing work best? A meta-analysis on the role of unions, culture, and values
Christos Doucouliagos, Patrice Laroche, Douglas Kruse, T Stanley
(2018), pp. 1-45, IZA discussion paper, Bonn, Germany, A6
Neither fixed nor random: weighted least squares meta-regression
T Stanley, H Doucouliagos
(2017), Vol. 8, pp. 19-42, Research synthesis methods, Chichester, Eng., C1
Finding the power to reduce publication bias
T Stanley, H Doucouliagos, J Ioannidis
(2017), Vol. 36, pp. 1580-1598, Statistics in Medicine, England, C1
The Power of Bias in Economics Research
J Ioannidis, T Stanley, H Doucouliagos
(2017), Vol. 127, pp. F236-F265, Economic Journal, C1
Limitations of PET-PEESE and other meta-analysis methods
T Stanley
(2017), Vol. 8, pp. 581-591, Social psychological and personality science, London, Eng., C1
B Becker, A Aloe, M Duvendack, T Stanley, J Valentine, A Fretheim, P Tugwell
(2017), Vol. 89, pp. 84-91, Journal of clinical epidemiology, Amsterdam, The Netherlands, C1
Quasi-experimental study designs series-paper 7: assessing the assumptions
T Bärnighausen, C Oldenburg, P Tugwell, C Bommer, C Ebert, M Barreto, E Djimeu, N Haber, H Waddington, P Rockers, B Sianesi, J Bor, G Fink, J Valentine, J Tanner, T Stanley, E Sierra, E Tchetgen, R Atun, S Vollmer
(2017), Vol. 89, pp. 53-66, Journal of clinical epidemiology, Amsterdam, The Netherlands, C1
T Stanley, S Massey
(2016), Vol. 79, pp. 41-45, Journal of clinical epidemiology, Amsterdam, The Netherlands, C1-1
Neither fixed nor random: weighted least squares meta-analysis
T Stanley, C Doucouliagos
(2015), Vol. 34, pp. 2116-2127, Statistics in medicine, Chichester, Eng., C1-1
M de Linde Leonard, T Stanley
(2015), Vol. 33, pp. 72-80, Labour economics, Amsterdam, The Netherlands, C1-1
Publication selection and the income elasticity of the value of a statistical life
H Doucouliagos, T Stanley, W Viscusi
(2014), Vol. 33, pp. 67-75, Journal of health economics, Amsterdam, The Netherlands, C1
Does the UK minimum wage reduce employment? A meta-regression analysis
M de Linde Leonard, T Stanley, H Doucouliagos
(2014), Vol. 52, pp. 499-520, British journal of industrial relations, Chichester, England, C1
Meta-regression approximations to reduce publication selection bias
T Stanley, C Doucouliagos
(2014), Vol. 5, pp. 60-78, Research synthetis methods, London, Eng., C1-1
Meta-analysis of economics research reporting guidelines
T Stanley, H Doucouliagos, M Giles, J Heckemeyer, R Johnston, P Laroche, J Nelson, M Paldam, J Poot, G Pugh, R Rosenberger, K Rost
(2013), Vol. 27, pp. 390-394, Journal of economic surveys, London, England, C1
Are all economic facts greatly exaggerated? Theory competition and selectivity
C Doucouliagos, T Stanley
(2013), Vol. 27, pp. 316-339, Journal of economic surveys, London, England, C1
What's to do about empirical economics?
T Stanley
(2013), Vol. 27, pp. 996-996, Journal of economic surveys, Chichester, Eng., C1-1
Publication selection in health policy research: the winner's curse hypothesis
J Costa-Font, A McGuire, T Stanley
(2013), Vol. 109, pp. 78-87, Health policy, Amsterdam, The Netherlands, C1-1
Does economics add up? An introduction to meta-regression analysis
T Stanley
(2013), Vol. 10, pp. 207-220, European journal of economics and economic policies: intervention, Cheltenham, Eng., C1-1
Meta-regression analysis in economics and business
T Stanley, H Doucouliagos
(2012), Oxon, England, A1
Pay for performance and corporate governance reform
H Doucouliagos, J Haman, T Stanley
(2012), Vol. 51, pp. 670-703, Industrial relations : a journal of economy and society, Cambridge, Mass, C1
Are estimates of the value of a statistical life exaggerated?
C Doucouliagos, T Stanley, M Giles
(2012), Vol. 31, pp. 197-206, Journal of health economics, Amsterdam, Netherlands, C1
Repeat Use of Human Recombinant Bone Morphogenetic Protein-2 for Second Level Lumbar Arthrodesis
Kern Singh, Mark Dumonski, Tom Stanley, Ravi Ponnappan, Frank Phillips
(2011), Vol. 36, pp. 192-196, SPINE, United States, C1-1
Could it be better to discard 90% of the data? A statistical paradox
T Stanley, S Jarrell, H Doucouliagos
(2010), Vol. 64, pp. 70-77, The American statistician, Alexandria, Va., C1
Publication selection bias in minimum-wage research? A meta-regression analysis
C Doucouliagos, T Stanley
(2009), Vol. 47, pp. 406-428, British journal of industrial relations, London, England, C1
Picture this : a simple graph that reveals much ado about research
T Stanley, H Doucouliagos
(2009), Vol. 24, pp. 170-191, Journal of economic surveys, Oxford, England, C1
Percutaneous Treatment of Vertebral Compression Fractures A Meta-analysis of Complications
Michael Lee, Mark Dumonski, Patrick Cahill, Tom Stanley, Daniel Park, Kern Singh
(2009), Vol. 34, pp. 1228-1232, SPINE, United States, C1-1
Meta-regression analysis as the socio-economics of economics research
T Stanley, C Doucouliagos, S Jarrell
(2008), Vol. 37, pp. 276-292, Journal of socio-economics, Amsterdam, Netherlands, C1
Publication bias in union-productivity research?
C Doucouliagos, P Laroche, T Stanley
(2005), Vol. 60, pp. 320-344, Relations Industrielles., Quebec, Canada, C1
An empirical critique of the Lucas critique
T Stanley
(2000), Vol. 29, pp. 91-107, Journal of socio-economics, Amsterdam, The Netherlands, C1-1
Gender wage discrimination bias? A meta-regression analysis
T Stanley, S Jarrell
(1998), Vol. 33, pp. 947-973, Journal of human resources, Madison, Wis., C1-1
"Regression-Discontinuity Design" By Any Other Name Might Be Less Problematic
T Stanley
(1991), Vol. 15, pp. 605-624, Evaluation Review, London, England, C1-1
J Cappelleri, W Trochim, T Stanley, C Reichardt
(1991), Vol. 15, pp. 395-419, Evaluation Review, London, England, C1-1
Let's get serious about Caprice
T Stanley
(1991), Vol. 20, pp. 37-56, Journal of socio-economics, Amsterdam, The Netherlands, C1-1
Opportunity to achieve: identifying mathematically gifted black students
A Robinson, R Bradley, T Stanley
(1990), Vol. 15, pp. 1-12, Contemporary educational psychology, Amsterdam, The Netherlands, C1-1
META‐REGRESSION ANALYSIS: A QUANTITATIVE METHOD OF LITERATURE SURVEYS
T Stanley, S Jarrell
(1989), Vol. 3, pp. 161-170, Journal of Economic Surveys, Chichester, Eng., C1-1
Forecasting from fallible data: correcting prediction bias with Stein‐rule least squares
T Stanley
(1988), Vol. 7, pp. 103-113, Journal of forecasting, Chichester, Eng., C1-1
Stein-rule least squares estimation: a heuristic for fallible data
T Stanley
(1986), Vol. 20, pp. 147-150, Economics letters, Amsterdam, The Netherlands, C1-1
Funded Projects at Deakin
No Funded Projects at Deakin found
Supervisions
No completed student supervisions to report