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Robert Grant has a list. I’ll just give the ones with more than 10,000 Google Scholar cites:
Cox (1972) Regression and life tables: 35,512 citations.
Dempster, Laird, Rubin (1977) Maximum likelihood from incomplete data via the EM algorithm: 34,988
Bland & Altman (1986) Statistical methods for assessing agreement between two methods of clinical measurement: 27,181
Geman & Geman (1984) Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images: 15,106
We can find some more via searching Google scholar for familiar names and topics; thus:
Metropolis et al. (1953) Equation of state calculations by fast computing machines: 26,000
Benjamini and Hochberg (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing: 21,000
White (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity: 18,000
Heckman (1977) Sample selection bias as a specification error: 17,000
Dickey and Fuller (1979) Distribution of the estimators for autoregressive time series with a unit root: 14,000
Cortes and Vapnik (1995) Support-vector networks: 13,000
Akaike (1973) Information theory and an extension of the maximum likelihood principle: 13,000
Liang and Zeger (1986) Longitudinal data analysis using generalized linear models: 11,000
Breiman (2001) Random forests: 11,000
Breiman (1996) Bagging predictors: 11,000
Newey and West (1986) A simple, positive semi-definite, heteroskedasticity and autocorrelationconsistent covariance matrix: 11,000
Rosenbaum and Rubin (2004) The central role of the propensity score in observational studies for causal effects: 10,000
Granger (1969) Investigating causal relations by econometric models and cross-spectral methods: 10,000
Hausman (1978) Specification tests in econometrics: 10,000
And, the two winners, I’m sorry to say:
Baron and Kenny (1986) The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations: 42,000
Zadeh (1965) Fuzzy sets: 45,000
Ugh.
But I’m guessing there are some biggies I’m missing. I say this because Grant’s original list included one paper, by Bland and Altman, with over 27,000 cites, that I’d never heard of!
P.S. I agree with Grant that using Google Scholar favors newer papers. For example, Cooley and Tukey (1965), “An algorithm for the machine calculation of complex Fourier series,” does not make the list, amazingly enough, with only 9300 cites. And the hugely influential book by Snedecor and Cochran has very few cites, I guess cos nobody cites it anymore. And, of course, the most influential researchers such as Laplace, Gauss, Fisher, Neyman, Pearson, etc., don’t make the cut. If Pearson got a cite for every chi-squared test, Neyman for every rejection region, Fisher for every maximum-likelihood estimate, etc., their citations would run into the mid to high zillions each.
P.P.S. I wrote this post a few months ago so all the citations have gone up. For example, the fuzzy sets paper is now listed at 49,000, and Zadeh has a second paper, “Outline of a new approach to the analysis of complex systems and decision processes,” with 16,000 cites. He puts us all to shame. On the upside, Efron’s 1979 paper, “Bootstrap methods: another look at the jackknife,” has just pulled itself over the 10,000 cites mark. That’s good. Also, I just checked and Tibshirani’s paper on lasso is at 9873, so in the not too distant future it will make the list too.
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