The DOI matches its Crossref record; 34 of the 36 references it cites were found in a registry or an index.
Parametric Empirical Bayes Inference: Theory and Applications
Abstract
This article reviews the state of multiparameter shrinkage estimators with emphasis on the empirical Bayes viewpoint, particularly in the case of parametric prior distributions. Some successful applications of major importance are considered. Recent results concerning estimates of error and confidence intervals are described and illustrated with data.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The highly parallel nature of gene expression experiments lends itself to a particular class of statistical methods, called parametric empirical Bayes, that borrow information between genes in a dynamic way (14,15).”
From limma powers differential expression analyses for RNA-sequencing and microarray studies (2015) · cites this paper as [15]
Citations
Cites
Cross validatory choice and assessment of statistical predictions
Stone, M. (1974) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1974.tb00994.x · Cited by 10,881
Journal of the Royal Statistical Society.
(1923) · The Economic Journal · doi:10.1093/ej/33.130.269 · Cited by 3,289
The Predictive Sample Reuse Method with Applications
Geisser, S. (1975) · Journal of the American Statistical Association · doi:10.1080/01621459.1975.10479865 · Cited by 2,748
Estimation with Quadratic Loss
James, W., & Stein, C. M. (1992) · Springer series in statistics · doi:10.1007/978-1-4612-0919-5_30 · Cited by 2,319
Bayes Estimates for the Linear Model
Lindley, D. V., & Smith, A. F. M. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00885.x · Cited by 2,025
Estimates of Income for Small Places: An Application of James-Stein Procedures to Census Data
Fay, R. E., & Herriot, R. A. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10482505 · Cited by 1,283
Stein's Estimation Rule and its Competitors—An Empirical Bayes Approach
Efron, B., & Morris, C. (1973) · Journal of the American Statistical Association · doi:10.1080/01621459.1973.10481350 · Cited by 981
Sampling and Bayes' Inference in Scientific Modelling and Robustness
Box, G. E. P. (1980) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2982063 · Cited by 905
Data Analysis Using Stein's Estimator and its Generalizations
Efron, B., & Morris, C. N. (1975) · Journal of the American Statistical Association · doi:10.1080/01621459.1975.10479864 · Cited by 863
An Empirical Bayes Approach to Statistics
Robbins, H. E. (1992) · Springer series in statistics · doi:10.1007/978-1-4612-0919-5_26 · Cited by 858
Research works printed but not linked: 8
- Berger J., 1983, Robustness in Bayesian Statistics
- Efron B., 1975, Advances in Mathematics, 16, 259
- Gini C., 1911, Metron, 15, 133
- Jackson D. A., 1970, Biometrika, 57, 439
- Morris C., 1983, The Annals of Statistics, 11
- Morris, C. and Van Slyke, L. “Empirical Bayes Methods for Pricing Insurance Classes,”. Proceedings of the Business and Economics Statistics Section. pp.579–582. American Statistical Association.
- van der Merwe A. J., 1981, “Confidence Intervals for a Multivariate Normal Mean in the Case of Empirical Bayes Estimation Using Pearson Curves and Normal Approximations,”
- Whitney, A. W. “The Theory of Experience Rating,”. Proceedings of the Casualty Actuarial Society. Vol. IV, pp.274–292.
Cited by
Sorted by citations
Items 501–600 of 1,001
On determination of sample size in hierarchical binomial models
Zou, K. H., & Normand, S. T. (2001) · Statistics in Medicine · doi:10.1002/sim.855 · Cited by 27
“Although methodology for the analyses of multi-centre trials has grown substantially with the advent of inexpensive computing and convenient simulation algorithms that permit basic [1], multi-level [2; 3], empirical [4], hierarchical [5] and fully Bayes analyses [6], as well as stratiLcation methods [7], methodology f…”
MethodPitselis, G. (2013) · Insurance Mathematics and Economics · doi:10.1016/j.insmatheco.2013.02.011 · Cited by 26
Li, Q., Guindani, M., Reich, B. J., Bondell, H. D., & Vannucci, M. (2017) · Statistical Analysis and Data Mining The ASA Data Science Journal · doi:10.1002/sam.11350 · Cited by 26
“…estimators in multiple-stage approaches and somewhat akin to Empirical Bayes methods, therefore relying on implicit assumptions of exchangeability of the observations, which may not be always justified in practice and can introduce bias in the estimation of posterior uncertainties [23,41].”
MethodStatistical Modelling of Citation Exchange Between Statistics Journals
Varin, C., Ca, U., Venezia, F., Profile, S., Cattelan, M., Varin, C., & Firth, D. (2016) · Cited by 26
Modeling Stochastic Variability in Multiband Time-series Data
Hu, Z., & Tak, H. (2020) · The Astronomical Journal · doi:10.3847/1538-3881/abc1e2 · Cited by 26
Inflation targeting: Genuine effects or publication selection bias?
Balima, H. W., Kilama, E. G., & Tapsoba, R. (2020) · European Economic Review · doi:10.1016/j.euroecorev.2020.103520 · Cited by 26
Candel, M. J. J. M., & Winkens, B. (2003) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986028002169 · Cited by 26
“Also the superiority of this particular EBE in terms of the mean squared error (when averaged across at least four subjects) has been shown (Casella, 1985; Morris, 1983).”
BackgroundEMPIRICAL BAYES METHODS: A TOOL FOR EXPLORATORY ANALYSIS
Braun, H. I. (1988) · ETS Research Report Series · doi:10.1002/j.2330-8516.1988.tb00281.x · Cited by 26
“Some discussion of robustness appears in Morris (1983) and the accompanying discussion.”
BackgroundMethodEmpirical Bayes prediction intervals in a normal regression model: higher order asymptotics
Basu, R., Ghosh, J. K., & Mukerjee, R. (2003) · Statistics & Probability Letters · doi:10.1016/s0167-7152(03)00083-x · Cited by 26
A Conversation with Dennis Lindley
Smith, A. F. M. (1995) · Statistical Science · doi:10.1214/ss/1177009940 · Cited by 26
On Truncation of Shrinkage Estimators in Simultaneous Estimation of Normal Means
Dey, D. K., & Berger, J. O. (1983) · Journal of the American Statistical Association · doi:10.1080/01621459.1983.10477033 · Cited by 26
Introduction to Individual Growth Curve Analysis
Francis, D. J., Schatschneider, C. W., & Carlson, C. D. (2000) · Issues in clinical child psychology · doi:10.1007/978-1-4615-4165-3_3 · Cited by 26
Flexible distributions for triple-goal estimates in two-stage hierarchical models
Paddock, S. M., Ridgeway, G. K., Lin, R., & Louis, T. A. (2005) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2005.05.008 · Cited by 26
“Approaches that exploit the twostage nature of clustered data improve estimation when the specified two-stage model holds (Morris 1983), which makes empirical Bayesian or fully Bayesian approaches more attractive than simply deriving the MLE in the standard way (i.e., θ mle k = y k ).”
MethodBayesian input in Stein estimation and a new minimax empirical Bayes estimator
Berger, J. O., & Berliner, L. M. (1984) · Journal of Econometrics · doi:10.1016/0304-4076(84)90039-3 · Cited by 26
On Analytic Empirical Bayes Estimation of Failure Rates
Vaurio, J. K. (1987) · Risk Analysis · doi:10.1111/j.1539-6924.1987.tb00468.x · Cited by 26
Benchmarks for Discrete Choice Models
Kalwani, M. U., Meyer, R. J., & Morrison, D. G. (1994) · Journal of Marketing Research · doi:10.1177/002224379403100106 · Cited by 26
The Returns to College(s): Relative Value-Added and Match Effects in Higher EducationPreprint
Mountjoy, J., & Hickman, B. R. (n.d.) · RePEc: Research Papers in Economics · Cited by 26
IntelligentPooling: practical Thompson sampling for mHealth
Tomkins, S., Liao, P., Klasnja, P., & Murphy, S. A. (2021) · Machine Learning · doi:10.1007/s10994-021-05995-8 · Cited by 29
Estimating Random Effects via Adjustment for Density Maximization
Morris, C. N., & Tang, R. (2011) · Statistical Science · doi:10.1214/10-sts349 · Cited by 25
“This is the density of θ if, independently for i = 1, . . . , k, θi|A∼N(0,A) and A∼Unif[0,∞), as seen from ∫ ∞ 0 e−1/2‖θ‖ 2/A dA Ak/2 ∝ ‖θ‖2−k.(30) This prior with c = 1, that is, A ∼ Unif[0,∞), is strongly suggested in the equal variance case by the fact that the James–Stein shrinkage constant B̂ = k−2 S+ is precisel…”
BackgroundInfluentialBenchmarked empirical Bayes methods in multiplicative area-level models with risk evaluation
Ghosh, M., Kubokawa, T., & Kawakubo, Y. (2015) · Biometrika · doi:10.1093/biomet/asv010 · Cited by 25
“…of τ 2, there are several methods proposed in the literature, which include the iterative method of moments estimator by Fay and Herriot (1979) and Morris (1983), the Prasad-Rao (1990) method of moment estimator, the maximum likelihood (ML) and the restricted maximum likelihood (REML)…”
MethodShrinkage Estimators in Online Experiments
Dimmery, D., Bakshy, E., & Sekhon, J. (2019) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3292500.3330771 · Cited by 25
“Efron says the derivation is from Morris [25] where the variance expression appears as equation (4.1).”
BackgroundInfluentialThomas, D. C., Pitkäniemi, J. M., Langholz, B. M., Tuomilehto‐Wolf, E., Tuomilehto, J., & DiMe Study Group (1995) · Genetic Epidemiology · doi:10.1002/gepi.1370120503 · Cited by 25
9 Bayesian Approaches in Ecological Analysis and Modeling
Reckhow, K. H. (2004) · Princeton University Press eBooks · doi:10.1515/9780691228846-011 · Cited by 25
Adult Literacy Development and Economic Growth
Reder, S. (2010) · PsycEXTRA Dataset · doi:10.1037/e529892011-001 · Cited by 25
“These are model-based empirical Bayes estimates (Morris, 1983) of individual growth curve parameters.”
MethodThe Returns to College(s): Relative Value-Added and Match Effects in Higher Education
Mountjoy, J., & Hickman, B. (2021) · National Bureau of Economic Research · doi:10.3386/w29276 · Cited by 30
Worker Beliefs About Outside Options
Jäger, S., Roth, C., Roussille, N., & Schoefer, B. (2021) · National Bureau of Economic Research · doi:10.3386/w29623 · Cited by 25
Weber, F., Knapp, G., Glass, A. S., Kundt, G., & Ickstadt, K. (2020) · Research Synthesis Methods · doi:10.1002/jrsm.1471 · Cited by 25
Blázquez-Rincón, D., Sánchez‐Meca, J., Botella, J., & Suero, M. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-022-01809-0 · Cited by 23
“Morris CN. Parametric empirical Bayes inference: theory and applications.”
MethodEMPIRICAL BAYES ESTIMATION FOR THE MEANS OF THE SELECTED POPULATIONS
Hwang, J. T. (2016) · Cited by 24
Bootstrap estimation of uncertainty in prediction for generalized linear mixed models
Flores-Agreda, D., & Cantoni, E. (2018) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2018.08.006 · Cited by 24
Applications of Bayesian Statistical Methods in Microarray Data Analysis
Yang, D., Zakharkin, S. O., Page, G. P., Brand, J. P. L., Edwards, J. W., Bartolucci, A. A., & Allison, D. B. (2004) · American Journal of PharmacoGenomics · doi:10.2165/00129785-200404010-00006 · Cited by 24
A Quasi-Empirical Bayes Method for Small Area Estimation
Raghunathan, T. E. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10476431 · Cited by 24
Nonparametric Empirical Bayes Growth Curve Analysis
Altman, N., & Casella, G. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476542 · Cited by 24
Empirical bayes methods in sequential estimation
Martinsek, A. T. (1987) · Sequential Analysis · doi:10.1080/07474948708836120 · Cited by 24
Mortality Effects and Choice Across Private Health Insurance Plans
Abaluck, J., Bravo, M. C., Hull, P., & Starc, A. (2020) · National Bureau of Economic Research · doi:10.3386/w27578 · Cited by 24
“These estimates are given by (recentered) OLS coefficients, and we estimate σ2w, σ2u , and σ2e by a conventional random effects procedure (Morris, 1983).”
MethodPardhan-Ali, A., Berke, O., Wilson, J. B., Edge, V. L., Furgal, C. M., Reid‐Smith, R. J., dos Santos, M. C., & McEwen, S. A. (2012) · International Journal of Health Geographics · doi:10.1186/1476-072x-11-17 · Cited by 24
“Empirical Bayesian estimation is used to stabilize the variance by “borrowing strength” from all other observations via the global estimate which removes part of the random variation and generates smoothed estimates of risk in each community [53,54].”
BackgroundMethodPowell, E. J., McDowell, S., O’Brien, R., & Oksasoglu, J. (2020) · Constitutional Political Economy · doi:10.1007/s10602-019-09298-y · Cited by 27
Cold-Start Promotional Sales Forecasting Through Gradient Boosted-Based Contrastive Explanations
Aguilar-Palacios, C., Muñoz-Romero, S., & Rojo‐Álvarez, J. L. (2020) · IEEE Access · doi:10.1109/access.2020.3012032 · Cited by 25
“To encode the nc categorical variables as numerical we use either the James-Stein encoder [22], or the target additive encoding [23], or the CatBoost approach [24].”
MethodMishra, N., Imes, C., Lafferty, J., & Hoffmann, H. (2018) · ACM SIGPLAN Notices · doi:10.1145/3296957.3173184 · Cited by 23
Applied Demography in the 21st Century
Murdock, S. H., & Swanson, D. A. (2008) · Springer eBooks · doi:10.1007/978-1-4020-8329-7_21 · Cited by 23
Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables
Johnson, M., Lipscomb, S., & Gill, B. (2014) · Journal of Research on Educational Effectiveness · doi:10.1080/19345747.2014.967898 · Cited by 23
“We adjust for measurement error in the teacher VAM estimates through an Empirical Bayes (shrinkage) procedure (Morris 1983).”
MethodJeong, H. (2015) · Biometrics & Biostatistics International Journal · doi:10.15406/bbij.2015.02.00020 · Cited by 23
Human Capital and the Supply of Religion
Engelberg, J., Fisman, R. J., Hartzell, J. C., & Parsons, C. A. (2016) · The Review of Economics and Statistics · doi:10.1162/rest_a_00582 · Cited by 23
Asymptotic analysis of statistical decision rules in econometrics
Hirano, K., & Porter, J. R. (2020) · Handbook of econometrics · doi:10.1016/bs.hoe.2020.09.001 · Cited by 26
Christensen, A. L., Jacobs, E., Maheshwari, K. K., Xing, F., Zhao, X., Simon, S. E., Domino, K. B., Posner, K. L., Stewart, A. F., Sanford, J. A., et al. (2020) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000005287 · Cited by 23
Robust hierarchical Bayes estimation of exchangeable means
Angers, J., & Berger, J. O. (1991) · Canadian Journal of Statistics · doi:10.2307/3315535 · Cited by 23
An Empirical Bayes Approach to Smoothing in Backcalculation of HIV Infection Rates
Liao, J., & Brookmeyer, R. (1995) · Biometrics · doi:10.2307/2532946 · Cited by 23
Comparisons of Alternative Predictors Under the Balanced One-Way Random Model
Peixoto, J. L., & Harville, D. A. (1986) · Journal of the American Statistical Association · doi:10.1080/01621459.1986.10478287 · Cited by 23
An Application of Bayes Methodology to the Analysis of Diary Records from a Water Use Study
James, I. R., & Knuiman, M. W. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478486 · Cited by 23
“The Bayesian estimation method is described in Section 4 and differs from standard empirical Bayes procedures in that separate data are used to estimate the prior distributions [see Morris (1983) and references therein].”
MethodHealthcare Exceptionalism? Performance and Allocation in the U.S. Healthcare Sector
Chandra, A., Finkelstein, A. N., Sacarny, A., & Syverson, C. (2015) · National Bureau of Economic Research · doi:10.3386/w21603 · Cited by 25
Differences in Differentiation: Rising Variety and Markups in Retail Food StoresPreprint
Brand, J. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3712513 · Cited by 23
“To alleviate some of this concern, I employ an empirical Bayes shrinkage procedure, following Morris (1983) and as implemented in Chandra et al. (2016)29.”
MethodComment: Fuzzy and Bayesian p-Values and u-Values
Gelman, A. (2005) · Statistical Science · doi:10.1214/088342305000000368 · Cited by 22
How Not to Fool Ourselves About Heterogeneity of Treatment Effects
von Hippel, P. T., & Schuetze, B. A. (2025) · Advances in Methods and Practices in Psychological Science · doi:10.1177/25152459241304347 · Cited by 29
“These shrunken estimates are variously known as empirical Bayes estimates (Morris, 1983) with a normal prior, James and Stein (1961) estimates, or best linear unbiased predictions in random-effects models (G. K. Robinson, 1991).”
Arrested Friendships? Justice Involvement and Interpersonal Exclusion among Rural Youth
Jacobsen, W. C., Ragan, D. T., Yang, M. H., Nadel, E. L., & Feinberg, M. E. (2021) · Journal of Research in Crime and Delinquency · doi:10.1177/00224278211048942 · Cited by 22
“…in responses in later waves, we follow Osgood, Baals, and Ramirez (2018; see also Baals 2018) by relying on a cross-wave measure of the frequency of free or reduced-price lunch (using our binary indicator), based on empirical Bayes shrinkage estimates (Morris 1983; Raudenbush and Bryk 2002).”
MethodMolina, L. K. R., López, J. Á. P., & Lucena, M. S. C. (2022) · Management Review Quarterly · doi:10.1007/s11301-022-00267-8 · Cited by 22
“In particular, this study uses the restricted maximum likelihood technique (Raudenbush 2009), a method of random effects, that has its origins in Morris (1983).”
Liu, D., Sun, T., Liu, D., Fu, Q., Zhang, L., Li, X., Li, M., Li, T., & Cui, S. (2022) · Journal of Hydrology · doi:10.1016/j.jhydrol.2022.128134 · Cited by 22
Small area estimation of non-monetary poverty with geospatial data
Masaki, T., Newhouse, D., Silwal, A. R., Bedada, A., & Engstrom, R. N. (2022) · Statistical Journal of the IAOS · doi:10.3233/sji-210902 · Cited by 24
The real exchange rate and economic growth: a meta-analysis
Ridhwan, M. M., Ismail, A., & Nijkamp, P. J. (2023) · Journal of Economic Studies · doi:10.1108/jes-10-2022-0548 · Cited by 25
Nonsubjective Bayes testing—an overview
Ghosh, J. K., & Samanta, T. (2002) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(01)00222-1 · Cited by 22
Zwick, R. (1993) · Journal of Educational Statistics · doi:10.3102/10769986018001091 · Cited by 22
“Within-school means on GMATV, GMATQ, UGPA, and FYA in the current study tended to be higher than those found in the MBA validity studies described in Wightman and Leary (1985), and within-school standard deviations on FYA tended to be smaller.”
ResultCasetti, E. (1991) · Environment and Planning A Economy and Space · doi:10.1068/a231045 · Cited by 22
“Some phases of estimation and inference for cases under (c) through (e) are addressed in the literature on random coefficients (Cooley and Prescott, 1976; Fomby et al, 1984; Swamy, 1971); on varying parameters (Judge et al, 1985; Maddala, 1977; Raj and Ullah, 1981); on Bayesian linear models (Lindley and Smith, 1972;…”
BackgroundOn the Problem of Finding the Largest Normal Mean under Heteroscedasticity
Gupta, S. S., & Miescke, K. J. (1986) · doi:10.21236/ada172023 · Cited by 22
“i(x,^ - 1] n <p{{xi - 9i)/pf)dT{d), (16)”
BackgroundInfluentialBid Takers or Market Makers? The Effect of Auctioneers on Auction Outcomes
Lacetera, N., Larsen, B., Pope, D. G., & Sydnor, J. (2013) · National Bureau of Economic Research · doi:10.3386/w19731 · Cited by 21
“There is a remarkable amount of variation across auctioneers with 13 See, among others, Chandra, Finkelstein, Sacarny, and Syverson (2013); Jacob and Lefgren (2005); and Morris (1983).”
The Impact of Organizational Boundaries on Healthcare Coordination and Utilization
Agha, L., Ericson, K. M. M., & Zhao, X. (2020) · National Bureau of Economic Research · doi:10.3386/w28179 · Cited by 22
“To account for statistical noise in PCP organizational concentration, we apply a conventional empirical Bayes correction (Morris 1983).”
MethodXu, Y., Li, K., & Liu, Y. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.111280 · Cited by 21
Can Value-Added Measures of Teacher Education Performance Be Trusted?
Guarino, C. M., Reckase, D., & Wooldridge, J. M. (2012) · Cited by 20
The Influence of Sellers on Contract Choice: Evidence from Flood Insurance
Collier, B., & Ragin, M. A. (2019) · Journal of Risk & Insurance · doi:10.1111/jori.12280 · Cited by 21
Comparative phylogeographic inference with genome‐wide data from aggregated population pairs
Xue, A. T., & Hickerson, M. J. (2020) · Evolution · doi:10.1111/evo.13945 · Cited by 22
“Hierarchical co-demographic modeling for sister taxon pairs is available in the software programs msBayes (Hickerson et al. 2007, 2014; Huang et al. 2011) and dpp-msbayes (Oaks 2014), which use an approximate Bayesian computation (ABC) inferential framework.”
MethodBaek, E., & Ferron, J. M. (2020) · Methodology · doi:10.5964/meth.2817 · Cited by 21
“A noninformative prior distribution is considered as one of the reasonable choices of objective prior distribution because noninformative distributions make the data speak for themselves so that posterior inferences are unaffected by external information (Berger, 2006; Gelman, 2002; Gelman et al., 2004; Goldstein, 200…”
BackgroundA random coefficient model for chlorophyll-nutrient relationships in lakes
Reckhow, K. H. (1993) · Ecological Modelling · doi:10.1016/0304-3800(93)90071-y · Cited by 21
What Is the Best Way to Estimate Hospital Quality Outcomes? A Simulation Approach
Ryan, A. M., Burgess, J. F., Strawderman, R. L., & Dimick, J. B. (2012) · Health Services Research · doi:10.1111/j.1475-6773.2012.01382.x · Cited by 21
Bayesian Hypothesis Testing of Two Normal Samples using Bootstrap Prior Technique
Olaniran, O. R., & Yahya, W. B. (2017) · Journal of Modern Applied Statistical Methods · doi:10.22237/jmasm/1509496440 · Cited by 21
Predicting Accident Frequencies for Drivers Classified by Two Factors
Tomberlin, T. J. (1988) · Journal of the American Statistical Association · doi:10.1080/01621459.1988.10478600 · Cited by 21
Exploring Baseball Hitting Data: What about those Breakdown Statistics?
Albert, J. (1994) · Journal of the American Statistical Association · doi:10.1080/01621459.1994.10476844 · Cited by 21
Modeling of rates over a hierarchical health administrative structure
Dean, C. B., & MacNab, Y. C. (2001) · Canadian Journal of Statistics · doi:10.2307/3316037 · Cited by 21
How Does Value Added Compare to Student Growth Percentiles?
Walsh, E., & Isenberg, E. (2015) · Statistics and Public Policy · doi:10.1080/2330443x.2015.1034390 · Cited by 20
“We used an empirical Bayes procedure as outlined in Morris (1983) to account for imprecise estimates.”
MethodHarmonization with Flow-Based Causal Inference
Wang, R., Chaudhari, P., & Davatzikos, C. A. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87199-4_17 · Cited by 20
Latent network models to account for noisy, multiply reported social network data
Bacco, C. D., Contisciani, M., Cardoso‐Silva, J., Safdari, H., Borges, G. L., Baptista, D., Sweet, T. M., Young, J.-G., Koster, J., Ross, C. T., et al. (2023) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1093/jrsssa/qnac004 · Cited by 23
“This is in line with Empirical Bayes approaches (Casella, 1985; Morris, 1983; Robbins, 1955) that estimate prior distributions from the data.”
Improving power for rare‐variant tests by integrating external controls
Lee, S., Kim, S., & Fuchsberger, C. (2017) · Genetic Epidemiology · doi:10.1002/gepi.22057 · Cited by 21
“Note that the consistent estimator of 𝜈 from the marginal distribution of ̂𝜃 is ̂𝜈 + = max(0 , ̂𝜃 2 − ̂𝜎 2 𝜃 ) , where ̂𝜎 2 𝜃 is an estimate of 𝜎 2 𝜃 (Morris, 1983).”
Influence and Information in Team Decisions: Evidence from Medical Residency
Chan, D. C. (2021) · American Economic Journal Economic Policy · doi:10.1257/pol.20180501 · Cited by 20
Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems
Mougan, C., Masip, D., Nin, J., & Pujol, O. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-85529-1_14 · Cited by 20
“This set of encoding techniques includes ordinal encoding, James-Stein Encoder [16,28,8], and several state of the art target encodings with different regularization values such as catboost [18], classical target encoder [15,27] and M-estimate target encoding [4] and generalized linear mixed models encoder [9,27].”
MethodA Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints
Mishra, N., Zhang, H., Lafferty, J., & Hoffmann, H. (2015) · ACM SIGARCH Computer Architecture News · doi:10.1145/2786763.2694373 · Cited by 20
An Empirical Bayes Approach to Analyzing Recurring Animal Surveys
Johnson, D. H. (1989) · Ecology · doi:10.2307/1941361 · Cited by 20
Empirical Bayes Estimation of the Reliability of Nuclear-Power-Plant Emergency Diesel Generators
Martz, H. F., Kvam, P. H., & Abramson, L. R. (1996) · Technometrics · doi:10.1080/00401706.1996.10484412 · Cited by 20
A Hierarchical Bayes Approach to Small Area Estimation with Auxiliary Information
Ghosh, M., & Lahiri, P. (1992) · Lecture notes in statistics · doi:10.1007/978-1-4612-2944-5_6 · Cited by 20
On The Problem of Finding The Largest Normal Mean Under Heteroscedasticity
Gupta, S. S., & Miescke, K. J. (1988) · Springer eBooks · doi:10.1007/978-1-4612-3818-8_4 · Cited by 20
Producing Health: Measuring Value Added of Nursing Homes
Liran Einav, B., Finkelstein, A. N., & Mahoney, N. (2022) · National Bureau of Economic Research · doi:10.3386/w30228 · Cited by 20
“To perform shrinkage we follow the procedure described in Morris (1983).”
Qiu, J., & Hwang, J. T. G. (2007) · Biometrics · doi:10.1111/j.1541-0420.2007.00770.x · Cited by 19
“See Morris (1983) and He (1992), which deal with θ i ’s, not θ ( i ) ’s. Morris’s confidence intervals are narrower than the standard intervals only on the average of all the N intervals whereas He’s approach results in a narrower interval for every θ i .”
BackgroundAssociation Between Race and Case Fatality Rate in Hospitalizations for Sepsis
Sandoval, E., & Chang, D. (2015) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-015-0181-0 · Cited by 20
Jiang, J., & Nguyen, T. D. (2021) · Springer series in statistics · doi:10.1007/978-1-0716-1282-8_1 · Cited by 20
Stambaugh, R. F. (2011) · Quarterly Journal of Finance · doi:10.1142/s2010139211000158 · Cited by 19
Admissible estimation, Dirichlet principles and recurrence of birth-death chains on ℤ p +
Johnstone, I. M. (1986) · Probability Theory and Related Fields · doi:10.1007/bf00332311 · Cited by 19
Confidence sets and the stein effect
Casella, G., & Hwang, J. T. (1986) · Communication in Statistics- Theory and Methods · doi:10.1080/03610928608829234 · Cited by 19
Bayesian nonparametric survival analysis for grouped data
Johnson, W. O., & Christensen, R. (1986) · Canadian Journal of Statistics · doi:10.2307/3315188 · Cited by 19
Bayesian Regression and the Expansion Method
Casetti, E. (1992) · Geographical Analysis · doi:10.1111/j.1538-4632.1992.tb00252.x · Cited by 19
Estimation of a Stationary Markov Chain
Billard, L., & Meshkani, M. R. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476514 · Cited by 19
Determining the Accuracy of Bayesian Empirical Bayes Estimates in the Familiar Exponential Families
Morris, C. N. (1988) · Springer eBooks · doi:10.1007/978-1-4613-8768-8_26 · Cited by 19
Shrinkage and Orthogonal Decomposition
Blaker, H. (1999) · Scandinavian Journal of Statistics · doi:10.1111/1467-9469.00133 · Cited by 19
Ranking Firms Using Revealed Preference
Sorkin, I. (2017) · National Bureau of Economic Research · doi:10.3386/w23938 · Cited by 19
Weisburst, E. (2022) · The Journal of Human Resources · doi:10.3368/jhr.0720-11019r2 · Cited by 18
Metadata
- Authors
- Morris, C. N.
- Affiliations
- The University of Texas at Austin (US)
- Corresponding author
- Morris, Carl N.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1983-03
- Volume
- 78
- Issue
- 381
- Pages
- 47-55
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W1983607152
- Cited by
- 1,448
- References
- 36
- Citations by year
- 2026: 32 · 2025: 30 · 2024: 52 · 2023: 42 · 2022: 40 · 2021: 51 · 2020: 62 · 2019: 44 · 2018: 49 · 2017: 43 · 2016: 54 · 2015: 63 · 2014: 66 · 2013: 49 · 2012: 48
- FWCI
- 24.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Keywords
- parametric empirical Bayes, confidence intervals, shrinkage estimation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
