Ranking USRDS provider specific SMRs from 1998–2001

Benjamini, Y., Hochberg, Y.: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. C Stat. Methodol. 57, 289–300 (1995)

Carlin, B.P., Louis, T.A.: Bayesian Methods for Data Analysis, 3rd edn. Chapman and Hall/CRC Press, Boca Raton FL (2008)

Christiansen, C., Morris, C.: Improving the statistical approach to health care provider profiling. Ann. Intern. Med. 127, 764–768 (1997)

Conlon, E.M., Louis, T.A.: Addressing multiple goals in evaluating region-specific risk using Bayesian methods. In: Lawson, A., Biggeri, A., Böhning, D., Lesaffre, E., Viel, J.-F., Bertollini, R. (eds.) Disease Mapping and Risk Assessment for Public Health, chap. 3, pp. 31–47. Wiley (1999)

Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm (C/R: P 22–37). J. R. Stat. Soc. Ser. C Stat. Methodol. 39, 1–22 (1977)

Diggle, P.J., Thomson, M.C., Christensen, O.F., Rowlingson, B., Obsomer, V., Gardon, J., Wanji, S., Takougang, I., Enyong, P., Kamgno, J., Remme, J.H., Boussinesq, M., Molyneux, D.H.: Spatial modelling and the prediction of Loa loa risk: decision making under uncertainty. Ann. Trop. Med. Parasitol. 101(6), 499–509 (2007)

Dominici, F., Parmigiani, G., Wolpert, R.L., Hasselblad, V.: Meta-analysis of migraine headache treatments: combining information from heterogeneous designs. J. Am. Stat. Assoc. 94, 16–28 (1999)

Efron, B., Tibshirani, R.: Empirical Bayes methods and false discovery rates for microarrays. Genet. Epidemiol. 23, 70–86 (2002)

ESRD: 1999 Annual Report: ESRD Clinical Performance Measures Project. Technical Report. Health Care Financing Administration (2000)

Gelman, A., Price, P.: All maps of parameter estimates are misleading. Stat. Med. 18, 3221–3234 (1999)

Gelman, A., Sturtz, S., Ligges, U., Gorjanc, G., and Kerman, J.: The R2WinBUGS package. http://cran.r-project.org/doc/packages/R2WinBUGS.pdf (2006)

Goldstein, H., Spiegelhalter, D. League tables and their limitations: statistical issues in comparisons of institutional performance (with discussion). J. R. Stat. Soc. Ser. A 159, 385–443 (1996)

Grigg, O.A., Farewell, V.T., Spiegelhalter, D.J.: Use of risk-adjusted CUSUM and RSPRT charts for monitoring in medical contexts. Stat. Methods Med. Res. 12(2), 147–170 (2003)

Lacson, E., Teng, M., Lazarus, J., Lew, N., Lowrie, E., Owen, W.: Limitations of the facility-specific standardized mortality ratio for profiling health care quality in dialysis. Am. J. Kidney Dis. 37, 267–275 (2001)

Laird, N.M.: Nonparametric maximum likelihood estimation of a mixing distribution. J. Am. Stat. Assoc. 78, 805–811 (1978)

Landrum, M., Bronskill, S., Normand, S.-L.: Analytic methods for constructing cross-sectional profiles of health care providers. Health. Serv. Outcomes Res. Method. 1, 23–48 (2000)

Lin, R., Louis, T.A., Paddock, S.M., Ridgeway, G.: Loss function based ranking in two-stages, hierarchical models. Bayesian Anal. 1(4), 915–946 (2006)

Liu, J., Louis, T. A., Pan, W., Ma, J., Collins, A.: Methods for estimating and interpreting provider-specific, standardized mortality ratios. Health. Serv. Outcomes Res. Method. 4, 135–149 (2004)

Lockwood, J., Louis, T.A., McCaffrey, D.F.: Uncertainty in rank estimation: implications for value-added modeling accountability systems. J. Edu. Behav. Stat. 27(3), 255–270 (2002)

Louis, T.A., Shen, W.: Innovations in Bayes and empirical Bayes methods: estimating parameters, populations and ranks. Stat. Med. 18, 2493–2505 (1999)

Louis, T.A., Zeger, S.L.: Effective communication of standard errors and confidence intervals. Biostatistics. http://dx.doi.org/10.1093/biostatistics/kxn014 (2008)

McClellan, M., Staiger, D.: The Quality of Health Care Providers. Technical Report 7327. National Bureau of Economic Research, Working Paper (1999)

Normand, S.-L.T., Glickman, M.E., Gatsonis, C.A.: Statistical methods for profiling providers of medical care: issues and applications. J. Am. Stat. Assoc. 92, 803–814 (1997)

Normand, S.-L.T., Shahian, D.M.: Statistical and clinical aspects of hospital outcomes profiling. Stat. Sci. 22, 206–226 (2007)

Ohlssen, D.I., Sharples, L.D., Spiegelhalter, D.J.: A hierarchical modelling framework for identifying unusual performance in health care providers. J. R. Stat. Soc. Ser. A Stat. Soc. 170(4), 865–890 (2007)

Paddock, S., Ridgeway, G., Lin, R., Louis, T.A.: Flexible distributions for triple-goal estimates in two-stage hierarchical models. Comput. Stat. Data Anal. 50/11, 3243–3262 (2006)

Pepe, M.S., Feng, Z., Huang, Y., Longton, G., Prentice, R., Thompson, I.M., Zheng, Y.: Integrating the predictiveness of a marker with its performance as a classifier. Am. J. Epidemiol. 167(3), 362–368 (2008). http://dx.doi.org/10.1093/aje/kwm305

Plummer, M., Best, N., Cowles, K., Vines, K.: The CODA Package. http://cran.r-project.org/doc/packages/coda.pdf (2006)

Shen, W., Louis, T.A.: Triple-goal estimates in two-stage, hierarchical models. J. R. Stat. Soc. Ser. B 60, 455–471 (1998)

Shen, W., Louis, T.A.: Triple-goal estimates for disease mapping. Stat. Med. 19, 2295–2308 (2000)

Silverman, B.W.: Density Estimation for Statistics and Data Analysis. Chapman & Hall Ltd (1986)

Spiegelhalter, D., Thomas, A., Best, N., Gilks, W.: BUGS: Bayesian Inference Using Gibbs Sampling, Version 0.60. Technical Report. Medical Research Council Biostatistics Unit, Institute of Public Health, Cambridge University (1999)

Storey, J.D.: A direct approach to false discovery rates. J. R. Stat. Soc. Ser. B Methodol. 64(3):479–498 (2002)

Storey, J.D.: The positive false discovery rate: a Bayesian Interpretation and the q-value. Ann. Stat. 31(6), 2013–2035 (2003)

USRDS. 2005 Annual Data Report: Atlas of end-stage renal disease in the United States. Technical report, Health Care Financing Administration (2005)

Zaslavsky, A.M.: Statistical issues in reporting quality data: small samples and casemix variation. Int. J. Qual. Health Care 13(6), 481–488 (2001)

Zhang, M., Strawderman, R.L., Cowen, M.E., Wells, M.T.: Bayesian inference for a two-part hierarchical model: an application to profiling providers in managed health care. J. Am. Stat. Assoc. 101(475), 934–945 (2006)