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Journal of the American Statistical Association Volume 78, 1983 - Issue 381
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Theory & Method

A Predictive View of the Detection and Characterization of Influential Observations in Regression Analysis

Wesley Johnson Division of Statistics, University of California, Davis, CA, 95616, USA
&
Seymour Geisser School of Statistics, University of Minnesota, Minneapolis, MN, 55455, USA
Pages 137-144 | Received 01 Apr 1981, Published online: 12 Mar 2012

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M. T. Pratola, E. I. George & R. E. McCulloch. (2024) Influential Observations in Bayesian Regression Tree Models. Journal of Computational and Graphical Statistics 33:1, pages 47-63.
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Xing-De Duan & Nian-Sheng Tang. (2016) Bayesian estimation and influence diagnostics of generalized partially linear mixed-effects models for longitudinal data. Statistics 50:3, pages 525-539.
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J. M. Fernández-Ponce, F. Palacios-Rodríguez & M. R. Rodríguez-Griñolo. (2013) Bayesian influence diagnostics in radiocarbon dating. Journal of Applied Statistics 40:1, pages 28-39.
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Hongtu Zhu, JosephG. Ibrahim, Hyunsoon Cho & Niansheng Tang. (2012) Bayesian Case Influence Measures for Statistical Models With Missing Data. Journal of Computational and Graphical Statistics 21:1, pages 253-271.
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Nurul Haque Mollah & S. K. Bhattacharjee. (2007) Predictive Influence of Variables in a Multivariate Distribution in Presence of Perfect Multicollinearity. Communications in Statistics - Theory and Methods 37:1, pages 121-136.
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D. J. Spiegelhalter & E. C. Marshall. (2006) Strategies for inference robustness in focused modelling. Journal of Applied Statistics 33:2, pages 217-232.
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Bruce E. Barrett. (2003) Understanding Influence in Multivariate Regression. Communications in Statistics - Theory and Methods 32:3, pages 667-680.
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Younshik Chung, Dipak K. Dey & Sangjeen Lee. (2001) APPLYING THE SAVAGE-DICKEY DENSITY RATIO TO DEFAULT BAYES FACTORS, WITH AN ILLUSTRATION TO OUTLIER DETECTION IN RANDOM EFFECTS MODELS. Communications in Statistics - Theory and Methods 30:12, pages 2563-2582.
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JosephG. Ibrahim. (1997) On Properties of Predictive Priors in Linear Models. The American Statistician 51:4, pages 333-337.
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Cinzia Carota, Giovanni Parmigiani & NicholasG. Polson. (1996) Diagnostic Measures for Model Criticism. Journal of the American Statistical Association 91:434, pages 753-762.
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S. K. Bhattachaijee & I. R. Dunsmore. (1995) The predictive influence of variables in a Normal Regression Model. Journal of Information and Optimization Sciences 16:2, pages 327-334.
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EhsanS. Soofi. (1994) Capturing the Intangible Concept of Information. Journal of the American Statistical Association 89:428, pages 1243-1254.
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JosephG. Ibrahim & PurushottamW. Laud. (1994) A Predictive Approach to the Analysis of Designed Experiments. Journal of the American Statistical Association 89:425, pages 309-319.
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S. K. Bhattacharjee. (1993) Tests of Equality of Parameters of Two Normal Populations in Bayesian Viewpoint. Journal of Information and Optimization Sciences 14:2, pages 161-166.
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S. Velilla. (1992) Influential observations in transformations: A bayesian approach. Communications in Statistics - Theory and Methods 21:11, pages 3197-3209.
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Michael Lavine. (1992) Local predictive influence in bayesian linear models with conjugate priors. Communications in Statistics - Simulation and Computation 21:1, pages 269-283.
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BradleyP. Carlin & BradleyP. Carlin. (1991) An Expected Utility Approach to Influence Diagnostics. Journal of the American Statistical Association 86:416, pages 1013-1021.
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William Thomas & R. Dennis Cook. (1990) Assessing Influence on Predictions From Generalized Linear Models. Technometrics 32:1, pages 59-65.
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. (1989) Book Reviews. Journal of the American Statistical Association 84:406, pages 611-635.
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RobertE. McCulloch. (1989) Local Model Influence. Journal of the American Statistical Association 84:406, pages 473-478.
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Daniel Peña & Irwin Guttman. (1989) Optimal collapsing of mixture distributions in robust recursive estimation. Communications in Statistics - Theory and Methods 18:3, pages 817-833.
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J. Brian Gray. (1988) A Classification of influence measures. Journal of Statistical Computation and Simulation 30:3, pages 159-171.
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Ross S. Sparks. (1988) A distribution free method of detecting outliers in regression. Communications in Statistics - Theory and Methods 17:3, pages 705-727.
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R. Dennis Cook, Daniel Peña & Sanford Weisberg. (1988) The likelihood displacement:a unifying principle for influence measures. Communications in Statistics - Theory and Methods 17:3, pages 623-640.
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Wesley Johnson. (1987) The Detection of Influential Observations for Allocation, Separation, and the Determination of Probabilities in a Bayesian Framework. Journal of Business & Economic Statistics 5:3, pages 369-381.
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John D. Morris & Carl J. Huberty. (1987) Selecting a Two-Group Classification Weighting Algorithm. Multivariate Behavioral Research 22:2, pages 211-232.
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T. M. F. Smith. (1987) Influential observations in survey sampling. Journal of Applied Statistics 14:2, pages 143-152.
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Seymour Geisser. (1987) Influential observations, diagnostics and discovery tests. Journal of Applied Statistics 14:2, pages 133-142.
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Wesley. Johnson, Jessica. Utts & Larry. M. Pearson. (1986) A monte carlo comparison of bayesian estimators and trimmed means. Journal of Statistical Computation and Simulation 25:3-4, pages 167-192.
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J.Brian Gray. (1986) A simple graphic for assessing influence in regression. Journal of Statistical Computation and Simulation 24:2, pages 121-134.
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MartinS. Levy & S.K. Perng. (1986) An Optimal Prediction Function for the Normal Linear Model. Journal of the American Statistical Association 81:393, pages 196-198.
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James C. Spall. (1985) An implicit function based procedure for analyzing maximum likelihood estimates from nonidentically distributed data. Communications in Statistics - Theory and Methods 14:7, pages 1719-1730.
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RobertF. Ling. (1984) Residuals and Influence in Regression. Technometrics 26:4, pages 413-415.
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J. Brian Gray & RobertF. Ling. (1984) K-Clustering as a Detection Tool for Influential Subsets in Regression. Technometrics 26:4, pages 305-318.
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D.G. Nel, D.J. De Waal & D.G. Marx. (1984) A predictive approach to the detection of additional information in a multivariate regression model. Communications in Statistics - Theory and Methods 13:17, pages 2119-2132.
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Martin S. Levy & S.K. Perng. (1984) A maximum likelihood prediction function for the linear model with consistency results. Communications in Statistics - Theory and Methods 13:10, pages 1257-1273.
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Sanford Weisberg. (1983) Discussion. Technometrics 25:3, pages 240-244.
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