Hussain, S.; Mohamed, M. A.; Holder, R.; Almasri, A.; Shukur, G. Performance evaluation based on the robust Mahalanobis distance and multilevel modeling using two new strategies. (English) Zbl 1153.62388 Commun. Stat., Simulation Comput. 37, No. 10, 1966-1980 (2008). Summary: We propose a general framework for performance evaluation of organizations and individuals over time using routinely collected performance variables or indicators. Such variables or indicators are often correlated over time, with missing observations, and often come from heavy-tailed distributions shaped by outliers. Two new double robust and model-free strategies are used for evaluation (ranking) of sampling units. Strategy 1 can handle missing data using residual maximum likelihood (RML) at stage two, while strategy two handles missing data at stage one. Strategy 2 has the advantage that overcomes the problem of multicollinearity. Strategy one requires independent indicators for the construction of the distances, where strategy two does not. Two different domain examples are used to illustrate the application of the two strategies. Example one considers performance monitoring of gynecologists and example two considers the performance of industrial firms. Cited in 1 Document MSC: 62P99 Applications of statistics 62H99 Multivariate analysis 90B99 Operations research and management science 65C60 Computational problems in statistics (MSC2010) 65F35 Numerical computation of matrix norms, conditioning, scaling Keywords:Mahalanobis distance; multilevel estimation; performance; ranking indicators; robust statistics; MANOVA Software:ROBETH PDFBibTeX XMLCite \textit{S. Hussain} et al., Commun. Stat., Simulation Comput. 37, No. 10, 1966--1980 (2008; Zbl 1153.62388) Full Text: DOI HAL References: [1] DOI: 10.1108/01437720510597676 [2] Gelman A., Bayesian Data Analysis (1995) [3] DOI: 10.2307/2983325 · Zbl 04533967 [4] DOI: 10.1136/bmj.38377.675440.8F [5] DOI: 10.1111/1467-985X.00094 · Zbl 04546495 [6] DOI: 10.1023/A:1008981510081 [7] DOI: 10.1198/10618600152628059 · Zbl 04567023 [8] DOI: 10.1214/aos/1032526972 · Zbl 0862.62049 [9] DOI: 10.2307/2291724 · Zbl 0882.62049 [10] Rousseeuw P. J., Mathematical Statistics and Applications B pp 283– (1985) [11] DOI: 10.2307/1270566 [12] DOI: 10.1002/0471725382 [13] DOI: 10.1002/9780470316856 [14] Seltzer M., Multilevel Modeling Methodological Advances, Issues, and Application (2003) This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.