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Comparison of E-Trust and Trust Concepts in Online and Offline Dimensions

). Customers for life: how to turn that one-time buyer into a lifetime customer, Crown Business; Revised Edition. Trif, S. M. (2013). The influence of overall satisfaction and trust on customer loyalty. Management & marketing challenges for the knowledge society, 8(1), 109-128. Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2010). An assessment of customers’ e-service quality perception, satisfaction and intention. International Journal of Information Management, 30(6), 481-492. Yi, J

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The Modified Lunn-Mcneil Model in the Assessment of Intensity of Exiting from the Unemployment

risks when failure times are discrete , Lifetime Data Analysis, 2(2), pp. 195-209, DOI: 10.1007/BF00128575. Crowder M., 1997, A test for independence of competing risks with discrete failure times , Lifetime Data Analysis, 3(3), pp. 215-223, DOI: 10.1023/A:1009696830515. Gooley T.A., Leisenring W., Crowley J., Storer B.E., 1999, Estimation of failure probabilities in the presence of competing risks: New representations of old estimators , Statistics in Medicine, 18(6), pp. 695-706, DOI:10.1002/(SICI)10970258(19990330)18:6<695::AID-SIM60>3.0.CO;2-O

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Competing Risk Models of Default in the Presence of Early Repayments

comparing the cumulative incidence function in the presence of a competing risk, The Annals of Statistics, 16, pp. 1141-1154. Haller B., Schmidt G., Ulm K., 2013, Applying competing risks regression models: an overview , Lifetime Data Analysis, 19, pp. 33-58. Højsgaard S., Halekoh U., Yan J., 2016, geepack: Generalized Estimating Equation Package , URL , R package version 1.2_1. Klein J.P., Andersen P.K., 2005, Regression modelling of competing risks data based on pseudo-values of the cumulative incidence

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