Unbiased Statistical Comparison of Creep and Shrinkage Prediction Models

Abstract

This paper addresses the problem of selecting the most realistic creep and shrinkage prediction model, important for designing durable and safe concrete structures. Statistical methods of standard and several nonstandard types and a very large experimental database have recently been used to compare and rank the existing prediction models, but conflicting results have been obtained by various investigators. This paper attempts to overcome this confusion. It introduces data weighting required to eliminate the bias due to improper data sampling in the database, and then examines Bazant and Baweja's Model B3, the ACI model, the CEB model, and two of Gardner's models. The statistics of prediction errors are based strictly on the method of least squares, which is the standard and the only statistically correct method, dictated by the maximum likelihood criterion and the central limit theorem of the theory of probability, as well as the requirement of noncorrelation of errors. Several nonstandard statistical methods that have recently been invented to evaluate creep and shrinkage models are also examined and their deficiencies are pointed out. The ranking of the models that ensues from the least-square regression statistics is shown to be quite different from the rankings obtained by the nonstandard statistics.