원문정보
초록
영어
Concrete compressive strength is one of the most important factors leading to building construction, in the civil engineering context. While evaluating such data, quantitative analysis required. As it is known that, concrete as a non-homogeneous material, consists of separate phases. The more complicated the concrete, the higher is the compressive strength. But if missing value exists in the microstructure of concrete, then it may provide some unusual effect on the compressive strength of concrete. Thus it is required to deal with the analysis of missing values. In this study traditional and modern estimation techniques of missing values are performed and the effect of these methods on correlation matrix is observed along with their comparison. The result shows that, modern techniques provide efficient estimates compared to traditional method. .The analysis described here were undertaken in the SPSS 13.0 packages.
목차
1. Introduction
2. Missing Values
2.1 Missing Completely At Random (MCAR)
2.2 Missing At Random (MAR)
2.3 Non Ignorable (NI) Missing Values
3. Traditional Approaches of Missing Values
3.1 Deletion Techniques
3.2 Imputation Techniques
3.3 Modern Alternatives For Working With Missing Values
4. Results of Empirical Application
5. Conclusion
References