Open Journal of Statistics , , 3, Received April 23, ; revised May 23, ; accepted May 30, This is an open access article distributed under the Creative Commons Attribution Li-.
Longitudinal studies are those in which the same variable is repeatedly measured at diffe rent times. These studies are. Since the presence of missing values may have an important im-. We compared its efficiency in eleven imputation methods. All these methods were tested on three markedly dif-. For each of them, we generated. Our results show that Copy Mean. The ef-. The Last Occurrence Carried Forward method is strongly. Longitudinal studies are those in which the same variable. They are more.
Indeed, it is frequent that subjects miss a clinical visit or. The missing data. Missing at Random MAR when the missingness prob-.
When the main analysis involves statistical modeling. However, selection models. This paper focuses on situations where the main anal-. These kinds of analyses. Twisk [8] and Engels [3] compared several imputation. Twisk proposed a clas-. Regarding the evaluation of performance, Engels pro-. These indices are mainly based on. The present article aims at comparing different impu-. Section 2 provides the general framework and the meth-.
This section re-. Section 3 presents the design of. Let us consider a set S of n subjects. For each subject, an. For subject i , the sequence. For a specific time l , vector. When il is missing, the value obtained by. In their founding documents, Rubin and Little distin-. They consid-. Then R denotes the. Boolean matrix of the location of a missing value and. Y the missing part of TRUE. The classification of Little and Rubin is then based.
