in the classical data envelopment analysis (dea) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. in recent years, there are few researches on handling missing data. this paper suggests a new interval based approach to apply missing data, which is the modified version of kousmanen (2009) approach. first, the prop...

congenitally missing of maxillary lateral incisors is one of the most common patterns of hypodontia. this paper presents a nine year old boy with congenital missing of lateral incisors. familial history showed that, his mother, aunts, uncle and grandmother have also congenital absence of lateral incisors.

background: hypodontia is the most common dental anomaly and might cause clinical complications. the aim of this study was to assess the prevalence and pattern of congenital missing in the permanent dentition dentition (excluding third molars), among iranian orthodontic patients. materials and methods: in this descriptive cross-sectional study, all approved panoramic radiographs of 3374 orthodo...

background: diagnostic models are frequently used to assess the role of risk factors on disease complications, and therefore to avoid them. missing data is an issue that challenges the model making. the aim of this study was to develop a diagnostic model to predict death in hiv/ aids patients when missing data exist. methods: hiv patients (n=1460) referred to voluntary consoling and testing cen...

in interventional or observational longitudinal studies, the issue of missing values is one of the main concepts that should be investigated. the researcher's main concerns are the impact of missing data on the final results of the study and the appropriate methods that missing values should be handled. regarding the role and the scale of the variable that missing values have been occurred and ...

Background Policy makers need models to be able to detect groups at high risk of HIV infection. Incomplete records and dirty data are frequently seen in national data sets. Presence of missing data challenges the practice of model development. Several studies suggested that performance of imputation methods is acceptable when missing rate is moderate. One of the issues which was of less concern...

background: the aim of the article is demonstrating an application of multiple imputation (mi) for handling missing clinical data in the setting of rheumatologic surveys using data derived from 10291 people participating in the first phase of the community oriented program for control of rheumatic disorders (copcord) in iran . methods: five data subsets were produced from the original data set....