Bu çalışmada objektif kriter ağırlıklandırma yöntemlerinden Entropy, Criteria Importance Through Intercriteria Correlation (CRITIC), Eşit ağırlık, MEthod based on the Removal Effects of (MEREC), Standart sapma ve Integrated Data Oriented Weighting System (IDDWS) yaklaşımları kullanılarak, bahsi geçen altı farklı tekniğin Simple Additive (SAW) Çok Kriterli Karar Verme (ÇKKV) yöntem sonuçları üze...

In text categorization, the class agnostic (unsupervised) tf× idf term weighting scheme has seen widespread usage. Recently proposed supervised term weighting methods including tf×rf and tf× δidf make use of term class distribution to improve the classification accuracy. However, they only account for the presence of terms in classes, ignoring the absence of key categorical terms, which may giv...

We review weighting adjustment methods for panel attrition and suggest approaches for incorporating design variables, such as strata, clusters, and baseline sample weights. Design information can typically be included in attrition analysis using multilevel models or decision tree methods such as the chi-square automatic interaction detection algorithm. We use simulation to show that these weigh...

OBJECTIVE To provide a tutorial for using propensity score methods with complex survey data. DATA SOURCES Simulated data and the 2008 Medical Expenditure Panel Survey. STUDY DESIGN Using simulation, we compared the following methods for estimating the treatment effect: a naïve estimate (ignoring both survey weights and propensity scores), survey weighting, propensity score methods (nearest ...

This study analyzes the impact of a welfare-to-work program on maternal depression mediated by employment experience in the context of a randomized experiment. We develop parametric and non-parametric weighting procedures as alternative strategies for removing selection bias in estimating the controlled direct effect of the policy and that of the mediator. Through ratio-of-mediator-probability ...

To improve the class separability of Fisher linear discriminant analysis (FDA) for large category problems, we investigate the weighted Fisher criterion (WFC) by integrating weighting functions for dimensionality reduction. The objective of WFC is to maximize the sum of weighted distances of all class pairs. By setting larger weights for the most confusable classes, WFC can improve the class se...