Cevapsızlık Durumunda Sıralı Küme Örneklemesi ve Medyan Sıralı Küme Örneklemesi Altında İki Yardımcı Değişkene Dayalı Regresyon Tahmincisi

Year 2025, Issue: ERKEN GÖRÜNÜM, 1 - 1

Ayşenur Akın Vargeloğlu , Yaprak Arzu Özdemir

https://doi.org/10.17134/khosbd.1758912

Abstract

Cevapsızlık durumu, uygulamalı araştırmalarda sıkça karşılaşılan başlıca sorunlardan biridir ve yığın parametrelerinin güvenilir biçimde tahmin edilmesini önemli ölçüde olumsuz etkiler. Bu çalışmada, cevapsızlık durumunda, Sıralı Küme Örnekleme ve Medyan Sıralı Küme Örnekleme yöntemleri altında, iki yardımcı değişkenden yararlanan regresyon tahmin edicileri önerilmiştir. Önerilen tahmin edicilerin etkinliğini değerlendirmek amacıyla kapsamlı bir simülasyon çalışması gerçekleştirilmiştir. Ayrıca, bu tahmin edicilerin uygulanabilirliği gerçek bir veri seti üzerinde gösterilmiştir. Değerlendirme sonuçlarına göre, önerilen tahmin ediciler, klasik regresyon ve oran tahmin edicilerine kıyasla daha yüksek etkinlik göstermiştir.

Keywords

Cevapsızlık , Sıralı Küme Örneklemesi , Regresyon tahmin Edicisi , Medyan Sıralı Küme Örneklemesi

Regression Estimator Based on Two Auxiliary Variables Under Ranked Set Sampling and Median Ranked Set Sampling in the Presence of Non-Response

Abstract

Non-response is one of the major issues frequently encountered in applied research, and it significantly impairs the reliable estimation of population parameters. In this study, regression estimators utilizing information from two auxiliary variables are proposed under Ranked Set Sampling and Median Ranked Set Sampling methods in the presence of non-response. A comprehensive simulation study was conducted to evaluate the efficiency of the proposed estimators. In addition, the applicability of these estimators was demonstrated through a real data application. Based on the evaluation results, the proposed estimators demonstrated higher efficiency than the conventional regression and ratio estimators.

Keywords

Non-response , Ranked Set Sampling , Regression Estimator , Median Ranked Set Sampling

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