Açıklayıcı Grafik Analizi: EGAnet R paketiyle Bir Uygulama

Abstract

Amaç: Boyut sayısının belirlenmesinde her tekniğin kendine göre sınırlılıkları mevcuttur. Bu durum doğru tahminler sağlayabilecek yeni faktör belirleme yöntemlerine ihtiyaç duyulmasına neden olmuştur. Bu araştırmanın amacı faktör belirleme yöntemlerine alternatif bir yaklaşım olan açıklayıcı grafik analiz yöntemi ve bu yöntemin analizleri için kullanılan R programlama dilindeki EGAnet paketi tanıtmaktır. Yöntem: Makale, pakette yer alan ölçek geliştirme çalışmalarında kullanılan fonksiyonların göstermesi amaçlamıştır. Bu amaçla, verinin analiz için hazırlanması, geleneksel ve bostraping açıklayıcı grafik analiz ile boyut belirleme, madde ve boyutlara ilişkin istatistiklerin elde edilmesi, yapısal tutarlılık, doğrulayıcı faktör analizi ve ölçme değişmezliği gibi uygulamaların nasıl kullanılabileceği gösterilmiştir. EGAnet paketinin işlevselliğini göstermek için gerçek veri seti üzerinden analizler yapılmıştır. Bunun için Çevrimiçi Oyun Oynama Motivasyon Ölçeği’nden elde edilen veriler ile açıklamalı R kodları gösterilmiştir. Sonuç: Bu araştırma sonucunda, geleneksel ve bostraping açıklayıcı grafik analiz sonuçlarıyla doğrulayıcı faktör analizi sonuçlarının aynı olduğu elde edilmiştir. Ayrıca cinsiyete göre yapılan ölçme değişmezliği sonucunda kısmi metrik değişmezlik sağlanmıştır. Özgünlük: Bu çalışmanın ölçek geliştirme sürecinde ölçeğin bütünsel olarak incelenmesi ve boyut belirleme konularında araştırmacılara yol göstereceği düşünülmektedir.

Keywords

• Boyut belirleme
• Keşifsel grafik analizi
• EGAnet
• ağ analizi.

Exploratory Graphic Analysis: An Application with the EGAnet R Package

Abstract

Purpose: Each technique has its own limitations in determining the number of dimensions. This situation has led to the need for new factor determination methods that can provide accurate predictions. The aim of this research is to introduce the explanatory graphical analysis method, which is an alternative approach to factor determination methods, and the EGAnet package in the R programming language used for the analysis of this method. Method: The article aims to show the functions used in the scale development studies in the package. For this purpose, it has been shown how applications such as preparation of data for analysis, dimension determination with traditional and bostraping explanatory graphic analysis, obtaining statistics regarding items and dimensions, structural consistency, confirmatory factor analysis and measurement invariance can be used. To demonstrate the functionality of the EGAnet package, analyzes are performed on the real data set. For this purpose, R codes are shown using data obtained from the Online Game Playing Motivation Scale. Conclusion: As a result of this research, it is found that the results of traditional and bostraping explanatory graphic analysis and confirmatory factor analysis are same. In addition, partial metric invariance is achieved as a result of measurement invariance based on gender. Originality: It is thought that this study will guide researchers in holistic examination of the scale and dimension determination during the scale development process.

Keywords

• Exploratory graph analysis
• EGAnet
• network analysis
• factor numbers.

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