Nicel Araştırmalarda Açıklayıcı Faktör Analizi (EFA) ve Pratik Hususlar

Year 2024, Volume: 13 Issue: 2, 947 - 965, 29.06.2024

Lütfi Sürücü , İbrahim Yıkılmaz , Ahmet Maşlakçı

https://doi.org/10.37989/gumussagbil.1183271

Cited By: 3

Abstract

Açıklayıcı faktör analizi (EFA), nicel araştırmalarda sıklıkla kullanılan çok değişkenli istatistiksel bir yöntem olup, sosyal bilimler, sağlık bilimleri ve ekonomi gibi birçok alanda kullanılmaya başlamıştır. EFA yardımıyla önemsiz olabilecek çok fazla öğeyi dikkate almak yerine, yapıyı açıklayan daha az sayıdaki öğeye odaklanır ve bu öğeleri anlamlı kategorilere (faktör) yerleştirerek çalışmalarını yürütürler. Bununla birlikte altmış yılı aşkın bir süredir birçok araştırmacı EFA’nın ne zaman ve nasıl kullanılacağına dair birbirinden farklı tavsiyelerde bulunmaktadır. Yapılan tartışma konularının başında örneklem büyüklüğü, madde sayısı, madde çıkarma yöntemleri, faktör tutma kriterleri, döndürme yöntemleri ve uygulanan prosedürlerin genel uygulanabilirliği konuları yer almaktadır. Literatürde yaşanan bu tartışmalar ve görüşlerin bolluğu, araştırmacıların EFA’da hangi prosedürleri izleyeceğine karar vermesini zorlaştırmaktadır. Bu nedenle EFA’nın kullanımındaki genel prosedürlere (örneklem sayısı, döndürme yöntemleri vb.) ait farklı bilgilerin bir araya getirilmesi araştırmacılar için faydalı olacaktır. Bu çalışmanın amacı; EFA uygulanırken hangi prosedürlerinin izleneceği konusunda okuyuculara genel bir bakış açısı sunmak ve EFA sürecindeki metodolojik kararlarla ilgili en son gelişmeler hakkında okuyuculara pratik bilgiler paylaşmaktır. Çalışmanın en güncel bilgileri toplu bir şekilde sunması yönü ile EFA kullanımında net karar yollarının geliştirilmesinde okuyuculara önemli bir kılavuz olacağı değerlendirilmektedir.

Keywords

Explanatory factor analysis (EFA), Rotation methods, Sample size, Quantitative Research, SPSS

Supporting Institution

Yoktur

Project Number

Yoktur

Thanks

Yoktur

Exploratory Factor Analysis (EFA) in Quantitative Researches and Practical Considerations

Abstract

Explanatory factor analysis (EFA) is a multivariate statistical method frequently used in quantitative research and has begun to be used in many fields such as social sciences, health sciences and economics. With EFA, researchers focus on fewer items that explain the structure, instead of considering too many items that may be unimportant and carry out their studies by placing these items into meaningful categories (factors). However, for over sixty years, many researchers have made different recommendations about when and how to use EFA. Differences in these recommendations confuse the use of EFA. The main topics of discussion are sample size, number of items, item extraction methods, factor retention criteria, rotation methods and general applicability of the applied procedures. The abundance of these discussions and opinions in the literature makes it difficult for researchers to decide which procedures to follow in EFA. For this reason, it would be beneficial for researchers to gather different information about the general procedures (sample number, rotation methods, etc.) in the use of EFA. This paper aims to provide readers with an overview of what procedures to follow when implementing EFA and share practical information about the latest developments in methodological decisions in the EFA process. It is considered that the study will be an important guide for the researchers in the development of clear decision paths in the use of EFA, with the aspect of presenting the most up-to-date information collectively.

Keywords

Explanatory factor analysis (EFA), Rotation methods, Sample size, SPSS, Quantitative Research

Project Number

Yoktur

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