Madde Tepki Modellemesinde Genellenebilirlik İle İki Yüzeyli Desenlerin İncelenmesi

Year 2018, Volume: 9 Issue: 1, 17 - 32, 31.03.2018

Gülden Kaya Uyanık , Selahattin Gelbal

https://doi.org/10.21031/epod.349718

Cited By: 1

Abstract

Bu çalışmada, Madde Tepki Modellemesinde Genellenebilirlik
(MTMG) yaklaşımı iki yüzeyli bx(m:t) deseni ile incelenmiş ve Genellenebilirlik
Kuramından (GK) elde edilen sonuçlar ile karşılaştırılmıştır. Çalışmada simülasyon
verisi kullanılmıştır. Genellenebilirlik Kuramı doğrusal veri seti bx (m:t)
dengelenmiş rastgele deseni için üretilmiştir. Üretilen veriler madde takımı
etkisi, madde takımı uzunluğu ve madde takımı sayısı açısından farklılık
göstermektedir. Veriler toplamda iki evrenden ve her evren dört farklı koşuldan
oluşmaktadır. Araştırmanın sonucu tüm evrenlere ait koşulların varyans
kestirimlerinin MTMG yaklaşımı ve GK ile elde edilen sonuçlar arasında bir fark
olmadığını göstermektedir. Elde edilen bu sonuç MTMG yaklaşımını ortaya atan ve
tek yüzeyli desen üzerinde inceleyen Briggs ve Wilson’ın yapmış oldukları
çalışma ile desteklenmektedir. MTMG yaklaşımı ve GK ile kestirilen değerler
arasında fark yoktur; ancak MTMG yaklaşımında hata varyansı etkileşim varyansından
ayrı olarak gözlenebilir. Çalışmada ayrıca madde takımları güvenirliği farklı
koşullar altında incelenmiştir. Birey-madde takımı etkileşiminin küçük olduğu
durumlarda etkileşimin büyük olduğu durumlara göre daha yüksek güvenirlik elde
edilmiştir. Bunun yanında madde takımı etkisi arttıkça güvenirliğin düştüğü
gözlenmiştir. Ayrıca tüm evrenlere ait koşullar incelendiğinde madde takımları
için madde sayısı artıkça güvenirliğin arttığı gözlenmiştir. 

Keywords

Madde tepki modellemesinde genellenebilirlik, genellenebilirlik kuramı, madde takımı, madde sayısı, güvenirlik

Investigation of Two Facets Design With Generalizability In Item Response Modeling

Abstract

An approach called generalizability in item response
modeling (GIRM) is investigated with two facets sx(i:t) design and results are
compared with results of generalizability theory in this study. In this study
simulated data is used. In Generalizability Theory linear model random facets
balanced bx(m:h) design are used for generating data. Generated data are
differed by factors. These factors are testlet effect, testlet length and
number of testlet. All generated data consist of two different universes and
all universes have four different conditions. According to the results of this
study the estimates of variance components obtained using GIRM approach are
generally quite similar to those obtained using GT approach. Briggs and
Wilson‘s study is supported this result. There is no difference between results
of GIRM and GT but error variance could be separated from residual variance
with GIRM.  This study also examines the
reliability of testlets under different conditions. Testlets are more reliable
when person-item variance is smaller. Furthermore, when testlet effect is
increased,reliability is decreased. When conditions of all universes are
investigated it is concluded that it is effective to have more items to
increase reliability.

Keywords

Generalizability in item response modeling, generalizability theory, testlet, number of item, reliability

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