SavedAdd your journal

Journals / Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi / 2020 / Cilt: 11 - Sayı: 4

Drawing a Sample with Desired Properties from Population in RPackage “drawsample”

R’da “drawsample” Paketi ile Evrenden İstenilen Özelliklere Sahip Örneklem Çekme

Kübra ATALAY KABASAKAL
Tuba GÜNDÜZ
Pages
405–429
Publication Date
2022-10-12
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It is thought that using the drawn samples obtained from real data with package drawsample will provide an alternative to simulation studies as well as a complement for these studies.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study is to develop an R package called drawsample, which will be used to draw samples with the desired properties from a real data set.
📊
Key Findings & Data:Different applications of the package drawsample are illustrated using real data from the “Science and Technology(Score_1)” and “Social Studies(Score_2)” subtests of 6th Grade Public Boarding and Scholarship Examinations (PBSE).
💡
Conclusion & Impact:It is thought that using the drawn samples obtained from real data with package drawsample will provide an alternative to simulation studies as well as a complement for these studies.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The aim of this study is to develop an R package called drawsample, which will be used to draw samples with the desired properties from a real data set. In accordance with the aim of the study, a sample with the desired properties can be drawn by purposive sampling with determining several conditions, such as deviation from normality (skewness and kurtosis) and sample size. Different applications of the package drawsample are illustrated using real data from the “Science and Technology(Score_1)” and “Social Studies(Score_2)” subtests of 6th Grade Public Boarding and Scholarship Examinations (PBSE). As the importance given to research with real data has increased in recent years, a good approach would be to draw a sample of the population. With this package, it is expected that researchers will draw samples as close as possible to the desired properties from the population or a large sample. It is thought that using the drawn samples obtained from real data with package drawsample will provide an alternative to simulation studies as well as a complement for these studies.

🔖

Cite This Article

KABASAKAL, K. A., GÜNDÜZ, T. (2022). Drawing a Sample with Desired Properties from Population in RPackage “drawsample”. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, Cilt: 11 - Sayı: 4, 405–429. https://ajindex.com/articles/497194

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (6)

  1. Abdel-fattah, A.-F. A. (1994, April). Comparing BILOG and LOGIST estimates for normal, truncated normal and beta ability distributions. Paper presented at the Annual Meeting of the American Educational Research Association, New Orleans, LA. American Educational Research Association. (2020). Journal of Educational and Behavioral Statistics. Retrieved from https://journals.sagepub.com/description/jeb
  2. Bahry L. M. (2012). Polytomous item response theory parameter recovery: An investigation of non-normal distributions and small sample size (Unpublished Master’s disertation). University of Alberta, Edmonton, Canada. Bıkmaz Bilgen, Ö., & Doğan, N. (2017). Çok kategorili parametrik ve parametrik olmayan madde tepki kuramı modellerinin karşılaştırılması [Comparison of Polytomous Parametric and Nonparametric Item Response Theory Models]. Journal of Measurement and Evaluation in Education and Psychology, 8(4), 354-372. DOI: 10.21031/epod.346650 Blanca, M. J., Arnau, J., López-Montiel, D., Bono, R., & Bendayan, R. (2013). Skewness and kurtosis in real data samples. Methodology,9(2), 78–84. DOI: 10.1027/1614-2241/a000057 Blanca, M., Alarcón, R., Arnau, J., Bono, R., & Bendayan, R. (2017). Non-normal data: Is ANOVA still a valid option?. Psicothema, 29(4), 552-557. DOI: 10.7334/psicothema2016.383 Blest, D. C. (2003). A new measure of kurtosis adjusted for skewness. Australian & New Zealand Journal of Statistics, 45(2), 175-179.
  3. Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York, NY: Guilford Press.
  4. Büyüköztürk, Ş., Çokluk, Ö., & Köklü, N. (2014). Sosyal Bilimler için istatistik. Ankara:
  5. Pegem Akademi. Çelikten, S., & Çakan, M. (2019). Bayesian ve nonbayesian kestirim yöntemlerine dayali olarak siniflama indekslerinin TIMSS 2015 matematik testi üzerinde incelenmesi. [Investigation of classification indices on TIMSS 2015 mathematic-subtest through Bayesian and nonbayesian estimation methods]. Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik Eğitimi Dergisi, 13(1), 105-124.
  6. Courville, T. G. (2004). An empirical comparison of item response theory and classical test theory item/person statistics (Doctoral dissertation, Texas A&M University). Custer, M., Omar, M. H., & Pomplun, M. (2006). Vertical scaling with the Rasch model utilizing default and tight convergence settings with WINSTEPS and BILOG-MG. Applied Measurement in Education, 19(2), 133- 149. DOI: 10.1207/s15324818ame1902_4 D'agostino, R. B., Belanger, A., & D'Agostino Jr, R. B.