EĞİTİM ARAŞTIRMALARINDA UYGUN MALİYETLİ SEÇKİSİZ DENEYLER TASARLAMAK İÇİN PRATİK BİR KILAVUZ: PİLOT ÇALIŞMALARDAN BÜYÜK ÖLÇEKLİ MÜDAHALELERE

Year 2022, Issue: 51, 129 - 147, 09.08.2022

Metin Bulus

https://doi.org/10.30794/pausbed.1078211

Abstract

Bu çalışma, pilot çalışmalardan büyük ölçekli müdahalelere kadar uygun maliyetli seçkisiz deneylerin nasıl tasarlanacağını göstermeyi amaçlamaktadır. Seçkisiz deneylerin optimal tasarımı için iki olası senaryo vardır; ilk olarak, toplam maliyeti sabit bir miktarda veya altında tutarken güç oranını maksimize etmek isteyebiliriz ve ikinci olarak, güç oranını nominal güç oranında (genellikle 0,80) veya üzerinde tutarken toplam maliyeti minimize etmek isteyebiliriz. Bu iki senaryo göz önüne alındığında, optimal tasarım stratejisi, maliyet açısından eşdeğer olası tüm tasarımlar arasından en yüksek güç oranına sahip tasarımı seçmemizi veya istatistiksel güç açısından eşdeğer olası tüm tasarımlar arasından en az maliyete sahip tasarımı seçmemizi sağlar. Katılımcılar/katılımcı grupları hakkında daha fazla bilgi toplanarak veya katılımcılar homojen alt kümelere bloke edilerek maliyet düşürülebilir. Maliyeti düşük tasarımları belirlemek için Bulus (2021) tarafından sağlanan excel sayfası ve cosa R paketi (Bulus & Dong, 2021a, 2021b) kullanıldı. Akademisyenler, kaynak kısıtlamaları olduğunda, örneklem büyüklüklerini bu şekilde gerekçelendirebilirler.

Keywords

optimal tasarım, seçkisiz deneyler, seçkisiz küme deneyleri, bloklanmış seçkisiz küme deneyleri, seçkisiz öntest-sontest kontrol grubu olan tasarımlar, uygun maliyetli deneyler, optimal tasarım, seçkisiz deneyler, seçkisiz küme deneyleri, bloklanmış seçkisiz küme deneyleri, seçkisiz öntest-sontest kontrol grubu olan tasarımlar, uygun maliyetli deneyler

A PRACTICAL GUIDE TO DESIGNING COST-EFFICIENT RANDOMIZED EXPERIMENTS IN EDUCATION RESEARCH: FROM PILOT STUDIES TO INTERVENTIONS AT SCALE

Abstract

This study aims to illustrate how to design cost-efficient randomized experiments from pilot studies to interventions at scale. There are two possible scenarios for optimal design of randomized experiments; first, we may want to maximize the power rate while keeping the total cost at or under a fixed amount, and second, we may want to minimize the total cost while keeping the power rate at or above a nominal power rate (often 0.80). Considering these two scenarios, the optimal design strategy ensures that we choose the design with the highest power rate among all possible cost-equivalent designs, or that we choose the design with the minimum cost among all possible power-equivalent designs. Further cost-efficiency can be achieved via collecting more information on the subjects/group of subjects, or via blocking subjects into homogenous subsets. We used the excel sheet provided by Bulus (2021) and cosa R package (Bulus & Dong, 2021a, 2021b) to determine cost-efficient designs. Scholars can justify their sample size in this fashion when they have resource constraints. This will indicate that they opted for the design with the highest power rate among all possible cost-equivalent designs (same cost but different power rates), or opted for the design with the minimum cost among all possible power-equivalent designs (same power rate but different costs).

Keywords

optimal design, randomized experiments, randomized trials, cluster-randomized trial, blocked cluster-randomized trial, randomized pretest-posttest control-group design, cost-efficient experiments, optimal design, randomized experiments, randomized trials, cluster-randomized trial, blocked cluster-randomized trial, randomized pretest-posttest control-group design, cost-efficient experiments

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