Open Source Web Based Software for Random Assignment/Allocation Methods in Data Processing

Küçük Resim Yok

Tarih

2019

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Ieee

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

In this study, it is aimed to develop a user-friendly open-source web-based software which enables the assignment of the subjects included in the scientific research to the groups with equal probability. An open source R package, Shiny, is used to develop the recommended web tool. In the developed software, one of the required equilibrium methods; random allocation rule, truncated binomial design, maximal procedure design, complete randomization methods; complete randomization design, blocking methods; permuted block randomization with random block constellation, the Hadamard randomization, adaptive methods; the big stick design, Efron's biased coin design, Wei's urn design, generalized biased coin design, Chen's biased coin design are included. A random allocation rule, one of the random assignment methods, is applied to a hypothetical data set where the sample size is 140 and the number of groups are two. As a result, in the first group, a random assignment was made in such a way that the number of samples are 70 and the number of samples in the second group are 70. According to the hypothetical data set findings, the developed easily assigns the subjects to the study groups by using random assignment methods. Therefore, it is stated that it easily solved a significant bias problem in scientific studies. In the following stages of the study, the scope of the software can be expanded with the addition of techniques comparing the results of random assignment methods.

Açıklama

International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEY

Anahtar Kelimeler

Data processing, Hypothetical data, Random assignment/allocation methods, Web based software

Kaynak

2019 International Conference on Artificial Intelligence and Data Processing (Idap 2019)

WoS Q Değeri

N/A

Scopus Q Değeri

N/A

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