Concurrent Generation of Binary, Ordinal, and Count Data with Specified Marginal and Associational Quantities in Pharmaceutical Sciences

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dc.contributor.authorDemirtas, Hakan
dc.contributor.authorCosar, Kübra
dc.contributor.authorAltuntas, Mutlu
dc.date.accessioned2025-03-23T18:55:11Z
dc.date.available2025-03-23T18:55:11Z
dc.date.issued2022
dc.departmentSinop Üniversitesi
dc.description.abstractThis manuscript is concerned with establishing a unified framework for concurrently generating data sets that include three major kinds of variables (i.e., binary, ordinal, and count) when the marginal distributions and a feasible association structure are specified for simulation purposes. The simulation paradigm has been commonly utilized in pharmaceutical practice. A central aspect of every simulation study is the quantification of the model components and parameters that jointly define a scientific process. When this quantification goes beyond the deterministic tools, researchers often resort to random number generation (RNG) in finding simulation-based solutions to address the stochastic nature of the problem. Although many RNG algorithms have appeared in the literature, a major limitation is that most of them were not devised to simultaneously accommodate all variable types mentioned above. Thus, these algorithms provide only an incomplete solution, as real data sets include variables of different kinds. This work represents an important augmentation of the existing methods as it is a systematic attempt and comprehensive investigation for mixed data generation. We provide an algorithm that is designed for generating data of mixed marginals; illustrate its operational, logistical, and computational details; and present ideas on how it can be extended to span more sophisticated distributional settings in terms of a broader range of marginal features and associational quantities.
dc.identifier.endpage32
dc.identifier.issn2980-0463
dc.identifier.issue1
dc.identifier.startpageJul
dc.identifier.urihttps://hdl.handle.net/11486/2431
dc.identifier.volume1
dc.language.isoen
dc.publisherInönü Üniversitesi
dc.relation.ispartofAnatolian Journal of Pharmaceutical Sciences
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20250323
dc.subjectBiserial correlation
dc.subjectphi coefficient
dc.subjectsimulation
dc.subjecttetrachoric correlation
dc.subjectrandom number generation
dc.subjectmixed data
dc.titleConcurrent Generation of Binary, Ordinal, and Count Data with Specified Marginal and Associational Quantities in Pharmaceutical Sciences
dc.typeArticle

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