An Algorithm for the Selection of Proper Group Intervals for Histograms Representing Clinical Laboratory Data

Although numerous statistical methods are available, proper definitive technics to deal with the determination of normal values or ranges in clinical chemistry are unresolved and ill-defined. Initially, the ability to the analyst to define a mathematical function that can be used to best fit the ran...

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Published inAmerican journal of clinical pathology Vol. 64; no. 3; pp. 327 - 334
Main Authors Martin, H. F., Gudzinowicz, B. J., Driscoll, J. L.
Format Journal Article
LanguageEnglish
Published England 01.09.1975
Subjects
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ISSN0002-9173
1943-7722
DOI10.1093/ajcp/64.3.327

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Abstract Although numerous statistical methods are available, proper definitive technics to deal with the determination of normal values or ranges in clinical chemistry are unresolved and ill-defined. Initially, the ability to the analyst to define a mathematical function that can be used to best fit the random distribution of generated laboratory values still depends on proper grouping of the data. Herein is proposed a method for grouping data, in order to select the proper class interval to be used. Arbitrariness is removed and maximum information about the population being tested can be achieved. The concepts of "regrouping" and "sign reversal" are utilized, and the validity of this technic for constructing the "best" frequency histogram is verified by a general computer algorithm.
AbstractList Although numerous statistical methods are available, proper definitive technics to deal with the determination of normal values or ranges in clinical chemistry are unresolved and ill-defined. Initially, the ability to the analyst to define a mathematical function that can be used to best fit the random distribution of generated laboratory values still depends on proper grouping of the data. Herein is proposed a method for grouping data, in order to select the proper class interval to be used. Arbitrariness is removed and maximum information about the population being tested can be achieved. The concepts of "regrouping" and "sign reversal" are utilized, and the validity of this technic for constructing the "best" frequency histogram is verified by a general computer algorithm.
Although numerous statistical methods are available, proper definitive technics to deal with the determination of normal values or ranges in clinical chemistry are unresolved and ill-defined. Initially, the ability to the analyst to define a mathematical function that can be used to best fit the random distribution of generated laboratory values still depends on proper grouping of the data. Herein is proposed a method for grouping data, in order to select the proper class interval to be used. Arbitrariness is removed and maximum information about the population being tested can be achieved. The concepts of "regrouping" and "sign reversal" are utilized, and the validity of this technic for constructing the "best" frequency histogram is verified by a general computer algorithm.Although numerous statistical methods are available, proper definitive technics to deal with the determination of normal values or ranges in clinical chemistry are unresolved and ill-defined. Initially, the ability to the analyst to define a mathematical function that can be used to best fit the random distribution of generated laboratory values still depends on proper grouping of the data. Herein is proposed a method for grouping data, in order to select the proper class interval to be used. Arbitrariness is removed and maximum information about the population being tested can be achieved. The concepts of "regrouping" and "sign reversal" are utilized, and the validity of this technic for constructing the "best" frequency histogram is verified by a general computer algorithm.
Author Martin, H. F.
Driscoll, J. L.
Gudzinowicz, B. J.
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StartPage 327
SubjectTerms Clinical Laboratory Techniques - methods
Clinical Laboratory Techniques - standards
Computers
Humans
Mathematics
Time Factors
Title An Algorithm for the Selection of Proper Group Intervals for Histograms Representing Clinical Laboratory Data
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