Biomaterial Database

Tolerance interval testing for assessing accuracy and precision simultaneously. 2021

Chieh Chiang, and Chin-Fu Hsiao

Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.

Tolerance intervals have been recommended for simultaneously validating both the accuracy and precision of an analytical procedure. However, statistical inferences for the corresponding hypothesis testing are scarce. The aim of this study is to establish a whole statistical inference for tolerance interval testing, including sample size determination, power analysis, and calculation of p-value. More specifically, the proposed method considers the bounds of a tolerance interval as random variables so that a bivariate distribution can be derived. Simulations confirm the theoretical properties of the method. Furthermore, an example is used to illustrate the proposed method.

UI	MeSH Term	Description	Entries
D012107	Research Design	A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly.	Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D003955	Diagnostic Tests, Routine	Diagnostic procedures, such as laboratory tests and x-rays, routinely performed on all individuals or specified categories of individuals in a specified situation, e.g., patients being admitted to the hospital. These include routine tests administered to neonates.	Admission Tests, Routine,Hospital Admission Tests,Physical Examination, Preadmission,Routine Diagnostic Tests,Admission Tests, Hospital,Diagnostic Test, Routine,Diagnostic Tests,Examination, Preadmission Physical,Preadmission Physical Examination,Routine Diagnostic Test,Test, Routine Diagnostic,Tests, Diagnostic,Tests, Hospital Admission,Tests, Routine Diagnostic,Admission Test, Hospital,Admission Test, Routine,Diagnostic Test,Examinations, Preadmission Physical,Hospital Admission Test,Physical Examinations, Preadmission,Preadmission Physical Examinations,Routine Admission Test,Routine Admission Tests,Test, Diagnostic,Test, Hospital Admission,Test, Routine Admission,Tests, Routine Admission
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000068598	Data Accuracy	A measure of scientific precision, exactness, or correctness of quantitative or qualitative values, relative to the actual or true measurements.	Data Quality,Accuracies, Data,Accuracy, Data,Data Accuracies,Data Qualities,Qualities, Data,Quality, Data
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016001	Confidence Intervals	A range of values for a variable of interest, e.g., a rate, constructed so that this range has a specified probability of including the true value of the variable.	Confidence Interval,Interval, Confidence,Intervals, Confidence
D018401	Sample Size	The number of units (persons, animals, patients, specified circumstances, etc.) in a population to be studied. The sample size should be big enough to have a high likelihood of detecting a true difference between two groups. (From Wassertheil-Smoller, Biostatistics and Epidemiology, 1990, p95)	Sample Sizes,Size, Sample,Sizes, Sample