Significance of Goodness-of-fit test
The Goodness-of-fit test is a statistical assessment designed to evaluate how well a model describes and fits observed data. It helps determine the accuracy of statistical models, particularly noted in methods like the Hosmer-Lemeshow test. This test is crucial in various fields, including drug release studies, where understanding the fit of the model is essential for reliable data interpretation and predictions. Overall, the Goodness-of-fit test plays an important role in statistical analysis and modeling.
Synonyms: Fit test, Chi-square test, Kolmogorov-smirnov test, Shapiro-wilk test
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The concept of Goodness-of-fit test in scientific sources
The Goodness-of-fit test is a statistical analysis used in drug release studies to evaluate the accuracy of a model in representing observed data, ensuring that predictions align closely with the actual outcomes.
From: The Malaysian Journal of Medical Sciences
(1) Statistical methods to evaluate how well a model fits the observed data, specifically noted as the Hosmer-Lemeshow test in the study.[1] (2) A statistical test used to determine how well a statistical model fits the data it is supposed to represent.[2]