Dealing with the Phenomenon of Quasi-complete Separation and a Goodness of Fit Test in Logistic Regression Models in the Case of Long Data Sets
| Autor: | K. A. Lindsay, V. G. Vassiliadis, A. G. Rigas, Jay R. Rosenberg, Ioannis Spyroglou |
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| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Statistics and Probability Separation (statistics) Test validity Logistic regression 01 natural sciences Biochemistry Genetics and Molecular Biology (miscellaneous) Plot (graphics) 010104 statistics & probability 03 medical and health sciences 030104 developmental biology Goodness of fit Statistics Binary data 0101 mathematics Q–Q plot Mathematics Quantile |
| Zdroj: | Statistics in Biosciences. 11:567-596 |
| ISSN: | 1867-1772 1867-1764 |
| Popis: | The phenomenon of quasi-complete separation that appears in the identification of the neuromuscular system called muscle spindle by a logistic regression model is considered. The system responds when it is affected by a number of stimuli. Both the response and the stimuli are very long binary sequences of events. In the logistic model, three functions are of special interest: the threshold, the recovery and the summation functions. The maximum likelihood estimates are obtained efficiently and very fast by using the penalized likelihood function. A validity test for the fitted model based on the randomized quantile residuals is proposed. The validity test is transformed to a goodness of fit test and the use of Q–Q plot is also discussed. |
| Databáze: | OpenAIRE |
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