Diagnostic estimation of OSAS using binary mixture logistic regression

Binary (Binomial) Logistic Regression is a statistical model that can be used for classification. Concerning the targeted outcome, if the variance of observations is higher than the variance of expectations, because of overdispersion the success rate of the method in classification goes down. This overdispersion is thought as arising from the unobserved heterogen samples in the data set. In Composite models, the overdispersion is minimized by clustering the data into homogeneous subsets and performing a subset based process. In this study a composite binary logistic regression was used for estimating the sleep apnea. Through this model, snoring signals were classified and with a 98.16% success rate the apnea was diagnosed.

[1]  Kathryn Roeder,et al.  Overdispersion Diagnostics for Generalized Linear Models , 1995 .

[2]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[3]  Henrik Madsen,et al.  Introduction to Generalized Linear Models , 2012 .

[4]  G. Bonney,et al.  Logistic regression for dependent binary observations. , 1987, Biometrics.

[5]  Derong Liu,et al.  A Neural Network Method for Detection of Obstructive Sleep Apnea and Narcolepsy Based on Pupil Size and EEG , 2008, IEEE Transactions on Neural Networks.

[6]  Biao Zhang.  A chi-squared goodness-of-fit test for logistic regression models based on case-control data , 1999 .

[7]  Jean-Michel Poggi,et al.  Wavelet Toolbox User s Guide , 1996 .

[8]  Martin L. Puterman,et al.  Analysis of Patent Data—A Mixed-Poisson-Regression-Model Approach , 1998 .

[9]  M. Puterman,et al.  Mixed Poisson regression models with covariate dependent rates. , 1996, Biometrics.

[10]  Necmettin Sezgin,et al.  Diagnostic Estimation of SAS From Snore Sounds Using Logistic Regression , 2013 .

[11]  Gary G. Koch,et al.  Categorical Data Analysis Using The SAS1 System , 1995 .

[12]  Irene Lena Hudson,et al.  Finite Mixture, Zero-inflated Poisson and Hurdle models with application to SIDS , 2003, Comput. Stat. Data Anal..

[13]  Martin L. Puterman,et al.  Mixed logistic regression models , 1998 .

[14]  David R. Cox,et al.  Some remarks on overdispersion , 1983 .

[15]  A.A. Morsy,et al.  Sleep Apnea Detection Using an Adaptive Fuzzy Logic Based Screening System , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[16]  C. Peng,et al.  Detection of obstructive sleep apnea from cardiac interbeat interval time series , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[17]  F. Leisch.  FlexMix: A general framework for finite mixture models and latent class regression in R , 2004 .

[18]  Eric R. Ziegel,et al.  An Introduction to Generalized Linear Models , 2002, Technometrics.

[19]  C. Borror.  Generalized Linear Models and Extensions, Second Edition , 2008 .