TY  - BOOK
AU  - Sabah Lotfy Mohamed Elsayed
AU  - Elhousseny Abdelbar Rady , 
TI  - Predicting length of stay and mortality rate in intensive care units / 
PY  - 2018///
CY  - Cairo : 
PB  - Sabah Lotfy Mohamed Elsayed , 
KW  - Goodness of Fit
KW  - ICU Mortality
KW  - Length of Stay
N1  - Thesis (M.Sc.) - Cairo University -Institute of Statistical Studies and Research - Department of Statistics and Econometrics; Issued also as CD
N2  - Modelling can be a useful tool to find out what the distributions of hospital length of stay (LOS) and the factors affecting it. The study aimed to identify the statistical models for predicting the length of stay and mortality rate in the intensive care unit at Zagazig University Hospital, Al Sharqia, Egypt. A study of 340 patients was conducted at the intensive care unit of Zagazig University Hospital during the period of 2016. At first, the descriptive statistical analysis of dependent variables using the SPSS Ver. 22. At second, the statistical analysis of regression models of dependent variables was performed using the R package.The predictive model was selected throughout the following steps: (1) The SPSS package was used to test the normality distribution of the length of stay; (2) The Cramer-von Mises test was used to select the fit model by using the R package; (3) Use Akaike information criterion and mean square error to affirm the best fit model for predicting the length of stay. Based on different statistical tools starting with descriptive statistics and then regression models. Form models of the length of the patients stay the normality assumption is tested
UR  - http://172.23.153.220/th.pdf
ER  -