Abstract
This paper illustrates the use of latent class analysis to classify 50,000 infants into a small number of classes or case types, as a preliminary to a study of the allocation of neonatal hospital resources throughout Scotland. Information, extracted from a detailed neonatal discharge record, was summarized by 11 clinical and diagnostic catagorical variables. Statistical models incorporating 1 to 6 latent classes were then estimated using the EM algorithm. The 4 class model was chosen because it provided a good description of the data and the resulting classes had a medical interpretation. The factors influencing the choice of model are discussed and goodness of fit tests are presented. The stability of the classes was also investigated using random halves of the data and an earlier comparable data set.
Original language | English |
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Pages (from-to) | 249-259 |
Number of pages | 11 |
Journal | Statistics in Medicine |
Volume | 3 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1984 |
Externally published | Yes |
Keywords
- Classification
- EM algorithm
- Latent class analysis
- Neonatal discharge record