Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - A latent variable scorecard for neonatal baby frailty.
AU - Whittaker, Joseph
AU - Bowden, Jack
N1 - RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research
PY - 2005/7
Y1 - 2005/7
N2 - A latent variable frailty model is built for data coming from a neonatal study conducted to investigate whether the presence of a particular hospital service given to families with premature babies has a positive effect on their care requirements within the first year of life. The predicted value of the latent frailty term from information obtained from the family in advance of the birth furnishes an overall measure of the quality of health of the baby. This identifies families at risk. Maximum likelihood and Bayesian approaches are used to estimate the effect of the variables on the value of the latent baby frailty and for prediction of health complications. It is found that these give much the same estimates of regression coefficients, but that the variance components are the more difficult to estimate. We indicate how the findings from the model may be presented as a scorecard for predicting frailty, and so be useful to doctors working in hospital neonatal units. New information about a baby is automatically combined with the current score to provide an up-to-date score, so that rapid decisions for taking appropriate action are made more possible. A diagnostic procedure is proposed to assess how well the independence assumptions of the model are met in fitting to this data. It is concluded that the frailty model provides an informative summary of the data from this neonatal study.
AB - A latent variable frailty model is built for data coming from a neonatal study conducted to investigate whether the presence of a particular hospital service given to families with premature babies has a positive effect on their care requirements within the first year of life. The predicted value of the latent frailty term from information obtained from the family in advance of the birth furnishes an overall measure of the quality of health of the baby. This identifies families at risk. Maximum likelihood and Bayesian approaches are used to estimate the effect of the variables on the value of the latent baby frailty and for prediction of health complications. It is found that these give much the same estimates of regression coefficients, but that the variance components are the more difficult to estimate. We indicate how the findings from the model may be presented as a scorecard for predicting frailty, and so be useful to doctors working in hospital neonatal units. New information about a baby is automatically combined with the current score to provide an up-to-date score, so that rapid decisions for taking appropriate action are made more possible. A diagnostic procedure is proposed to assess how well the independence assumptions of the model are met in fitting to this data. It is concluded that the frailty model provides an informative summary of the data from this neonatal study.
KW - community neonatal services • conditional independence • empirical Bayes prediction • frailty scorecard • GLLAMM • Hand and Crowder quality model • JAGS • MIMIC model • neonatal unit • premature birth
U2 - 10.1191/1471082X05st093oa
DO - 10.1191/1471082X05st093oa
M3 - Journal article
VL - 5
SP - 159
EP - 172
JO - Statistical Modelling
JF - Statistical Modelling
SN - 1471-082X
IS - 2
ER -