PMC:7116472 / 10369-10978 JSONTXT

{"project":"LitCovid-sentences","denotations":[{"id":"T68","span":{"begin":0,"end":53},"obj":"Sentence"},{"id":"T69","span":{"begin":54,"end":242},"obj":"Sentence"},{"id":"T70","span":{"begin":243,"end":427},"obj":"Sentence"},{"id":"T71","span":{"begin":428,"end":609},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"We used a three stage model building process (fig 1). Firstly, generalised additive models were built incorporating continuous smoothed predictors (penalised thin plate splines) in combination with categorical predictors as linear components. A criterion based approach to variable selection was taken based on the deviance explained, the unbiased risk estimator, and the area under the receiver operating characteristic curve. Secondly, we visually inspected plots of component smoothed continuous predictors for linearity, and selected optimal cut-off values by using the methods of Barrio and colleagues.18"}