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Collerton, D., Perry, E. & McKeith, I. Why people see things that are not there: a novel Perception and Attention Deficit model for recurrent complex visual hallucinations.

The Andersen-Gill model (A-G model), an extension of the standard Cox proportional hazard model for recurrent events, accommodates censored data and time-dependent covariates (Fleming and Harrington 1991; Therneau and Grambsch 2000).

Here, our main goal is to validate a method of predictions from a joint model for recurrent events and death as accurate predictions.

To account for the recurrent events and their association with the risk of death, we used a joint frailty model for recurrent events and a terminal event.

Falls rates in hospital will be analysed using Cox semi-parametric proportional hazards regression analysis (Anderson-Gill model for recurrent events) with the intervention groups entered as dummy variables.

To determine risk factors for recurrent events, we used an extension of the Cox proportional hazards model for recurrent event data, the Prentice, Williams and Peterson gap time (PWP-GT) model [ 18].

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The proposed simulation algorithm can also be applied to simulate the recurrence process in joint models for recurrent events and a terminal event [ 28, 29].

Procedures for estimating the parameters of the general class of semiparametric models for recurrent events proposed by Peña and Hollander [(2004). Models for recurrent events in reliability and survival analysis. In: Soyer R., Mazzuchi T., Singpurwalla N. (Eds)., Mathematical Reliability: An Expository Perspective. Kluwer Academic Publishers, Dordrecht, pp. 105 123 (Chapter 6)] are developed.

Pena et al [ 19] and Pena et al [ 20] also discussed the general class of semi-parametric models for recurrent events.

Cox models for recurrent falls showed that intervention had a negative effect (hazard ratio [HR] 1.46, 95% CI 1.03 2.09) and that functional impairment (HR 1.42, 95% CI 0.97 2.12), previous falls (HR 1.09, 95% CI 0.74 1.60), and cognitive impairment (HR 1.08, 95% CI 0.72 1.60) had no effect on the assessment.

ABSOLUTE [ 122] uses data from copy number variations for optimizing models of recurrent cancer karyotypes and expected allelic fraction values for somatic SNVs.

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