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Table 2 Overview of the different scenarios, corresponding log-likelihood functions and parasitaemia data that is included in the analyses

From: Modelling longitudinal binary outcomes with outcome dependent observation times: an application to a malaria cohort study

Scenario

Log-likelihood function

Parasitaemia data

1

\(ll_{1}(\varvec{\beta }, \varvec{\theta } | \varvec{y}, \varvec{X}) = \sum _{i = 1}^{n}{\log \left[ L_{1j}(\varvec{\beta }, \varvec{\theta } | \varvec{y}_{i}, \varvec{x}_i)\right] }\)

Routine

2

\(ll_{1}(\varvec{\beta }, \varvec{\theta } | \varvec{y}, \varvec{X}) = \sum _{i = 1}^{n}{\log \left[ L_{1j}(\varvec{\beta }, \varvec{\theta } | \varvec{y}_{i}, \varvec{x}_i)\right] }\)

Routine & clinical\(^{*}\)

3

\(ll_{2}(\varvec{\zeta }, \varvec{\vartheta } | \varvec{t}, \varvec{y}, \varvec{a}, \varvec{X}) = \sum _{i = 1}^{n}{\log \left[ L_{2i}(\varvec{\zeta }, \varvec{\vartheta } | \varvec{t}_{i}, \varvec{y}_i, \varvec{a}_{i}, \varvec{x}_i)\right] }\)

Clinical

4

\(ll_{3}(\varvec{\beta }, \varvec{\theta }, \varvec{\zeta }, \varvec{\vartheta } | \varvec{t}, \varvec{y}, \varvec{a}, \varvec{X}) = \sum _{i = 1}^{n}{\log \left[ L_{3i}(\varvec{\beta }, \varvec{\theta }, \varvec{\zeta }, \varvec{\vartheta } | \varvec{t}_{i}, \varvec{y}_i, \varvec{a}_{i}, \varvec{x}_i)\right] }\)

Routine & clinical

  1. \(^{*}\) Scenario 2 does not take ODS into account