Description Usage Arguments Value Warning Author(s) References See Also Examples

Produces marginal Wald tests or Performs a likelihood ratio test between two nested joint models.

1 2 3 |

`object` |
an object inheriting from class |

`object2` |
an object inheriting from class |

`test` |
logical; if |

`process` |
for which of the two submodels to produce the marginal Wald tests table. |

`L` |
a numeric matrix of appropriate dimensions defining the contrasts of interest. |

`...` |
additional arguments; currently none is used. |

An object of class `aov.jointModel`

with components,

`nam0` |
the name of |

`L0` |
the log-likelihood under the null hypothesis ( |

`aic0` |
the AIC value for the model given by |

`bic0` |
the BIC value for the model given by |

`nam1` |
the name of |

`L1` |
the log-likelihood under the alternative hypothesis ( |

`aic1` |
the AIC value for the model given by |

`bic1` |
the BIC value for the model given by |

`df` |
the degrees of freedom for the test (i.e., the difference in the number of parameters). |

`LRT` |
the value of the Likelihood Ratio Test statistic (returned if |

`p.value` |
the |

`aovTab.Y` |
a data.frame with the marginal Wald tests for the longitudinal process;
produced only when |

`aovTab.T` |
a data.frame with the marginal Wald tests for the event process;
produced only when |

`aovTab.L` |
a data.frame with the marginal Wald tests for the user-defined contrasts matrix;
produced only when |

The code minimally checks whether the models are nested! The user is responsible to supply nested models in order the LRT to be valid.

Dimitris Rizopoulos [email protected]

Rizopoulos, D. (2012) *Joint Models for Longitudinal and Time-to-Event Data: with
Applications in R*. Boca Raton: Chapman and Hall/CRC.

Rizopoulos, D. (2010) JM: An R Package for the Joint Modelling of Longitudinal and Time-to-Event Data.
*Journal of Statistical Software* **35** (9), 1–33. http://www.jstatsoft.org/v35/i09/

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ```
## Not run:
# linear mixed model fit without treatment effect
fitLME.null <- lme(sqrt(CD4) ~ obstime,
random = ~ 1 | patient, data = aids)
# cox model fit without treatment effect
fitCOX.null <- coxph(Surv(Time, death) ~ 1,
data = aids.id, x = TRUE)
# joint model fit without treatment effect
fitJOINT.null <- jointModel(fitLME.null, fitCOX.null,
timeVar = "obstime", method = "weibull-PH-aGH")
# linear mixed model fit with treatment effect
fitLME.alt <- lme(sqrt(CD4) ~ obstime * drug - drug,
random = ~ 1 | patient, data = aids)
# cox model fit with treatment effect
fitCOX.alt <- coxph(Surv(Time, death) ~ drug,
data = aids.id, x = TRUE)
# joint model fit with treatment effect
fitJOINT.alt <- jointModel(fitLME.alt, fitCOX.alt, timeVar = "obstime",
method = "weibull-PH-aGH")
# likelihood ratio test for treatment effect
anova(fitJOINT.null, fitJOINT.alt)
## End(Not run)
``` |

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