anova.joint | R Documentation |

Perform a likelihood ratio test between two (**nested**) `joint`

models. The user must decide whether the models are truly nested.

```
## S3 method for class 'joint'
anova(object, object2, ...)
```

`object` |
a joint model fit by the |

`object2` |
a joint model fit by the |

`...` |
additional arguments (none used). |

A list of class `anova.joint`

with elements

`mod0`

the name of

`object`

.`l0`

the log-likelihood of the nested model, i.e. fit under the null.

`AIC0`

AIC for

`object`

.`BIC0`

BIC for

`object`

.`mod1`

the name of

`object2`

.`l1`

the log-likelihood under the alternative hypothesis.

`AIC1`

AIC for

`object2`

.`BIC1`

BIC for

`object2`

.`LRT`

likelihood ratio test statistic.

`p`

the p-value of

`LRT`

.`warnSurv`

internal - logical value for printing difference in survival models.

`warnRanefs`

internal - logical value for printing difference in random effects specifications.

James Murray (j.murray7@ncl.ac.uk)

`joint`

and `logLik.joint`

.

```
rm(list=ls())
data(PBC)
# Compare quadratic vs linear time specification for log(serum bilirubin) -----
PBC$serBilir <- log(PBC$serBilir)
long.formulas1 <- list(serBilir ~ drug * time + (1 + time|id))
long.formulas2 <- list(serBilir ~ drug * (time + I(time^2)) + (1 + time + I(time^2)|id))
surv.formula <- Surv(survtime, status) ~ drug
family <- list('gaussian')
# Fit the two competing models (fit is nested in fit2) ------------------------
fit <- joint(long.formulas1, surv.formula, PBC, family,
control = list(verbose = FALSE))
fit2 <- joint(long.formulas2, surv.formula, PBC, family, control = list(verbose = FALSE))
anova(fit, fit2)
# Quadratic terms improve fit significantly.
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.