summary.joint: Summarise a random effects joint model fit

Description Usage Arguments Value Author(s) Examples

View source: R/summary.joint.R

Description

Generic function used to produce summary information from a fitted random effects joint model as represented by object of class joint.

Usage

1
2
## S3 method for class 'joint'
summary(object, variance = TRUE, ...)

Arguments

object

an object of class joint.

variance

should the variance components be output as variances or standard deviations? Defaults to variance = TRUE.

...

further arguments for the summary.

Value

An object inheriting from class summary.joint with all components included in object (see joint for a full description of the components) plus the following components:

nobs

the total number of (typically longitudinal) observations (i.e. rows in an unbalanced data set).

ngrps

the number of groups in the analyzed dataset, often individual subjects.

Author(s)

Pete Philipson

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
data(heart.valve)
heart.surv <- UniqueVariables(heart.valve,
                              var.col = c("fuyrs","status"),
                              id.col = "num")
heart.long <- heart.valve[, c("num", "time", "log.lvmi")]
heart.cov <- UniqueVariables(heart.valve,
                             c("age", "hs", "sex"),
                             id.col = "num")
heart.valve.jd <- jointdata(longitudinal = heart.long,
                            baseline = heart.cov,
                            survival = heart.surv,
                            id.col = "num",
                            time.col = "time")
fit <- joint(data = heart.valve.jd,
             long.formula = log.lvmi ~ 1 + time + hs,
             surv.formula = Surv(fuyrs,status) ~ hs,
             model = "intslope")
summary(fit)

Example output

Loading required package: survival

Call:
joint(data = heart.valve.jd, long.formula = log.lvmi ~ 1 + time + 
    hs, surv.formula = Surv(fuyrs, status) ~ hs, model = "intslope")

Random effects joint model
 Data: heart.valve.jd 
 Log-likelihood: -424.7062 

Longitudinal sub-model fixed effects: log.lvmi ~ 1 + time + hs                              
(Intercept)        4.993354492
time              -0.006966354
hsStentless valve  0.055452730

Survival sub-model fixed effects: Surv(fuyrs, status) ~ hs                           
hsStentless valve 0.7926683

Latent association:                 
gamma_0 0.8227578

Variance components:
        U_0         U_1    Residual 
0.113521695 0.001757578 0.037086210 

Convergence at iteration: 13 

Number of observations: 988 
Number of groups: 256 

joineR documentation built on June 1, 2021, 5:06 p.m.