logitord | R Documentation |
logitord
fits an longitudinal proportional odds model in discrete
time to the ordinal outcomes and a logistic model to the probability of
dropping out using a common random effect for the two.
logitord(
y,
id,
out.ccov = NULL,
drop.ccov = NULL,
tvcov = NULL,
out.tvcov = !is.null(tvcov),
drop.tvcov = !is.null(tvcov),
pout,
pdrop,
prand.out,
prand.drop,
random.out.int = TRUE,
random.out.slope = !is.null(tvcov),
random.drop.int = TRUE,
random.drop.slope = !is.null(tvcov),
binom.mix = 5,
fcalls = 900,
eps = 1e-04,
print.level = 0
)
y |
A vector of binary or ordinal responses with levels 1 to k and 0 indicating drop-out. |
id |
Identification number for each individual. |
out.ccov |
A vector, matrix, or model formula of time-constant
covariates for the outcome regression, with variables having the same
length as |
drop.ccov |
A vector, matrix, or model formula of time-constant
covariates for the drop-out regression, with variables having the same
length as |
tvcov |
One time-varying covariate vector. |
out.tvcov |
Include the time-varying covariate in the outcome regression. |
drop.tvcov |
Include the time-varying covariate in the drop-out regression. |
pout |
Initial estimates of the outcome regression coefficients, with length equal to the number of levels of the response plus the number of covariates minus one. |
pdrop |
Initial estimates of the drop-out regression coefficients, with length equal to one plus the number of covariates. |
prand.out |
Optional initial estimates of the outcome random parameters. |
prand.drop |
Optional initial estimates of the drop-out random parameters. |
random.out.int |
If TRUE, the outcome intercept is random. |
random.out.slope |
If TRUE, the slope of the time-varying covariate is random for the outcome regression (only possible if a time-varying covariate is supplied and if out.tvcov and random.out.int are TRUE). |
random.drop.int |
If TRUE, the drop-out intercept is random. |
random.drop.slope |
If TRUE, the slope of the time-varying covariate is random for the drop-out regression (only possible if a time-varying covariate is supplied and if drop.tvcov and random.drop.int are TRUE). |
binom.mix |
The total in the binomial distribution used to approximate the normal mixing distribution. |
fcalls |
Number of function calls allowed. |
eps |
Convergence criterion. |
print.level |
If 1, the iterations are printed out. |
A list of class logitord
is returned.
T.R. Ten Have and J.K. Lindsey
Ten Have, T.R., Kunselman, A.R., Pulkstenis, E.P. and Landis, J.R. (1998) Biometrics 54, 367-383, for the binary case.
y <- trunc(runif(20,max=4))
id <- gl(4,5)
age <- rpois(20,20)
times <- rep(1:5,4)
logitord(y, id=id, out.ccov=~age, drop.ccov=age, pout=c(1,0,0),
pdrop=c(1,0))
logitord(y, id, tvcov=times, pout=c(1,0,0), pdrop=c(1,0))
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