Description Usage Arguments Value References See Also Examples
Joint modeling of longitudinal continuous data and competing risks
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p |
The dimension of fixed effects (include intercept) in yfile. |
yfile |
Y matrix for longitudinal measurements in long format. For example, for a subject with n measurements, there should be n rows for this subject. The # of rows in y matrix is the total number of measurements for all subjects in the study. The columns in Y should start with the longitudinal outcome (column 1), the covariates for the random effects, and then the covariates for the fixed effects. |
cfile |
C matrix for competing risks failure time data. Each subject has one data entry, so the number of rows equals to the number of subjects. The survival / censoring time is included in the first column, and the failure type coded as 0 (censored events), 1 (risk 1), or 2 (risk 2) is given in the second column. Two competing risks are assumed. The covariates are included in the third column and on. |
mfile |
M vector to indicate the number of longitudinal measurements per subject. The number of rows equals to the number of subjects. |
point |
Quadrature points used in the EM procedure.Default is 20. |
maxiterations |
Maximum values of iterations. Default is 100000. |
do.trace |
Print detailed information of each iteration. Default is false, i.e., not to print the iteration details. |
type_file |
Types of inputs. Default is true, i.e. data files with headers. If set to "F", inputs are changed to data matrixes or data.frames (with headers) |
Object of class JMcmprsk
with elements
vcmatrix | The variance-covariance matrix for all the parameters. The parameters are in the order: β, σ^2, γ, ν, and Σ. The elements in Σ are output in the order along the main diagonal line, then the second main diagonal line, and so on. |
betas | The point estimates of β. |
se_betas | The standard error estimate of β. |
gamma_matrix | The point estimate of γ. |
se_gamma_matrix | The standard error estimate of γ. |
v_estimate | The point estimate of ν. |
se_v_estimate | The standard error estimate of ν. |
sigma2_val | The point estimate of σ^2. |
se_sigma2_val | The standard error estimate of σ^2. |
sigma_matrix | The point estimate of Σ (only the upper triangle portion of the matrix is output). |
se_sigma | The standard error estimate of Σ.The standard errors are given in this order: main diagonal, the second main diagonal, and so on. |
loglike | Log Likelihood. |
Elashoff, Robert M., Gang Li, and Ning Li. "A joint model for longitudinal measurements and survival data in the presence of multiple failure types." Biometrics 64.3 (2008): 762-771.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # A toy example on a dataset called from file paths
require(JMcmprsk)
set.seed(123)
yfile=system.file("extdata", "jmcsimy.txt", package = "JMcmprsk")
cfile=system.file("extdata", "jmcsimc.txt", package = "JMcmprsk")
mfile=system.file("extdata", "jmcsimm.txt", package = "JMcmprsk")
jmc_0fit = jmc_0(p=4, yfile, cfile, mfile, point=6, do.trace = FALSE)
## Not run:
# A toy example on data frames/matrices
require(JMcmprsk)
set.seed(123)
data(lung)
lungY <- lung[, c(2:11)]
lungC <- unique(lung[, c(1, 12, 13, 6:10)])
lungC <- lungC[, -1]
lungM <- data.frame(table(lung$ID))
lungM <- as.data.frame(lungM[, 2])
res1=jmc_0(p=8, lungY, lungC, lungM, point=20, do.trace = FALSE, type_file = FALSE)
res1
## End(Not run)
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