TY - JOUR
T1 - A linear mixed-effects model for multivariate censored data
AU - Pan, Wei
AU - Louis, Thomas A.
PY - 2000/3
Y1 - 2000/3
N2 - We apply a linear mixed-effects model to multivariate failure time data. Computation of the regression parameters involves the Buckley-James method in an iterated Monte Carlo expectation-maximization algorithm, wherein the Monte Carlo E-step is implemented using the Metropolis-Hastings algorithm. From simulation studies, this approach compares favorably with the marginal independence approach, especially when there is a strong within-cluster correlation.
AB - We apply a linear mixed-effects model to multivariate failure time data. Computation of the regression parameters involves the Buckley-James method in an iterated Monte Carlo expectation-maximization algorithm, wherein the Monte Carlo E-step is implemented using the Metropolis-Hastings algorithm. From simulation studies, this approach compares favorably with the marginal independence approach, especially when there is a strong within-cluster correlation.
KW - Buckley-James method
KW - Generalized estimating equations
KW - Least squares
KW - Metropolis-Hastings algorithm
KW - Monte Carlo expectation- maximization
KW - Restricted maximum likelihood estimation
UR - http://www.scopus.com/inward/record.url?scp=0034104426&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0034104426&partnerID=8YFLogxK
U2 - 10.1111/j.0006-341X.2000.00160.x
DO - 10.1111/j.0006-341X.2000.00160.x
M3 - Article
C2 - 10783791
AN - SCOPUS:0034104426
SN - 0006-341X
VL - 56
SP - 160
EP - 166
JO - Biometrics
JF - Biometrics
IS - 1
ER -