Abstract
Incomplete data are common phenomenon in research that adopts the longitudinal design approach. If incomplete observations are present in the longitudinal data structure, ignoring it could lead to bias in statistical inference and interpretation. We adopt the disposition model and extend it to the analysis of longitudinal binary outcomes in the presence of monotone incomplete data. The response variable is modeled using a conditional logistic regression model. The nonresponse mechanism is assumed ignorable and developed as a combination of Markov's transition and logistic regression model. MLE method is used for parameter estimation. Application of our approach to rheumatoid arthritis clinical trials is presented.
Highlights
Let Nt, t 0 be a homogeneous Poisson process and let Yi, i 1, 2, 3, ..., be i.i.d.random variables, independent of the process Nt, t 0
The statistical significance of the compound Poisson process arises from its applicability in real life situations, where the researcher often observes only the total amount X t, which is composed of an unknown random number N t of random contributions Yi, i 1, 2, 3
The Laplace Stieltjes transforms of the distribution function of the first exit time with positive jumps were given by Bar-Lev et al [8] for the compound Poisson process where Yi, i 1, 2, ..., were continuous random variables
Summary
Let Nt , t 0 be a homogeneous Poisson process and let Yi , i 1, 2, 3, ..., be i.i.d. The Laplace Stieltjes transforms of the distribution function of the first exit time with positive jumps were given by Bar-Lev et al [8] for the compound Poisson process where Yi , i 1, 2, ..., were continuous random variables. The explicit distribution function of the first exit time for the compound Poisson process was obtained by Ozel and Inal [9] where Yi , i 1, 2, ..., are discrete random variables. Yi , i 1, 2, ..., are discrete random variables representing the positive integer-valued jump sizes. The mean first exit time is obtained for the compound Poisson process with an upper horizontal boundary and positive integer-valued jump sizes.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
