Analysis of mixed correlated bivariate zero-inflated count and (k, l)-inflated beta responses with application to social network datasets. Issue 7 (3rd April 2019) - Tabrizi, E.; Samani, E. Bahrami; Ganjali, M.
ABSTRACT: This paper presents a new model that monitors the basic network formation mechanisms via the attributes through time. It considers the issue of joint modeling of longitudinal inflated (0, 1)-support continuous and inflated count response variables. For joint model of mentioned response variables, a correlated generalized linear mixed model is studied. The fraction response is inflated in two points k and l ( k < l ) and a k and l inflated beta distribution is introduced to use as its distribution. Also, the count response is inflated in zero and we use some members of zero-inflated power series distributions, hurdle-at-zero, members of zero-inflated double power series distributions and zero-inflated generalized Poisson distribution as our count response distribution. A full likelihood-based approach is used to yield maximum likelihood estimates of the model parameters and the model is applied to a real social network obtained from an observational study where the rate of the i th node's responsiveness to the j th node and the number of arrows or edges with some specific characteristics from the i th node to the j th node are the correlated inflated (0, 1)-support continuous and inflated count response variables, respectively. The effect of the sender and receiver positions in an office environment on the responses are investigated simultaneously.