An EM Algorithm for Mixed-Type Multiple Outcome Regressions With Applications to a Prostate Cancer Study
An EM Algorithm for Mixed-Type Multiple Outcome Regressions With Applications to a Prostate Cancer Study
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Date
2008-06-05
Authors
Rudd, JoAnn M.
Advisor
Smith, Paul J.
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Abstract
We propose a joint model for binary and continuous responses using a latent
variable for the binary response. The observed continuous response and the latent
response are treated as correlated normals obeying a bivariate regression model. We
develop an EM algorithm to find maximum likelihood estimates for the parameters.
We perform the E-step analytically and use an iterative algorithm for the M-step.
The algorithm is applied to a prostate cancer clinical trial whose goal was
to assess therapeutic effects of diethylstilbestrol (DES) in advanced cancer patients
and to assess possible excess cardiovascular mortality. Therapeutic effects were
measured as prostatic acid phosphatase (PAP) levels follow-up and whether the
patient progressed to stage IV or died of cancer. The treatment reduced PAP levels
but not the incidence of cancer mortality within a six-month time frame. Higher
doses of DES were associated with increased risk of cardiovascular-related death.