کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
415575 681214 2007 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Likelihood approach for count data in longitudinal experiments
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Likelihood approach for count data in longitudinal experiments
چکیده انگلیسی

In many cancer studies and clinical research, repeated observations of response variables are taken over time on each individual in one or more treatment groups. In such cases the repeated observations of each vector response are likely to be correlated and the autocorrelation structure for the repeated data plays a significant role in the estimation of regression parameters. A random intercept model for count data is developed using exact maximum-likelihood estimation via numerical integration. A simulation study is performed to compare the proposed methodology with the traditional generalized linear mixed model (GLMM) approach and with the GLMM when penalized quasi-likelihood method is used to perform maximum-likelihood estimation. The methodology is illustrated by analyzing data sets containing longitudinal measures of number of tumors in an experiment of carcinogenesis to study the influence of lipids in the development of cancer.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 12, 15 August 2007, Pages 6511–6520
نویسندگان
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