ESTIMASI MAKSIMUM LIKELIHOOD PADA MODEL GROWTH CURVE DAN APLIKASINYA PADA MODEL GROWTH CURVE LINEAR

• المؤلفون الرئيسيون: , FAUZIA FATMANINGRUM, , Prof. Dr. Sri Haryatmi, M.Sc.
• التنسيق: Theses and Dissertations NonPeerReviewed
• منشور في: [Yogyakarta] : Universitas Gadjah Mada 2013
• الموضوعات: ETD
• الوصول للمادة أونلاين: https://repository.ugm.ac.id/122941/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=63050
• المؤسسة: Universitas Gadjah Mada

Growth curve model is a model of Generalized Multivariate Analysis of variance (GMANOVA) that is specifically used to analyze the growth problem in a short time series. For the case of linear growth of the subject, the model used linear growth curve. The purpose of the analysis is the comparison of the model growth curve parameters to determine the response variables were observed at a particular time series, on some existing group. Where in several fields of science such as animal science, horticulture, clinical trials, medical science, psychology, experimental psychology, biology, and social analysis is required on the issue of comparing the observed growth a subject back in a certain time series for the case of more than 2 groups or treatment. The problem has some similarities with the MANOVA problem, it's just that the response variable defined as the growth of a particular subject or time series which is called the case of repeated measure. Repeated measure refers to a situation in which several variables measuring the response obtained, for some period of time, from each experimental unit. Typically, responses are taken from time to time, in the weekly / monthly. In this paper the steps used to analyze the growth curve is the growth curve testing of model assumptions, the estimated growth curve model parameters using the Maximum likelihood estimator (MLE) to estimate the growth curve model parameters, and benchmarking parameters of growth curve models.