Document Type : Original Article
Authors
- Mohammad Reza Baneshi 1
- Somayeh Shahroudi 2
- Maliheh Rezaei 2
- Farzaneh Zolala 3
- Maryam Okhovati 4
- Ali Akbar Haghdoost 5
1 PhD in Marv Epidemiology and Biostatistics PhD , Associate Professor, Department of Epidemiology and Biostatistics, Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences
2 M.Sc. Student in Epidemiology, Iranian Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran
3 PhD in Epidemiology, Assistant Professor, Department of Epidemiology and Biostatistics, Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
4 PhD in Information Sciences, Assistant Professor, Department of Library Sciences, Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
5 PhD in Epidemiology, Professor, Department of Epidemiology, Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
Abstract
Background & Objective: Improving the quality of education is the most central values of academic institutions and higher education Given professors have played a decisive role in this context for assessing the quality of education we need to evaluate the quality of instruction One of the common methods for professors evaluation is evaluation by students that it usually takes place at the end of each semester With regard to the professors evaluation data are of various types: the longitudinal data or repeated measurements over time therefore to evaluate it the quality of instruction should be used with longitudinal data analysis However such methods often are explained by complex methodology This article introduces multilevel linear model and generalized estimating equations approach and valueadded models by simple and applied expression as appropriate models for analysis of longitudinal data such as professors evaluation data
Keywords
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