Mohammad Reza Baneshi; Farzaneh Zolala; Elham Mohebbi
Volume 11, Issue 3 , November 2014, , Pages 321-329
Abstract
Background & Objective: The main purpose of medical researches is to answer a research question or to solve a problem to promote the health of a society The first objective is to answer the research question correctly with minimal errors The second objective is the publication of the results ...
Read More
Background & Objective: The main purpose of medical researches is to answer a research question or to solve a problem to promote the health of a society The first objective is to answer the research question correctly with minimal errors The second objective is the publication of the results in order to generalize them to a population and use in a wider dimension To achieve these objectives using biostatistics is necessary Despite the importance of biostatistics in medical research researchers have limited understanding of it or due to its complications they refrain from its use Statistics help the researcher in different levels of research including writing a proposal and interpretation of other papers Moreover biostatisticians and epidemiologists also play a very important role in the preparation of manuscripts for publication The present article has eloquently described the most important statistical tests in medical research with applied examples
Mohammad Reza Baneshi; Somayeh Shahroudi; Maliheh Rezaei; Farzaneh Zolala; Maryam Okhovati; Ali Akbar Haghdoost
Volume 11, Issue 2 , August 2014, , Pages 196-204
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 ...
Read More
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
Mohammad Reza Baneshi; saeide hajimaghsoodi; Azam Rastegari; Mohammad Reza Mahmoodi
Volume 8, Issue 1 , July 2011, , Pages 4-13
Abstract
In recent years using statistics in medical sciences is increasing and statistics is an essential part of each research At present for each study design and for each type of data there are appropriate statistical methods which yield to valid results and inferences Familiarity with such methods is essential ...
Read More
In recent years using statistics in medical sciences is increasing and statistics is an essential part of each research At present for each study design and for each type of data there are appropriate statistical methods which yield to valid results and inferences Familiarity with such methods is essential especially for those involved in the field of medical research as they might confuse majority of readers who are not familiar with details of statistical analysis and data interpretation Other consequences include waste of money time and energy spent for each research project In recent years some papers have been published to enhance researchers knowledge of statistics and its application in research methodology but still there are many methodological mistakes in manuscripts In this article we aim to demonstrate appropriate methods for data analysis We will discuss importance of confidence intervals and their advantages over Pvalue We will finally highlight common errors in data analysis such as univariate methods ignoring power in detection of difference between groups and using correlation coefficient to assess the agreement between scores
