Statistical meta-analysis for ordinal categorical data

Hossain, Md. Belal and Khan, Shahjahan (2012) Statistical meta-analysis for ordinal categorical data. In: 11th Islamic Countries Conference on Statistical Sciences (ICCSS-11), 19-22 Dec 2011, Lahore, Pakistan.


Traditionally the odds ratio (OR) is used for measuring the extent of association between exposure and its binary outcomes in randomised controlled trials (RCTs) and similar studies. It is inapplicable if the outcomes are on an ordinal scale with more than two categories. In those studies, the generalised odds ratio (GOR) is used for summarising the difference between two stochastically ordered distributions of an ordinal categorical variable. Meta-analysis combines data from various independent trials in estimating the overall effect measure to make the sample size larger so that the inference based on the
combined data is more reliable. In this paper we developed a method of meta-analysis using the GOR under independent multinomial sampling scheme for ordinal categorical data.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Lecture)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2011, Islamic Countries Society of Statistical Sciences. Permanent restricted access to published version due to publisher copyright policy.
Faculty/School / Institute/Centre: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 15 May 2012 03:06
Last Modified: 02 May 2017 23:26
Uncontrolled Keywords: generalised odds ratio; ordinal data; multinomial distribution; meta-analysis
Fields of Research : 11 Medical and Health Sciences > 1199 Other Medical and Health Sciences > 119999 Medical and Health Sciences not elsewhere classified
01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
01 Mathematical Sciences > 0104 Statistics > 010405 Statistical Theory
Socio-Economic Objective: C Society > 92 Health > 9299 Other Health > 929999 Health not elsewhere classified
E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences

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