Literature DB >> 15236422

A latent normal distribution model for analysing ordinal responses with applications in meta-analysis.

Wai-Yin Poon1.   

Abstract

We consider the comparison of two treatments (or a treatment and a control/placebo) with responses that are classified into ordinal categories. By operating on the assumption that the responses are manifestations of some underlying continuous variables and that the definitions of the categories for the treatment group and the placebo group are the same in the same clinical test centre, we develop a model to examine the possible treatment effects. These treatment effects can be identified as location effect or dispersion effect. The method can be generalized to analyse clinical test results coming from different centres, where each centre may have its own standard in classifying responses. The method is technically undemanding and can be implemented in a very simple and straightforward way by using easily accessible software that can be downloaded at no cost. Real data sets are analysed for illustration. Copyright 2004 John Wiley & Sons, Ltd.

Mesh:

Substances:

Year:  2004        PMID: 15236422     DOI: 10.1002/sim.1814

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  5 in total

1.  A unified framework for the comparison of treatments with ordinal responses.

Authors:  Tong-Yu Lu; Wai-Yin Poon; Siu Hung Cheung
Journal:  Psychometrika       Date:  2013-11-28       Impact factor: 2.500

2.  The trend odds model for ordinal data.

Authors:  Ana W Capuano; Jeffrey D Dawson
Journal:  Stat Med       Date:  2012-12-06       Impact factor: 2.373

3.  Analysis of an ordinal outcome in a multicentric randomized controlled trial: application to a 3- arm anti- malarial drug trial in Cameroon.

Authors:  Solange Youdom Whegang; Leonardo K Basco; Henri Gwét; Jean-Christophe Thalabard
Journal:  BMC Med Res Methodol       Date:  2010-06-18       Impact factor: 4.615

Review 4.  Meta-analysis of test accuracy studies: an exploratory method for investigating the impact of missing thresholds.

Authors:  Richard D Riley; Ikhlaaq Ahmed; Joie Ensor; Yemisi Takwoingi; Amanda Kirkham; R Katie Morris; J Pieter Noordzij; Jonathan J Deeks
Journal:  Syst Rev       Date:  2015-02-04

5.  Multivariate random effects meta-analysis of diagnostic tests with multiple thresholds.

Authors:  Taye H Hamza; Lidia R Arends; Hans C van Houwelingen; Theo Stijnen
Journal:  BMC Med Res Methodol       Date:  2009-11-10       Impact factor: 4.615

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.