SciELO - Scientific Electronic Library Online

 
vol.35 special issue 2An Extension to the Scale Mixture of Normals for Bayesian Small-Area EstimationComparison between SVM and Logistic Regression: Which One is Better to Discriminate? author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Revista Colombiana de Estadística

Print version ISSN 0120-1751

Abstract

CATALAN, MÓNICA; GALINDO, M. PURIFICACIÓN; MARTIN, JAVIER  and  LEIVA, VÍCTOR. Integration Methods of Odds Ratio Based on Meta-AnalysisUsing Fixed and Random Effect Models Useful in Public Health. Rev.Colomb.Estad. [online]. 2012, vol.35, n.spe2, pp.205-222. ISSN 0120-1751.

Meta-analysis integrates information from different studies to generate a common response to a determined problem. In the literature, we find several integration methods of results, with the integration method of levels of probability being the more basic and, with a greater complexity, the integration method of the effect size, which uses fixed and random effect models. In this study, we compare the results of two estimation methods of the effect size based on meta-analysis using fixed and random effect models. The measure of the effect size considered here is the odds ratio, due to this measure is frequently used in systematic reviews of several topics of interest in public health, such as heart diseases, laparoscopic colectomy, Parkinson disease, tobacco addiction and uterine cervical cancer. Conclusions of this work indicate the applicability conditions of the analyzed estimators of the odds ratio in function of the size of the population effect, of the variability among studies, of the size of the meta-analysis and of the sample sizes of such studies.

Keywords : Biostatistics; Clinical trials; Effect size; Medicine.

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License