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Link to original content: http://pubmed.ncbi.nlm.nih.gov/25031857/
Detecting and Accommodating Outliers in Meta-Analysis for Evaluating Effect of Albendazole on Ascaris lumbricoides Infection - PubMed Skip to main page content
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. 2014 May;16(5):e17648.
doi: 10.5812/ircmj.17648. Epub 2014 May 5.

Detecting and Accommodating Outliers in Meta-Analysis for Evaluating Effect of Albendazole on Ascaris lumbricoides Infection

Hamid Alavi Majd  1 , Khadijeh Najafi Ghobadi  1 , Alireza Akbarzadeh Baghban  2 , Nayebali Ahmadi  3 , Elham Sajjadi  4
Affiliations

Detecting and Accommodating Outliers in Meta-Analysis for Evaluating Effect of Albendazole on Ascaris lumbricoides Infection

Hamid Alavi Majd et al. Iran Red Crescent Med J. 2014 May.

Abstract

Background: Meta-analysis is a statistical technique in which the results of two or more independent studies, with similar objectives, are mathematically combined in order to improve the reliability of the results. The outliers, which may exist even in random models, can affect the validity and strength of meta-analysis results.

Objectives: The current study uses "random effects variance shift model" to evaluate and correct the outliers in performing a meta-analysis study of the effect of albendazole in treating patients with Ascaris lumbricoides infection.

Patients and methods: The study used data from 14 clinical trials; each article was composed of two groups, a treatment group and a placebo group. These articles compared the effect of single dose intakes of 400 mg albendazole in treating two groups of patients with Ascaris lumbricoides infection. The articles were published in a number of internationally indexed journals between 1983 to 2013. For both groups in each article, the total number of participants, the number of those with Ascaris lumbricoides infection, and the number of those recovered following the intake of albendazole were identified and recorded. The relative risk (RR) and variance were computed for each article individually. Then, using meta-analysis, the RR was computed for all the articles together. In order to detect outliers the "random effects variance shift model" and "likelihood ratio test" (LRT) were used. Adopting the bootstrap method, the accuracy rates for sampling distribution of the tests, which were used for multiple testing, were obtained and the relevant graphs were depicted. For data analysis, STATA and R software were used.

Results: According to meta-analysis results, the estimate for RR was 2.91, with a 95% confidence interval of 2.6 to 3.25. According to the method used in this study, three articles (articles number 4, 7, and 12) were outliers and, as such, they were detected in the graphs.

Conclusions: We can detect and accommodate outliers in meta-analysis by using random effects variance shift model and likelihood ratio test.

Keywords: Albendazole; Ascaris lumbricoides; Meta-Analysis; Outliers; Random Effects Variance Shift Model.

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Figures

Figure 1.
Figure 1.. Forest Plot Diagram Used to Investigate the Effect of Albendazole on Patients With Ascaris lumbricoides Infection
Figure 2.
Figure 2.. Random Effect Variance Shift Outlier Model Statistics Plotted Against Study Number for the Effect of Albendazole on Patients With Ascaris lumbricoides Infection
(2a) Variance shift estimates.ω2j; (2b) random effect variance estimates τˆ2; (2c) estimates for treatment effect µˆ; (2d) likelihood ratio test statistics for a RVSOM for study j, plotted against study number.
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References

    1. Whitehead A. Meta-analysis of controlled clinical trials. John Wiley & Sons; 2003.
    1. Hedges LV, Olkin I, Statistiker M. Statistical methods for meta-analysis. New York: Academic Press; 1985.
    1. Iyengar S, Greenhouse JB. Sensitivity Analysis and Diagnostics. Handbook of Research Synthesis and Meta-Analysis. 2009. pp. 417–33.
    1. Wang MC, Bushman BJ. Using the normal quantile plot to explore meta-analytic data sets. Psychol Methods. 1998;3(1):46. doi: 10.1037/1082-989X.3.1.46. - DOI
    1. Shadish WR, Haddock CK. Combining estimates of effect size. The handbook of research synthesis and meta-analysis. 2009. pp. 257–77.

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