The Effects of Imputing the Missing Standard Deviations on the Standard Error of Meta Analysis Estimates |
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| Authors: | Nik Ruzni Nik Idris Chris Robertson |
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| Institution: | 1. Department of Computational and Theoretical Sciences , International Islamic University Malaysia , Kuantan, Pahang Malaysia ruzni@iiu.edu.my;3. Department of Statistics and Modelling Sciences , University of Strathclyde , Glasgow, Scotland;4. Health Protection Scotland , Glasgow, Scotland |
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| Abstract: | A common problem in the meta analysis of continuous data is that some studies do not report sufficient information to calculate the standard deviation (SDs) of the treatment effect. One of the approaches in handling this problem is through imputation. This article examines the empirical implications of imputing the missing SDs on the standard error (SE) of the overall meta analysis estimate. The simulation results show that if the SDs are missing under Missing Completely at Random and Missing at Random mechanism, imputation is recommended. With non random missing, imputation can lead to overestimation of the SE of the estimate. |
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| Keywords: | Imputation MCAR Meta analysis Missing SDs Standard error |
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