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  1. 2 Statistics in Transition new series

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  1. 2 Longford N. T.

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  1. 1 2021

  2. 1 2015

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Unreported standard errors in meta-analysis

100%
Longford N. T.
Statistics in Transition new series
|
2021
|
vol. 22
|
issue 4
1-17
EN
A study that would otherwise be eligible is commonly excluded from a meta-analysis when the standard error of its treatment-effect estimator, or the estimate of the variance of the outcomes, is not reported and cannot be recovered from the available information. This is wasteful when the estimate of the treatment effect is reported. We assess the loss of information caused by this practice and explore methods of imputation for the missing variance. The methods are illustrated on two sets of examples, one constructed specifically for illustration and another based on a published systematic review.
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Policy-oriented inference and the analyst-client cooperation. An example from small-area statistics

86%
Longford N. T.
Statistics in Transition new series
|
2015
|
vol. 16
|
issue 1
65–82
EN
We show on an application to small-area statistics that efficient estimation is not always conducive to good policy decisions because the established inferential procedures have no capacity to incorporate the priorities and preferences of the policy makers and the related consequences of incorrect decisions. A method that addresses these deficiencies is described. We argue that elicitation of the perspectives of the client (sponsor) and their quantification are essential elements of the analysis because different estimators (decisions) are appropriate for different perspectives. An example of planning an intervention in a developing country’s districts with high rate of illiteracy is described. The example exposes the deficiencies of the general concept of efficiency and shows that the criterion for the quality of an estimator has to be formulated specifically for the problem at hand. In the problem, the established small-area estimators perform poorly because the minimum mean squared error is an inappropriate criterion.
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