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Development of Missing Data Imputation Models for Railway Asset Manage by Paul McMahon

In the big data era, huge amounts of data are being collected as a result of the day-to-day operation of organisations. While this increased availability of data brings potential value to organisations and society it also brings challenges. The usefulness or quality of this data and accounting for that quality in data driven decision making is a concern. Relevant problems associated with the quality of data include missing data, incorrect data, and the inclusion of outliers. The specific nature of these problems impacts on how the data is improved and its quality dealt with. Available methods for addressing these problems focus on missing data in sample surveys for smaller datasets. Large datasets require advanced methods for imputation when mining data. Many of the datasets available for monitoring asset condition, and for asset decision analysis, contain missing values. Inappropriate treatment of missing data may cause large errors in the classification of data patterns and inaccurat

Impact of missing outcome data in meta-analyses of lifestyle intervent by Rebecca G Harris, Marijka Batterham et al

High risk of bias associated with missing outcome data (MOD) in meta-analyses (MAs) of the effects of lifestyle interventions during pregnancy on postpartum weight retention (PPWR) casts doubt on whether such interventions can be relied upon as truly effective. This systematic overview of three MAs (19 RCTs), each with high MOD rates in the subset of RCTs included, examined how MOD were addressed in the estimation of summary intervention effects. All MAs reported beneficial and statistically significant intervention effects estimated based on complete case analyses, deemed valid if MOD was missing at random (MAR). Therefore, we conducted sensitivity analyses using pattern mixture models and informative missingness parameters (describing how the outcome in the missing participants may be related to the outcome in the completers), to ascertain the robustness of the estimates to reasonable deviations from the MAR assumption. In plausible scenarios where the response in intervention group

Datagate - Everything2 com

1. Lost in the Post It became apparent on the 20th November that two compact discs containing the personal and financial details of some twenty-five mil.

Experts from the American Institutes for Research to Present at Society for Research on Educational Effectiveness 2021 Conference

Experts from the American Institutes for Research to Present at Society for Research on Educational Effectiveness 2021 Conference
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