Sensitivity analysis for causal inference using inverse probability weighting

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Inferring causal effects from longitudinal repeated measures data has high relevance to a number of areas of research, including economics, social sciences and epidemiology. In observational studies in particular, the treatment receipt mechanism is typically not under the control of the investigator; it can depend on various factors, including the outcome of interest. This results in differenti...

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Inverse probability weighting.

Statistical analysis usually treats all observations as equally important. In some circumstances, however, it is appropriate to vary the weight given to different observations. Well known examples are in meta-analysis, where the inverse variance (precision) weight given to each contributing study varies, and in the analysis of clustered data. Differential weighting is also used when different p...

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ژورنال

عنوان ژورنال: Biometrical Journal

سال: 2011

ISSN: 0323-3847

DOI: 10.1002/bimj.201100042