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metamiss: Meta-analysis with missing data


  • Ian White

    () (MRC Biostatistics Unit, Cambridge)

  • Julian Higgins

    (MRC Biostatistics Unit, Cambridge)


A new command metamiss performs meta-analysis when some or all studies have missing data. A variety of assumptions are available, including missing-at-random, missing=failure, worst and best cases, and incorporating a user-specified prior distribution for the degree of informative missingness. This is joint work with Julian Higgins.

Suggested Citation

  • Ian White & Julian Higgins, 2007. "metamiss: Meta-analysis with missing data," United Kingdom Stata Users' Group Meetings 2007 09, Stata Users Group.
  • Handle: RePEc:boc:usug07:09

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    References listed on IDEAS

    1. Roger Newson, 2006. "Confidence intervals for rank statistics: Percentile slopes, differences, and ratios," Stata Journal, StataCorp LP, vol. 6(4), pages 497-520, December.
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