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Connection

David Hoaglin to Algorithms

This is a "connection" page, showing publications David Hoaglin has written about Algorithms.
Connection Strength

0.894
  1. Kulinskaya E, Hoaglin DC. On the Q statistic with constant weights in meta-analysis of binary outcomes. BMC Med Res Methodol. 2023 06 21; 23(1):146.
    View in: PubMed
    Score: 0.580
  2. Bakbergenuly I, Hoaglin DC, Kulinskaya E. On the Q statistic with constant weights for standardized mean difference. Br J Math Stat Psychol. 2022 11; 75(3):444-465.
    View in: PubMed
    Score: 0.132
  3. Kulinskaya E, Hoaglin DC, Bakbergenuly I, Newman J. A Q statistic with constant weights for assessing heterogeneity in meta-analysis. Res Synth Methods. 2021 Nov; 12(6):711-730.
    View in: PubMed
    Score: 0.127
  4. Bakbergenuly I, Hoaglin DC, Kulinskaya E. Methods for estimating between-study variance and overall effect in meta-analysis of odds ratios. Res Synth Methods. 2020 May; 11(3):426-442.
    View in: PubMed
    Score: 0.029
  5. Bakbergenuly I, Hoaglin DC, Kulinskaya E. Pitfalls of using the risk ratio in meta-analysis. Res Synth Methods. 2019 Sep; 10(3):398-419.
    View in: PubMed
    Score: 0.027
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.