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Data Processing for Longitudinal Studies

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  • H. Goldstein

Abstract

An account is given of some data‐processing problems which arise in longitudinal studies. Computer programs which have been developed to deal efficiently with such data are described.

Suggested Citation

  • H. Goldstein, 1970. "Data Processing for Longitudinal Studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 19(2), pages 145-151, June.
    • Handle: RePEc:bla:jorssc:v:19:y:1970:i:2:p:145-151
    DOI: 10.2307/2346544
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    Cited by:

    1. Rössler, E. & Sokolov, A.P. & Eiermann, P. & Warschewske, U., 1993. "Dynamical phase transition in simple supercooled liquids and polymers - an NMR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 201(1), pages 237-256.
    2. Wahnström, Göran & Lewis, Laurent J., 1993. "Molecular dynamics simulation of a molecular glass at intermediate times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 201(1), pages 150-156.
    3. T. J. Cole, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Harvey Goldstein and his time at the Institute of Child Health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 748-752, July.
    4. Charlotte S C Woolley & Ian G Handel & B Mark Bronsvoort & Jeffrey J Schoenebeck & Dylan N Clements, 2020. "Is it time to stop sweeping data cleaning under the carpet? A novel algorithm for outlier management in growth data," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-21, January.
    5. Fischer, E.W., 1993. "Light scattering and dielectric studies on glass forming liquids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 201(1), pages 183-206.

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