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SPMM

eagle-i ID

http://harvard.eagle-i.net/i/0000013a-d1da-5038-0802-e06e80000000

Resource Type

  1. Algorithmic software component

Properties

  1. Resource Description
    "This macro fits the following model to longitudinal Gaussian data: Yij = Xij*beta + f(tij) + Zij*bi + Ui(tij) + esp(ij), where beta is parametric fixed effects, f(.) is a smooth function, bi is random effects, Ui(.) is a Gaussian process, esp(ij) is the measurement error. Maximum penalized likelihood was used to estimate the beta and f(.), while smoohting parameter and the parameters in the variance matrix are estimated by REML method, which treats f(.) as an integrated Wiener process."
  2. Additional Name
    SAS Macro for semiparametric stochastic mixed models
  3. Used by
    Lin Laboratory
  4. Version
    1.0
  5. Software purpose
    Statistical analysis and modeling objective
  6. Related Publication or Documentation
    Semiparametric stochastic mixed models for longitudinal data
  7. Website(s)
    http://www.hsph.harvard.edu/xlin/dat/spmm.txt
  8. Website(s)
    http://www.hsph.harvard.edu/xlin/software.html#spmm
  9. Developed by
    Zhang, Daowen
  10. Coded in
    SAS
 
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Provenance Metadata About This Resource Record

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