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Relationship between Derivatives of the Observed and Full Loglikelihoods and Application to Newton-Raphson Algorithm

Author

Listed:
  • Commenges Daniel

    (INSERM)

  • Rondeau Virginie

    (INSERM)

Abstract

In the case of incomplete data we give general relationships between the first and second derivatives of the loglikelihood relative to the full and the incomplete observation set-ups. In the case where these quantities are easy to compute for the full observation set-up we propose to compute their analogue for the incomplete observation set-up using the above mentioned relationships: this involves numerical integrations. Once we are able to compute these quantities, Newton-Raphson type algorithms can be applied to find the maximum likelihood estimators, together with estimates of their variances. We detail the application of this approach to parametric multiplicative frailty models and we show that the method works well in practice using both a real data and a simulated example. The proposed algorithm outperforms a Newton-Raphson type algorithm using numerical derivatives.

Suggested Citation

  • Commenges Daniel & Rondeau Virginie, 2006. "Relationship between Derivatives of the Observed and Full Loglikelihoods and Application to Newton-Raphson Algorithm," The International Journal of Biostatistics, De Gruyter, vol. 2(1), pages 1-28, March.
    • Handle: RePEc:bpj:ijbist:v:2:y:2006:i:1:n:4
    DOI: 10.2202/1557-4679.1010
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    Cited by:

    1. J. Guedj & R. Thiébaut & D. Commenges, 2007. "Maximum Likelihood Estimation in Dynamical Models of HIV," Biometrics, The International Biometric Society, vol. 63(4), pages 1198-1206, December.

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