Skip to main content
SpringerLink
Log in

Signal-to-noise ratio (SNR) as a measure of reproducibility: design, estimation, and application

  • Published:
Health Services and Outcomes Research Methodology Aims and scope Submit manuscript

Abstract

This paper proposes the use of signal-to-noise ratio (SNR) as another index of a measurement’s reproducibility. We derive its maximum likelihood estimation and discuss confidence interval construction within the framework of the one-way random effect model. We investigate the validity of the approximate normal confidence interval by Monte-Carlo simulations. The paper also derives the optimal allocation for the number of subject and the number of repeated measurements needed to minimize the variance of the maximum likelihood estimator of the SNR. We discuss efficiency in estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated on two examples: one from MRI data and the other on the WHO immunization coverage data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Ashton, E.A., Takahashi, C., Berg, M.J., Goodman, A., Totterman, S., Ekholm S.: Accuracy and reproducibility of manual and semi automated quantification of MS lesions by MRI. J. Magn. Reson. Imaging 17, 300–308 (2003)

    Article  PubMed  Google Scholar 

  • Berube, Wu: Signal-to-noise ratio and related measures in parameter design optimization: an overview. Sankhya 62, 417–432 (2000)

    Google Scholar 

  • Box, G.: Signal-to-noise ratios, performance criteria, and transformations (with discussion). Technometrics 30, 1–40 (1988)

    Article  Google Scholar 

  • Box, G., Bisgaard, S.: The scientific context of quality improvement. Qual. Prog. 6, 54–61 (1987)

    Google Scholar 

  • Cunningham, I., Shaw, R.: Signal-to-noise optimization of medical imaging system. J. Opt. Soc. Am. A 16, 621–632 (1999)

    Article  Google Scholar 

  • Dunn, G.: Design and analysis of reliability studies. Stat. Methods Med. Res. 1, 123–157 (1992)

    Article  PubMed  CAS  Google Scholar 

  • Fleiss, J.: Design and Analysis of Clinical Experiments. Wiley, New York (1986)

    Google Scholar 

  • Jung, J.A., Coakley, F.V., Vigneron, D.B., Swanson, M.G., Qayyum, A., Weinberg, V., Jones K.D., Carroll, P.R., Kurhanewicz, J.: Prostate depiction at endorectal MR spectroscopic imaging: investigation of a standardized evaluation system. Radiology 233, 701–708 (2004)

    Article  PubMed  Google Scholar 

  • Kendall, M., Stuart, A.: The Advanced Theory of Statistics. Griffin, London (1986)

    Google Scholar 

  • Mian, I., Shoukri, M., Tracy, D.: Maximum likelihood estimation of sibling correlations in the analysis of family data. J. Stat. Plan. Inference 27, 125–141 (1991)

    Article  Google Scholar 

  • Nair, V.: Taguchi’s parameter design: a panel discussion. Technometrics 34, 127–160 (1992)

    Article  Google Scholar 

  • Nair, V., Pregibon, D.: A data analysis strategy for quality engineering experiments. AT&T Tech. J. 65, 73–84 (1986)

    Google Scholar 

  • Rao, S.: Optimization: Theory and Applications. Wiley Eastern Limited, New Delhi (1994)

    Google Scholar 

  • Scheffe, H.: The Analysis of Variance. Wiley, New York (1959)

    Google Scholar 

  • Shoukri, M.M.: Measures of Inter-observer Agreement. Chapman & Hall/CRC Press, Boca Raton, FL (2004)

    Google Scholar 

  • Sim, K.S., Kamel, N.S.: Image signal-to-noise ratio estimation using the autoregressive model. Scanning 26, 135–139 (2004)

    PubMed  CAS  Google Scholar 

  • Srinivasan, S., Ophir, J., Alam, S.K.: Theoretical derivation of SNR, CNR and spatial resolution for a local adaptive strain estimator for elastography. Ultrasound Med. Biol. 30, 1185–1197 (2004)

    Article  PubMed  CAS  Google Scholar 

  • Sukhatme, P., Sukhatme, B., Sukhatme, S., Asok, C.: Sampling Theory of Surveys with Applications. Iowa State University Press, Ames, IA (1984)

    Google Scholar 

  • Taguchi, G.: Introduction to Quality Engineering: Designing Quality into Products and Processes. Kraus International Publications, White Plains, NY (1986)

    Google Scholar 

  • Taguchi, G., Wu, Y.: Introduction to Off-line Quality Control. Central Japan Quality Control Association, Nagaya, Japan (1985)

    Google Scholar 

  • Tukey, J.: Variance of variance components: I. Balanced design. Ann. Math. Stat. 27, 722–736 (1956)

    Article  Google Scholar 

  • World Health Organization, Department of Immunization Vaccines and Biologicals, Vaccine Assessment and Monitoring Team.http://www.who.int/vaccines-surveillance. Accessed 16 Apr 2005

Download references

Author information

Authors and Affiliations

  1. Department of Biostatistics and Epidemiology and Scientific Computing, King Faisal Specialist Hospital & Research Centre, MBC#3, 3354, Riyadh, 11211, Saudi Arabia

    N. Elkum & M. M. Shoukri

  2. Department of Epidemiology and Biostatistics, Schulich School of Medicine, University of Western Ontario, London, Ontario, Canada

    M. M. Shoukri

Authors
  1. N. Elkum
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. M. Shoukri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N. Elkum.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Elkum, N., Shoukri, M.M. Signal-to-noise ratio (SNR) as a measure of reproducibility: design, estimation, and application. Health Serv Outcomes Res Method 8, 119–133 (2008). https://doi.org/10.1007/s10742-008-0030-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10742-008-0030-2

Keywords

Search

Navigation