Literature DB >> 7724916

A comparison of methods that characterize pulses in a time series.

D T Mauger1, M B Brown, R H Kushler.   

Abstract

There is general recognition that some glands secrete hormones primarily as a series of pulses. One can generally classify the proposed methods of pulse identification and characterization as either (i) criterion-based, that is, they use a criterion such as a test statistic to identify a rise and/or fall in hormone level within a moving window, or (ii) model-based, that is, they specify a statistical model for the time-varying portion of the signal and estimate its parameters. Using simulated data, we compare and contrast seven criterion-based methods and three model-based methods. The model-based methods perform better in estimating the parameters of interest; they are most effective with the sampling rate chosen so that there are 3-5 samples taken during the half-life of the hormone. At higher sampling rates the methods may overidentify pulses (false positives) and at lower sampling rates they may miss pulses (false negatives), both of which lead to biased estimates for the parameters of the signal.

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Year:  1995        PMID: 7724916     DOI: 10.1002/sim.4780140309

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  9 in total

Review 1.  Pulsatility of Hypothalamo-Pituitary Hormones: A Challenge in Quantification.

Authors:  Daniel M Keenan; Johannes D Veldhuis
Journal:  Physiology (Bethesda)       Date:  2016-01

Review 2.  Motivations and methods for analyzing pulsatile hormone secretion.

Authors:  Johannes D Veldhuis; Daniel M Keenan; Steven M Pincus
Journal:  Endocr Rev       Date:  2008-10-21       Impact factor: 19.871

3.  Modeling associations between latent event processes governing time series of pulsing hormones.

Authors:  Huayu Liu; Nichole E Carlson; Gary K Grunwald; Alex J Polotsky
Journal:  Biometrics       Date:  2017-10-31       Impact factor: 2.571

4.  Modeling diurnal hormone profiles by hierarchical state space models.

Authors:  Ziyue Liu; Wensheng Guo
Journal:  Stat Med       Date:  2015-07-07       Impact factor: 2.373

5.  Updated assays for inhibin B and AMH provide evidence for regular episodic secretion of inhibin B but not AMH in the follicular phase of the normal menstrual cycle.

Authors:  John F Randolph; Siobán D Harlow; Margaret E Helmuth; Huiyong Zheng; Daniel S McConnell
Journal:  Hum Reprod       Date:  2013-12-18       Impact factor: 6.918

6.  Bayesian analysis improves pulse secretion characterization in reproductive hormones.

Authors:  Huayu Liu; Alex J Polotsky; Gary K Grunwald; Nichole E Carlson
Journal:  Syst Biol Reprod Med       Date:  2017-12-29       Impact factor: 3.061

7.  A population-based approach to analyzing pulses in time series of hormone data.

Authors:  K W Horton; N E Carlson; G K Grunwald; M J Mulvahill; A J Polotsky
Journal:  Stat Med       Date:  2017-04-09       Impact factor: 2.373

8.  A Bayesian approach to modeling associations between pulsatile hormones.

Authors:  Nichole E Carlson; Timothy D Johnson; Morton B Brown
Journal:  Biometrics       Date:  2009-06       Impact factor: 2.571

9.  A comparison of methods for analyzing time series of pulsatile hormone data.

Authors:  N E Carlson; K W Horton; G K Grunwald
Journal:  Stat Med       Date:  2013-06-21       Impact factor: 2.373

  9 in total

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