Experimental Design and Mathematical Modelling Methods for the Study of Anthelmintic Resistance in UK Livestock Populations

Research output: ThesisDoctoral Thesis

Abstract

The Faecal Egg Count Reduction Test (FECRT) is the most widely used field-based method for estimating anthelmintic efficacy and as an indicator of anthelmintic resistant nematodes in cattle. In this thesis, statistical aspects such as the analysis of cattle faecal egg count (FEC) data and the identification of statistically robust experimental study designs for the FECRT, are examined. Using field study cattle FECRT data, the validity of current guidelines on parameter estimates for evaluating percentage estimates and confidence intervals (CIs), were assessed. For FECs obtained using sensitive counting techniques, percentage estimates are recommended to be evaluated using arithmetic group means. For FECs obtained by less sensitive counting techniques, the maximum likelihood estimator of zero inflated distributions is recommended when evaluating percentage estimates. It would not be recommended however, to use CIs that assume FECs to be normal, and it is therefore recommended that relevant intervals for percentage estimates be obtained using a Bootstrap or Bayesian framework. A simulation study was conducted using Bootstrap methodology to assess the coverage probability of 95% percentile intervals, associated with different percentage estimates. The coverage was considered for scenarios involving various diagnostic sensitivities, treatment group sizes and classifications of pre-treatment group means. Very few scenarios consisted of 95% Bootstrapped percentile intervals with adequate coverage probabilities. A further simulation study was then carried out with Bayesian methodologies being employed. The accuracy of percentage estimates was examined under the scenarios described above. In the majority of scenarios: in order to obtain the most accurate percentage estimates, one would only need to adopt a paired study design involving a positive treatment group.
LanguageEnglish
QualificationPhD
Awarding Institution
  • University Of Strathclyde
Supervisors/Advisors
  • Kelly, Louise, Supervisor
  • Robertson, Charles, Supervisor
Thesis sponsors
Award date10 Jan 2019
Place of PublicationGlasgow
Publisher
Publication statusPublished - 10 Jan 2019

Fingerprint

Experimental design
Modeling Method
Mathematical Modeling
Design of experiments
Agriculture
Percentage
Estimate
Scenarios
Count
Maximum likelihood
Percentile
Coverage Probability
Bootstrap
Interval
Confidence interval
Counting
Simulation Study
Arithmetic Groups
Distribution of Zeros
Field Study

Keywords

  • experimental design
  • mathematical modelling
  • UK
  • livestock

Cite this

@phdthesis{927ff56b503e4bd3b29369cd72e03ff0,
title = "Experimental Design and Mathematical Modelling Methods for the Study of Anthelmintic Resistance in UK Livestock Populations",
abstract = "The Faecal Egg Count Reduction Test (FECRT) is the most widely used field-based method for estimating anthelmintic efficacy and as an indicator of anthelmintic resistant nematodes in cattle. In this thesis, statistical aspects such as the analysis of cattle faecal egg count (FEC) data and the identification of statistically robust experimental study designs for the FECRT, are examined. Using field study cattle FECRT data, the validity of current guidelines on parameter estimates for evaluating percentage estimates and confidence intervals (CIs), were assessed. For FECs obtained using sensitive counting techniques, percentage estimates are recommended to be evaluated using arithmetic group means. For FECs obtained by less sensitive counting techniques, the maximum likelihood estimator of zero inflated distributions is recommended when evaluating percentage estimates. It would not be recommended however, to use CIs that assume FECs to be normal, and it is therefore recommended that relevant intervals for percentage estimates be obtained using a Bootstrap or Bayesian framework. A simulation study was conducted using Bootstrap methodology to assess the coverage probability of 95{\%} percentile intervals, associated with different percentage estimates. The coverage was considered for scenarios involving various diagnostic sensitivities, treatment group sizes and classifications of pre-treatment group means. Very few scenarios consisted of 95{\%} Bootstrapped percentile intervals with adequate coverage probabilities. A further simulation study was then carried out with Bayesian methodologies being employed. The accuracy of percentage estimates was examined under the scenarios described above. In the majority of scenarios: in order to obtain the most accurate percentage estimates, one would only need to adopt a paired study design involving a positive treatment group.",
keywords = "experimental design, mathematical modelling, UK, livestock",
author = "Johnathan Love",
year = "2019",
month = "1",
day = "10",
language = "English",
publisher = "University of Strathclyde",
school = "University Of Strathclyde",

}

Experimental Design and Mathematical Modelling Methods for the Study of Anthelmintic Resistance in UK Livestock Populations. / Love, Johnathan.

Glasgow : University of Strathclyde, 2019. 331 p.

Research output: ThesisDoctoral Thesis

TY - THES

T1 - Experimental Design and Mathematical Modelling Methods for the Study of Anthelmintic Resistance in UK Livestock Populations

AU - Love, Johnathan

PY - 2019/1/10

Y1 - 2019/1/10

N2 - The Faecal Egg Count Reduction Test (FECRT) is the most widely used field-based method for estimating anthelmintic efficacy and as an indicator of anthelmintic resistant nematodes in cattle. In this thesis, statistical aspects such as the analysis of cattle faecal egg count (FEC) data and the identification of statistically robust experimental study designs for the FECRT, are examined. Using field study cattle FECRT data, the validity of current guidelines on parameter estimates for evaluating percentage estimates and confidence intervals (CIs), were assessed. For FECs obtained using sensitive counting techniques, percentage estimates are recommended to be evaluated using arithmetic group means. For FECs obtained by less sensitive counting techniques, the maximum likelihood estimator of zero inflated distributions is recommended when evaluating percentage estimates. It would not be recommended however, to use CIs that assume FECs to be normal, and it is therefore recommended that relevant intervals for percentage estimates be obtained using a Bootstrap or Bayesian framework. A simulation study was conducted using Bootstrap methodology to assess the coverage probability of 95% percentile intervals, associated with different percentage estimates. The coverage was considered for scenarios involving various diagnostic sensitivities, treatment group sizes and classifications of pre-treatment group means. Very few scenarios consisted of 95% Bootstrapped percentile intervals with adequate coverage probabilities. A further simulation study was then carried out with Bayesian methodologies being employed. The accuracy of percentage estimates was examined under the scenarios described above. In the majority of scenarios: in order to obtain the most accurate percentage estimates, one would only need to adopt a paired study design involving a positive treatment group.

AB - The Faecal Egg Count Reduction Test (FECRT) is the most widely used field-based method for estimating anthelmintic efficacy and as an indicator of anthelmintic resistant nematodes in cattle. In this thesis, statistical aspects such as the analysis of cattle faecal egg count (FEC) data and the identification of statistically robust experimental study designs for the FECRT, are examined. Using field study cattle FECRT data, the validity of current guidelines on parameter estimates for evaluating percentage estimates and confidence intervals (CIs), were assessed. For FECs obtained using sensitive counting techniques, percentage estimates are recommended to be evaluated using arithmetic group means. For FECs obtained by less sensitive counting techniques, the maximum likelihood estimator of zero inflated distributions is recommended when evaluating percentage estimates. It would not be recommended however, to use CIs that assume FECs to be normal, and it is therefore recommended that relevant intervals for percentage estimates be obtained using a Bootstrap or Bayesian framework. A simulation study was conducted using Bootstrap methodology to assess the coverage probability of 95% percentile intervals, associated with different percentage estimates. The coverage was considered for scenarios involving various diagnostic sensitivities, treatment group sizes and classifications of pre-treatment group means. Very few scenarios consisted of 95% Bootstrapped percentile intervals with adequate coverage probabilities. A further simulation study was then carried out with Bayesian methodologies being employed. The accuracy of percentage estimates was examined under the scenarios described above. In the majority of scenarios: in order to obtain the most accurate percentage estimates, one would only need to adopt a paired study design involving a positive treatment group.

KW - experimental design

KW - mathematical modelling

KW - UK

KW - livestock

M3 - Doctoral Thesis

PB - University of Strathclyde

CY - Glasgow

ER -