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Email

clloyd@unimelb.edu.au

Credentials


Position
Honorary (Professorial Fellow)
Department of Business Administration
Education
PhD
University of Melbourne
ORCID

0000-0001-5745-1951

Prof Chris Lloyd

Honorary (Professorial Fellow)
Department of Business Administration

132 Scholarly works
1 Projects

HIGHLIGHTS

  • 2025

    Journal article

    A Primer of Quasi-Exact Tests for Randomized Clinical Trials with Binary Endpoints
    DOI: 10.1080/19466315.2024.2402899
  • 2024

    Journal article

    Exact samples sizes for clinical trials subject to size and power constraints
    DOI: 10.1111/anzs.12424
  • 2022

    Journal article

    Exact confidence limits compatible with the result of a sequential trial
    DOI: 10.1016/j.jspi.2021.07.014
  • 2021

    Journal article

    A comprehensive open-source library for exact required sample size in binary clinical trials
    DOI: 10.1016/j.cct.2021.106491
  • 2021

    Journal article

    Exact confidence limits after a group sequential single arm trial
    DOI: 10.1002/sim.8909
  • 2020

    Journal article

    Reply to Drs Almendra‐Arao and Sotres‐Ramos regarding Barnard's concept of convexity and possible extensions
    DOI: 10.1002/pst.1997
  • 2020

    Journal article

    Growing rich without growing old: the impact of internal migration in China
    DOI: 10.1080/17441730.2020.1750187
Chris Lloyd

RECENT SCHOLARLY WORKS

  • 2019

    Journal article

    A scenario analysis of future Hong Kong age and labour force profiles and its implications
    DOI: 10.1111/rssa.12428
  • 2019

    Journal article

    Tests for noninferiority trials with binomial endpoints: A guide to modern and quasi-exact methods for biomedical researchers
    DOI: 10.1002/pst.1929
  • 2018

    Journal article

    An exhaustive numerical assessment of alternative unconditional tests of a binary treatment effect
    DOI: 10.1080/00949655.2018.1452018

RECENT PROJECTS

  • 2003

    Research Grant

    New and Computationally Feasible Methods for Constructing Efficient and Exact Confidence Limits From Count Data

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