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Step-up testing procedure for multiple comparisons with a control for a latent variable model with ordered

Yueqiong Lin1, Koon Shing Kwong, Siu Hung Cheung

  • 1School of Economics and Management, Fuzhou University, Fuzhou, China.

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A new step-up procedure using latent normal models improves statistical testing in clinical trials with ordered categorical data. This method enhances accuracy and provides sample size calculation for robust study design.

Keywords:
familywise error ratelatent normal variable modelordered categorical responsesample size determination

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Area of Science:

  • Biostatistics
  • Clinical Trial Methodology
  • Statistical Inference

Background:

  • Clinical studies frequently involve multiple treatment comparisons with ordered categorical outcomes.
  • The proportional odds logistic regression model is a common but potentially flawed analysis approach.
  • Violation of the proportional odds assumption can inflate the familywise type I error rate, compromising clinical findings.

Purpose of the Study:

  • To introduce a novel step-up testing procedure for analyzing ordered categorical data in clinical trials.
  • To address the limitations of existing methods when the proportional odds assumption is violated.
  • To develop a sample size determination algorithm based on the proposed procedure.

Main Methods:

  • Development of a step-up procedure leveraging the correlation structure of test statistics within a latent normal model framework.
  • Comparison with existing single-step and stepwise testing procedures.
  • A simulation study was conducted to evaluate the performance of the proposed method.
  • Derivation of an algorithm for sample size and allocation determination.

Main Results:

  • The proposed step-up procedure demonstrated superior performance compared to all existing testing procedures in simulation studies.
  • The method effectively controls the familywise type I error rate.
  • The derived algorithm facilitates pre-trial sample size planning for desired statistical power.

Conclusions:

  • The novel step-up procedure offers a more robust and accurate statistical approach for clinical trials with ordered categorical responses.
  • This method provides a reliable tool for sample size determination, enhancing clinical trial design and validity.
  • The approach is illustrated with a practical clinical example.