Test and estimation in binary data analysis under an incomplete block crossover design

To improve the power of a parallel groups design and reduce the time length of a crossover trial, we may consider an incomplete block crossover design. Under a distribution-free random effects logistic regression model, we derive an exact test and a Mantel-Haenszel Type of summary test procedure for testing non-equality in binary data when comparing three treatments. We employ Monte Carlo simulation to evaluate the performance of these test procedures. We find that both test procedures developed here can perform well in a variety of situations. We use the data taken as a part of the crossover trial comparing the low and high doses of an analgesic with a placebo for the relief of pain in primary dysmenorrhea to illustrate the use of the proposed test procedures.

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Estimation of the treatment effect under an incomplete block crossover design in binary data – A conditional likelihood approach

Statistical Methods in Medical Research ◽

10.1177/0962280215595434 ◽

2015 ◽

Vol 26 (5) ◽

pp. 2197-2209 ◽

Cited By ~ 6

Author(s):

Kung-Jong Lui

Keyword(s):

Treatment Effect ◽

Binary Data ◽

Crossover Design ◽

Conditional Likelihood ◽

Incomplete Block ◽

Likelihood Approach

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Binary Data Analysis

Molecular Tools for Screening Biodiversity ◽

10.1007/978-94-009-0019-6_59 ◽

1998 ◽

pp. 329-331 ◽

Cited By ~ 1

Author(s):

Michael W. Bruford ◽

Mark A. Beaumont

Keyword(s):

Data Analysis ◽

Binary Data

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Test Equality between Three Treatments under an Incomplete Block Crossover Design

Journal of Biopharmaceutical Statistics ◽

10.1080/10543406.2014.920867 ◽

2014 ◽

Vol 25 (4) ◽

pp. 795-811 ◽

Cited By ~ 5

Author(s):

Kung-Jong Lui

Keyword(s):

Crossover Design ◽

Incomplete Block

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Notes on estimation in Poisson frequency data under an incomplete block crossover design

Statistical Methodology ◽

10.1016/j.stamet.2016.01.007 ◽

2016 ◽

Vol 32 ◽

pp. 53-62 ◽

Cited By ~ 2

Author(s):

Kung-Jong Lui

Keyword(s):

Crossover Design ◽

Incomplete Block ◽

Frequency Data

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Markov chain models for multivariate repeated binary data analysis

Communications in Statistics - Simulation and Computation ◽

10.1080/03610910008813651 ◽

2000 ◽

Vol 29 (4) ◽

pp. 1001-1019

Author(s):

Wei Tian ◽

Stewart J. Anderson

Keyword(s):

Markov Chain ◽

Data Analysis ◽

Binary Data ◽

Markov Chain Models

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Behavioral Testing of Antidepressant Compounds: An Analysis of Crossover Design for Correlated Binary Data

Biometrical Journal ◽

10.1002/bimj.200410130 ◽

2005 ◽

Vol 47 (3) ◽

pp. 286-298

Author(s):

Ziv Shkedy ◽

Veerle Vandersmissen ◽

Geert Molenberghs ◽

Hansfried Van Craenendonck ◽

Nancy Aerts ◽

...

Keyword(s):

Binary Data ◽

Crossover Design ◽

Behavioral Testing ◽

Correlated Binary Data

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A reproducible robust likelihood approach to inference about marginal characteristics of binary data in paired settings

Statistical Methods in Medical Research ◽

10.1177/0962280219832232 ◽

2019 ◽

Vol 29 (1) ◽

pp. 282-292

Author(s):

Tsung-Shan Tsou

Keyword(s):

Data Analysis ◽

Binary Data ◽

Real Data ◽

Paired Data ◽

Real Data Analysis ◽

Marginal Homogeneity ◽

New Strategy ◽

Likelihood Approach ◽

Robust Likelihood ◽

Joint Probabilities

We introduce a robust likelihood approach to inference about marginal distributional characteristics for paired data without modeling correlation/joint probabilities. This method is reproducible in that it is applicable to paired settings with various sizes. The virtue of the new strategy is elucidated via testing marginal homogeneity in paired triplet scenario. We use simulations and real data analysis to demonstrate the merit of our robust likelihood methodology.

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