Bayesian Analysis of a 2 × 2 Contingency Table with Both Completely and Partially Cross-Classified Data

1985 ◽  
Vol 10 (1) ◽  
pp. 31 ◽  
Author(s):  
Philip J. Smith ◽  
Sung C. Choi ◽  
Erdogan Gunel
1985 ◽  
Vol 10 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Philip J. Smith ◽  
Sung C Choi ◽  
Erdogan Gunel

A frequently used experimental design is one in which the experimental units are measured twice (e.g., under different test conditions). When the response variable is dichotomous, the equality of the two proportions is usually assessed by a test due to McNemar (1947) . However, in addition to obtaining this complete data where two responses are available for each unit, incomplete data may be available also: In this case observations are available on the first response alone for some units and additional observations are available on the second response alone for other units. In this paper Bayesian methods are presented for estimating and testing hypotheses regarding the two success probabilities in light of both the complete and incomplete data. A method by which the prior distribution may be assessed is sketched and a numerical example to illustrate the method is presented.


2017 ◽  
Vol 27 (11) ◽  
pp. 3411-3419 ◽  
Author(s):  
Yan Lin ◽  
Stuart R Lipsitz ◽  
Debajyoti Sinha ◽  
Garrett Fitzmaurice ◽  
Steven Lipshultz

Altham (Altham PME. Exact Bayesian analysis of a 2 × 2 contingency table, and Fisher’s “exact” significance test. J R Stat Soc B 1969; 31: 261–269) showed that a one-sided p-value from Fisher’s exact test of independence in a 2 × 2 contingency table is equal to the posterior probability of negative association in the 2 × 2 contingency table under a Bayesian analysis using an improper prior. We derive an extension of Fisher’s exact test p-value in the presence of missing data, assuming the missing data mechanism is ignorable (i.e., missing at random or completely at random). Further, we propose Bayesian p-values for a test of independence in a 2 × 2 contingency table with missing data using alternative priors; we also present results from a simulation study exploring the Type I error rate and power of the proposed exact test p-values. An example, using data on the association between blood pressure and a cardiac enzyme, is presented to illustrate the methods.


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