Abstract
The present chapter has a somewhat different character from the preceding ones. It is concerned with problems regarding the proper choice and interpretation of tests and confidence procedures, problems which—despite a large literature—have not found a definitive solution. The discussion will thus be more tentative than in earlier chapters, and will focus on conceptual aspects more than on technical ones. Consider the situation in which either the experiment \({\mathcal {E}}\) of observing a random quantity X with density \(p_{\theta }\) (with respect to \(\mu \)) or the experiment \({\mathcal {F}}\) of observing an X with density \(q_{\theta }\) (with respect to \(\nu \)) is performed with probability p and \(q=1-p\) respectively.
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Notes
- 1.
A distinction between experimental mixtures and the present situation, relying on aspects outside the model, is discussed by Basu (1964) and Kalbfleisch (1975).
- 2.
The family \({\mathcal {P}}\) is then a group family; see Lehmann and Casella (1998), Section 1.3.
- 3.
For a more detailed discussion of equivariance, see Lehmann and Casella (1998), Chapter 3.
- 4.
So far, nonexistence has not been proved. It seems likely that a proof can be obtained by the methods of Unni (1978).
- 5.
For other implications of this requirement, called the weak conditionality principle, see Birnbaum (1962) and Berger and Wolpert (1988).
- 6.
For a discussion of this issue, see Buehler (1959), Robinson (1976, 1979a), and Bondar (1977).
- 7.
Randomized and nonrandomized conditioning is interpreted in terms of betting strategies by Buehler (1959) and Pierce (1973).
- 8.
Fisher’s contributions to this topic are discussed in Savage (1976, pp. 467–469).
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Lehmann, E.L., Romano, J.P. (2022). Conditional Inference. In: Testing Statistical Hypotheses. Springer Texts in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-70578-7_10
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