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Recommendation list of books for hypothesis testing?
More precisely, i need list of standard theoretical textbooks that focus on hypothesis testing used in US graduate schools and these books are over 300 pages long.
It seems to me that there are lack of books in this area.
How about Testing Statistical Hypotheses by Lehmann and Romano? The third edition is 786 pages at the PhD statistics level. This book covers both small and large sample theory at a fairly rigorous level. It also introduces some resampling methods, such as the bootstrap. It covers multiple comparisons and goodness of fit testing. Finally, there are over 700 problems.
Electrical engineers study a fair amount of hypothesis testing (as well as estimation) at the graduate level, and there are many textbooks geared towards the applications (signal detection, signal parameter estimation, statistical signal processing) that interest EEs. Many of these books do exceed 300 pages in length (though not all the pages are devoted to hypothesis testing).
Here, for example, is the Books on Reserve in the Library for the Spring 2015 offering of ECE 561: Detection and Estimation Theory at the University of Illinois at Urbana-Champaign
Levy, B.; Principles of Signal Detection and Parameter Estimation
Poor, H. V.; Introduction to Signal Detection and Estimation 2nd ed.
Van Trees, H. L.; Detection, Estimation, and Modulation Theory, Vol. 1
Kay, Steven M.; Fundamentals of Statistical Signal Processing: Estimation Theory v.2
Kay, Steven; Fundamentals of Statistical Signal Processing vol.1
Lehmann, E.L.; Testing Statistical Hypotheses 2nd ed.
Wong, E./Hajek, B.; Stochastic Processes in Engineering Systems
I suspect that only one of these books will be familiar to (or immediately recognizable by) the cognoscenti of this site.