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Bernhard Spangl, Norbert Kaiblinger, Peter Ruckdeschel & Dieter Rasch. (2023) Minimal sample size in balanced ANOVA models of crossed, nested, and mixed classifications. Communications in Statistics - Theory and Methods 52:6, pages 1728-1743.
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Stephen M. Scariano & James M. Davenport. (1986) A four-moment approach and other practical solutions to the behrens-f1sher problem. Communications in Statistics - Theory and Methods 15:5, pages 1467-1505.
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KennethS. Kaminsky. (1974) Confidence Intervals and Tests for Two Exponential Scale Parameters Based On Order Statistics in Compressed Samples. Technometrics 16:2, pages 251-254.
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KennethS. Kaminsky & PaulI. Nelson. (1974) Prediction Intervals for the Exponential Distribution Using Subsets of the Data. Technometrics 16:1, pages 57-59.
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Jingchun Xie & Chengli Huang. (2023) On the formation of thrust fault-related landforms on Mercury: The key parameters controlling the mechanical structure of the lithosphere. Icarus 401, pages 115594.
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K Nisa, N Hamsyiah, M Usman & Warsono. (2020) Analysis of variance for strip plot design with missing values: bias correction of the mean squares. Journal of Physics: Conference Series 1524:1, pages 012049.
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Rohan Nagare, Mark S. Rea, Barbara Plitnick & Mariana G. Figueiro. (2019) Nocturnal Melatonin Suppression by Adolescents and Adults for Different Levels, Spectra, and Durations of Light Exposure. Journal of Biological Rhythms 34:2, pages 178-194.
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Math JJM Candel & Gerard JP van Breukelen. (2014) Sample size calculation for treatment effects in randomized trials with fixed cluster sizes and heterogeneous intraclass correlations and variances. Statistical Methods in Medical Research 24:5, pages 557-573.
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James M Davenport & Brian Schlain. (2000) Testing Claimed Minimal Detectable Concentrations of in Vitro Medical Diagnostic Devices. Clinical Chemistry 46:10, pages 1669-1680.
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J. M. Davenport & J. T. Webster. (1975) The Behrens-Fisher problem, an old solution revisited. Metrika 22:1, pages 47-54.
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Umesh D. Naik. (1974) On Some Procedures for Testing a Linear Relation Among Variances. Journal of the Royal Statistical Society Series B: Statistical Methodology 36:2, pages 243-257.
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