1,720,964 research outputs found
Supplementary_File_1 – Supplemental material for The cluster randomized crossover trial: The effects of attrition in the AB/BA design and how to account for it in sample size calculations
No full textSupplemental material, Supplementary_File_1 for The cluster randomized crossover trial: The effects of attrition in the AB/BA design and how to account for it in sample size calculations by Mirjam Moerbeek in Clinical Trials</p
Supplementary_File_2 – Supplemental material for The cluster randomized crossover trial: The effects of attrition in the AB/BA design and how to account for it in sample size calculations
No full textSupplemental material, Supplementary_File_2 for The cluster randomized crossover trial: The effects of attrition in the AB/BA design and how to account for it in sample size calculations by Mirjam Moerbeek in Clinical Trials</p
sj-docx-1-smm-10.1177_09622802211037066 - Supplemental material for Optimal allocation to treatments in a sequential multiple assignment randomized trial
No full textSupplemental material, sj-docx-1-smm-10.1177_09622802211037066 for Optimal allocation to treatments in a sequential multiple assignment randomized trial by Andrea Morciano and Mirjam Moerbeek in Statistical Methods in Medical Research</p
Optimal sample sizes for the incomplete within–subject design with scenario 1.
No full textOptimal sample sizes for the incomplete within–subject design with scenario 1.</p
Efficiency of the incomplete within–subject design relative to the complete within–subject design.
No full textEfficiency of the incomplete within–subject design relative to the complete within–subject design.</p
Efficiency of uniform allocation relative to optimal allocation.
No full textEfficiency of uniform allocation relative to optimal allocation.</p
Optimal sample sizes as a function of the parameter <i>λ</i><sub>1</sub>.
No full textOptimal sample sizes as a function of the parameter λ1.</p
Optimal sample sizes for the incomplete within–subject design with scenario 2.
No full textOptimal sample sizes for the incomplete within–subject design with scenario 2.</p
Data_Sheet_1_Sample size determination for Bayesian ANOVAs with informative hypotheses.pdf
No full textResearchers can express their expectations with respect to the group means in an ANOVA model through equality and order constrained hypotheses. This paper introduces the R package SSDbain, which can be used to calculate the sample size required to evaluate (informative) hypotheses using the Approximate Adjusted Fractional Bayes Factor (AAFBF) for one-way ANOVA models as implemented in the R package bain. The sample size is determined such that the probability that the Bayes factor is larger than a threshold value is at least η when either of the hypotheses under consideration is true. The Bayesian ANOVA, Bayesian Welch's ANOVA, and Bayesian robust ANOVA are available. Using the R package SSDbain and/or the tables provided in this paper, researchers in the social and behavioral sciences can easily plan the sample size if they intend to use a Bayesian ANOVA.</p
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