Modelling digestive hydrolysis of nutrients in fish using factorial designs and desirability function. [PDF]
PLoS ONE, 2018 Models simulating the in vitro digestive hydrolysis of nutrients by different animal species are frequently used to obtain a better understanding of factors affecting this process.
Neda Gilannejad +3 more
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Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial [PDF]
Frontiers in Psychology, 2022 Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion ...
Florian Loffing, Florian Loffing
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Factorial Designs Help to Understand How Psychological Therapy Works [PDF]
Frontiers in Psychiatry, 2020 A large amount of research time and resources are spent trying to develop or improve psychological therapies. However, treatment development is challenging and time-consuming, and the typical research process followed—a series of standard randomized ...
Edward R. Watkins, Alexandra Newbold
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Unbalanced 2 x 2 factorial designs and the interaction effect: a troublesome combination. [PDF]
PLoS ONE, 2015 In this power study, ANOVAs of unbalanced and balanced 2 x 2 datasets are compared (N = 120). Datasets are created under the assumption that H1 of the effects is true. The effects are constructed in two ways, assuming: 1.
Johannes A Landsheer +1 more
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QANOVA: quantile-based permutation methods for general factorial designs [PDF]
Test (Madrid), 2021 Population means and standard deviations are the most common estimands to quantify effects in factorial layouts. In fact, most statistical procedures in such designs are built toward inferring means or contrasts thereof.
Marc Ditzhaus +2 more
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Multilevel factorial designs with experiment-induced clustering. [PDF]
Psychol Methods, 2018 Factorial experimental designs have many applications in the behavioral sciences. In the context of intervention development, factorial experiments play a critical role in building and optimizing high-quality, multicomponent behavioral interventions. One
Nahum-Shani I, Dziak JJ, Collins LM.
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Use of Factorial Designs to Reduce Stability Studies for Parenteral Drug Products: Determination of Factor Effects via Accelerated Stability Data Analysis [PDF]
PharmaceuticsObjectives: This study explores the potential of factorial analysis as an alternative strategy for optimizing stability study designs for registration batches—an approach not currently addressed in ICH Q1D, which focuses solely on bracketing and ...
Lara Pavčnik +3 more
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Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond. [PDF]
Educ Psychol Meas, 2017 Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs).
Wiens S, Nilsson ME.
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GFD: An R Package for the Analysis of General Factorial Designs
Journal of Statistical Software, 2017 Factorial designs are widely used tools for modeling statistical experiments in all kinds of disciplines, e.g., biology, psychology, econometrics and medicine. For testing null hypotheses in this framework, ANOVA methods are widely used.
Sarah Friedrich +2 more
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A Bayesian approach to the selection of two-level multi-stratum factorial designs [PDF]
Annals of Statistics, 2018 In a multi-stratum factorial experiment, there are multiple error terms (strata) with different variances that arise from complicated structures of the experimental units. For unstructured experimental units, minimum aberration is a popular criterion for
Ming-Chung Chang, Ching‐Shui Cheng
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