Results 31 to 40 of about 951,451 (326)
In this paper a method of constructing a class of flexible single replicate factorial designs in blocks is given. Simple expressions for calculating loss of information on low order interactions is presented.
Michael Kamau Gachii +2 more
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Exact Optimal Designs of Experiments for Factorial Models via Mixed-Integer Semidefinite Programming
The systematic design of exact optimal designs of experiments is typically challenging, as it results in nonconvex optimization problems. The literature on the computation of model-based exact optimal designs of experiments via mathematical programming ...
Belmiro P. M. Duarte
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Causal inference for multiple treatments using fractional factorial designs [PDF]
We consider the design and analysis of multi‐factor experiments using fractional factorial and incomplete designs within the potential outcome framework.
Nicole E. Pashley, M. Bind
semanticscholar +1 more source
Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments
Factorial designs are widely used to study multiple treatments in one experiment. While t-tests using a fully-saturated “long” model provide valid inferences, “short” model t-tests (that ignore interactions) yield higher power if interactions are zero,
K. Muralidharan +2 more
semanticscholar +1 more source
Generation of 2n series fractional factorial plans robust against linear-trend
Trend-free design for single factor at two level factorial experiments (complete and fractional both) are available in literature but trend-free multi-factor design could not be traced in the literature.
SUSHEEL KUMAR SARKAR +4 more
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Optimal Structure (k) Designs for Comparing Test Treatments with a Control [PDF]
Mukerjee (1979) introduced structure (k) property of a factorial design. In this article, we introduce structure (k1), structure (k2) and structure (k1k2) properties of a factorial design.
M. A. Chowdhury +3 more
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RANCANGAN STRIP PLOT MODEL TETAP
The experiment involve the study of the effects of two or more factors can be used the factorial designs. The factorial designs have several advantages. They are more efficient than one factor at a time experints.
Triastuti Wuryandari +2 more
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Bayesian-inspired minimum contamination designs under a double-pair conditional effect model
In two-level fractional factorial designs, conditional main effects can provide insights by which to analyze factorial effects and facilitate the de-aliasing of fully aliased two-factor interactions. Conditional main effects are of particular interest in
Ming-Chung Chang
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SUMMARY Serial factorial designs are designs for long-term experiments with one or more basic treatments repeated as separate factors every year. The designs are cyclic, with essentially the same structure in any period of successive years. For example, three rates of a single basic treatment (e.g.
openaire +2 more sources
Neural Network Assisted Experimental Designs for Food Research
The ability of artificial neural networks (ANN) in predicting full factorial data from the fractional data corresponding to some of the commonly used experimental designs is explored in this paper.
H.S. Ramaswamy +4 more
doaj +3 more sources

