Questions tagged [fractional-factorial]
Experimental designs that use only a subset of possible factor combinations. Typically, some factors are intentionally confounded w/ some interactions, making the interactions impossible to estimate, but requiring a smaller N for the study.
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De-aliasing two-factor interactions in a Plackett-Burman design
what I've got so far is a 2-level experiment design with 10 factors and 32 experiments, which is made of a resolution III Plackett-Burman design that I folded (complete foldover) so that it is a ...
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1answer
35 views
How to extend Plackett-Burman design to further explore the interactions?
My situation is as follows: I have built a 2-level Plackett-Burman design with 10 factors (some are actual 0/1-variables, the others are numeric and I used the minimum and the maximum) and 32 ...
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Interaction Effects, Zero or non-Zero in 2 factor factorial design?
In a 2 factor factorial design it is common to use the following linear model and the associated notation:
$y_{ijk}=\mu+\alpha_{i}+\beta_{j}+(\alpha\beta)_{ij}+\epsilon_{ijk}$
$(\alpha\beta)_{ij}$ ...
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How to deciding on the number of experimental runs in R for orthogonal fractional factorial design?
Presently I am working on designing a questionnaire for my discrete choice experiment. I want to generate an orthogonal fractional factorial design for the following problem-
The respondent has to ...
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50 views
Is there value in assigning a dimension-specific weighting when calculating the main effect?
I've been looking into factorial designs and noticed an interesting property. Is this simply a mathematical trick or can we attribute some 'meaning' to it?
Say we have a $2^k$ design where k = 3 here....
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1answer
29 views
Why is there aliasing in a full-factorial design?
I am using the R package AlgDesign to evaluate the design of a simple full-factorial experiment, tweaking an example from R Bloggers. I've specified ...
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26 views
Bayesian updating of log-normal parameter after observation of poisson process
I am trying to update my estimate of a parameter (error rate) which has a prior log-normal distribution using an observation of errors (presumed to be Poisson distributed). However, I am having some ...
5
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1answer
79 views
Do I want a mixed model for fractional factorial designs?
I have created a d-efficient fractional factorial design of 48 combinations from a total of 192 possible combinations (4x2x2x3x2x2).
For the experiment, I plan to have 4 runs in 12 blocks and 40 ...
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1answer
51 views
How to generate a design for a response surface with a discrete input random variable?
I'm trying to generate a design of experiments for fitting a response surface for a quantity $Y$ such that, $Y = f(X_1, ..., X_6)$. I'm open to a factorial design as well as a random design. $X_1,..., ...
4
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1answer
623 views
Advantages/disadvantages of fractional factorial design vs completely randomized design
I'm new to the design of experiments (DoE) and will be running a screening experiment to estimate the effect of a large number of binary independent variables (approximately 10) on a single continuous ...
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1answer
60 views
How to analyze experiment (based on DoE and via mixed model)?
I am about to deploy my DoE which is based on six parameters with two whole plots: Temperature and relative humidity. The experiment aims at studying a sensor due to the presence of several gases (...
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What is a “regular” fractional factorial (2-level)?
What is the difference between a regular fractional factorial design and a non-regular fractional factorial design? I found it several times but especially in the FrF2-package.
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1answer
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How to study a fractional factorial design? [closed]
I wonder why a DoE/fractional factorial design isn't studied with the help of a linear mixed model? Or an Anova?
How to analyze it in general is e.g. given here.
Background: I will study several gas ...
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0answers
26 views
Interpreting interaction effects in Factorial design
I have factor1 with 2 levels fully crossed with factor2 (5 levels). Now samples are collected from same experimental units at 6 different times. Time is used as within-subject variable. When I run ...
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0answers
33 views
Full factorial repeated measures ANOVA
I have a Full factorial design where factor1 has 2 levels and factor2 has 5 levels fully crossed (10 treatments in total). Then the samples are collected from same individuals (plots) at 6 different ...
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0answers
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“Incomplete Design” Problem: 2(between) x 2(within) x 2(within--but only in one between group!)
Problem:
I am trying to analyze an experiment with the design in the title:
2(between) x 2(within) x 2(within--but only manipulated in one group)
My initial hunch was to run two separate 2 (between)...
1
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1answer
186 views
Fractional factorial DOE in pythonDOE problem
I need to do a fractional factorial DOE analysis for my data that will come at the end of the post as image, I am using this code in python . It would need to pip install diversipy if you haven't ...
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114 views
Multi-level factor design of experiments
How should I select interactions in order to be able to encode multi-level features using interactions of main features in my design?
I'm wanting to create an experimental design to be used to create ...
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1answer
48 views
logistic and anova
In here, you can see original data.
My data is $4\times3\times3\times2$ completely randomized design experiment data.
I want to model the probability of survival in terms of the stimulus variables.
...
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1answer
68 views
Factorial design name
I was just wondering, as I have been using ordinary least squares regression a lot lately, could anyone explain why a factorial design called a "factorial" design?
What part of the calculation is ...
5
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1answer
300 views
How to calculate (standardized) orthogonal contrast coding in R?
I want to determine efficient fractional factorial designs and blocked designs for factorial surveys and am using the R library AlgDesign. The criteria I'm using to determine if a design is efficient ...
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1answer
26 views
Adding center points in $2^k$ models
I'm not sure I understand this concept. In $2^k$ designs, the independent variables have only two values and are coded as either being -1 (low value) or +1 (high value).
We can add a center point to ...
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1answer
29 views
Comparison of treatment differences in fully factorial design
I have a dataset from a fully factorial experiment aimed at looking at mortality rates in fish depending on chemical additions.
There are manipulations of Buffers (2 types), Nutrients (Ca and Mg) ...
0
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1answer
59 views
Constrained design of experiments
I would like to conduct a 2-level fractional factorial experimental design on 8 factors. I used the FrF2 package in R to do so. I have capacity to do roughly 30 experiments, so I selected a resolution ...
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0answers
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Factorial experiment design with incompatible levels in IVs
Is it safe to run a Factorial ANOVA if you cannot collect data for some cells?
Scenario: There are two independent variables, and one dependent variable.
All independent variables are nominal:
D (...
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1answer
15 views
Does a factorial design work for factors that have discrete levels, but can't be classified as “high” or “low”?
I have eight factors, four with 2 levels and four with 3 levels. These levels are not "high" and "low" in the sense that they can be turned off and on—but are instead things like "voiced" and "...
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0answers
80 views
Simulate responses for fractional factorial design
I want to simulate responses for fractional factorial design.
As an input for simulation I want to use estimated effect sizes of main factors and some interactions.
I know there is a formula for ...
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1answer
31 views
Central composite design
I'm a data scientist who has not used central composite design before, I only heard of it, but I'm not able to grasp for what it can be used and how it can be used.
Can someone please explain this to ...
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0answers
17 views
Arbitrary combination of levels in fractional factorial Experiments
I have a problem figuring out the properties of an existing fractional factorial experiment. I basically have the following samples 1-6 and the properties A-D:
...
2
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1answer
479 views
DOE for evaluating a factor with more than 2 levels
I am new to designing experiments. I like the simplicity of 2-level, fractional factorial designs for screening what factors and interactions are important. However, I often conduct competitive ...
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0answers
44 views
When do three-factor interactions or higher be assumed negligible?
I am referring to fractional factorial designs where some two-factor interactions are aliased with three factor-interactions, and three-factor interactions are aliased together.
To simplify the ...
2
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1answer
661 views
Fractional Factorial design for 3 factorial
I would like to be assisted on how to go about choosing the treatments to work with in a fractional factorial the following scenario.
I have 3 factors ie 3 feeding intervals, 3 larval densities and 3 ...
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0answers
232 views
How to quantify the “resolution” of “Fractional factorial design”? [duplicate]
The Design Expert software gives me the picture of resolution for the fractional factorial design, in which Resolution III, IV and V are most critical.
But can I ask, how can I determine the ...
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1answer
159 views
Design of Experiments for Baking
I am very new to design of experiments concept. I would like to design an experiment to understand the relationship between input parameters like amount of various ingredients, cooking temperature, ...
3
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1answer
430 views
How to set up a mixed model with partially crossed factor levels
I would need some help with the analysis of a soil data set. The variable Ms was measured with n=5 over several campaigns (7 levels; i, ii, iii...) throughout a year on an agricultural field that ...
0
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1answer
203 views
Incomplete treatments in Fractional Factorial Designs
I'm trying to analize a chemical experiment with four factors or independent variables. Initially each factor had three levels, so i proposed a $3^4$ factorial design; the problem was that all the ...
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0answers
278 views
2x2x2 (reduced) design to study main effects
I'm at the point of conducting a 2x2x2 factorial design to study corporate adoption decisions. I am only interested in the main effects and run a ANCOVA. This experiment is only one part of a bigger ...
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1answer
109 views
confounding ABC in factorial experiment
Consider a $ 2^3 $ factorial design lay out in 2 blocks ,each of size 4, as follows
Block I: {1,a,b,c}
Block II: {ab,ac,bc,abc}
Here,the treatments combinations are written in Yate's notation. ...
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0answers
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DoE - full factorial with less levels or fractional factorial with more levels?
I am planning on doing a variance components analysis (random effects anova). I'm wondering if anyone has any advice regarding balancing the number of levels to include in the design vs. the type of ...
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0answers
55 views
Question regarding a factorial design and the main effect of one of its factor
Suppose we consider the following $2^4$ factorial design with factors A, B, C and D in the usual order.
$Block1 - (0,0,0,0),(0,1,0,1),(1,0,1,0),(1,1,1,1),(1,1,0,1),(0,0,1,0).$
$Block2 - (0,0,1,1),(...
5
votes
1answer
992 views
Algorithm for generating a multi-level fractional factorial design
I would like to perform some black box testing on some software that takes a large number of input variables. These variables can have some interactions (either intentional or non-intentional) so I ...
5
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0answers
301 views
Optimum approximate theory D-Optimal design
I am using optFederov, from package AlgDesign, to create D-Optimial designs. However, I am a bit confused on what measure to use as efficiency measure. I'd like to use D-Optimal but I don't know which ...
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1answer
426 views
Experimental (factorial) design not exploiting the variance
I want to construct a design to use Choice Based Conjoint Analysis. I want to focus on D-Optimality, for that reason I use the R package AlgDesign which uses Fedorov Algorithm. I create 7 attributes ...
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0answers
445 views
How to interpret Experimental design created by AlgDesign?
I'm doing an experimental study of 5 factors with a different amount of levels in each. More specifically: 9, 13, 12, 6 & 15.
Using the AlgDesign library in R, i ran the following syntax to ...
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1answer
400 views
Machine Learning for optimization of configuration file
For my master's thesis I am using a 3rd party program (SExtractor) in addition to a python pipeline to work with astronomical image data. SExtractor takes a configuration file with numerous parameters ...
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0answers
294 views
How to combine in a (fractional) factorial design model the blocking effect with a treatment (package planor)
For my greenhouse experiment with potted trees, I am planing a fractional factorial design. The experiment has six factors (treatments) each with two factor-levels, and I want to use a model/package, ...
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Fractional factorial designs: lower $p$ vs. more replications
If you were to choose between a 2(X-1) with only one replication or a 2(X-2) with two replications, what would be preferred and why? The goal is to both predict the values of the effect parameters as ...
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0answers
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How do I analyze interaction in two-factor factorial data when sample size is not given?
I am looking at two-factor factorial data where the response variable is number of cancer cells after an experiment is performed.
The two-factors are:
Factor A, which has a = 2 levels: "...
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0answers
248 views
True replicates or nested data ANOVA - only one experimental unit per condition
I'm in materials science. I have a fractional factorial experiment. I am investigating the main effect of various treatments on a measured response. The exact details are probably not needed to ...
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1answer
264 views
How can I fit a polynomial given some prior knowledge but fewer observations than coefficients?
I want to fit a second degree polynomial to data from a fractional factorial design in five dimensions. Because of the cost of trials, I am initially only going to do eight runs. So I have fewer ...
