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Accuracy of Pressure and Shear Measurement
Published in J G Webster, Prevention of Pressure Sores, 2019
Experiments can be divided between single factor experiments and factorial experiments (Box et al 1978). Whenever only one factor is varied, the experiment is referred to as a single factor experiment. In a factorial experiment, several factors may be varied simultaneously. In a factorial design the investigator selects a fixed number of levels (i.e. high and low) for each factor (i.e. shear, temperature, etc.) and then runs experiments with all possible combinations. For example, assume we are interested in the effect of shear, temperature, and humidity on a sensor’s output. If we select a high and low level for each factor, then there are 2-levels3-factors = 8 combinations. In general, it can be shown that factorial experiments are the most efficient designs when the experimenter is interested in the effect of more than one factor. The following example illustrates some of the advantages of factorial design. Note that the example experiment is very simple and it is not very realistic. However, it is useful for illustration purposes.
Experimental Studies
Published in M. Venkataswamy Reddy, Statistical Methods in Psychiatry Research and SPSS, 2019
In factorial experiments, the effects of several factors of variation are studied and investigated simultaneously. Here, the treatments are the combinations of different factors under study. In these experiments, an attempt is made to estimate the effects of each of the factors and also their interactive effects. Let us suppose that there are p different doses of diazepam and q different doses of nitrazepam. The p and q are termed as the levels of the factors diazepam and nitrazepam, respectively. A series of experiments in which only one factor is varied at a time would be lengthy, costly, and unsatisfactory because of systematic change in the general background conditions. Moreover, these simple experiments do not tell us anything about the interaction effect. Alternatively, we try to investigate the variation in several factors simultaneously by conducting a p×q factorial experiment. In general, if the levels of various factors are equal, then rs experiment means a factorial experiment with s factors each at r levels.
Evaluating eHealth
Published in Lisette van Gemert-Pijnen, Saskia M. Kelders, Hanneke Kip, Robbert Sanderman, eHealth Research, Theory and Development, 2018
Floor Sieverink, Nadine Köhle, Ken Cheung, Anne Roefs, Hester Trompetter, Julia Keizer, Annemarie Braakman-Jansen, Saskia M. Kelders
Consider the following example: you are interested in investigating the effects of four additional components in a physical activity intervention: Keeping an emotion diary related to physical activity (yes or no)Using an activity tracker (yes or no)Weekly group activities (yes or no)Daily email reminders (yes or no) In a factorial experiment, each of the components that you wish to investigate will be manipulated experimentally, thus becoming an independent variable. In this case, there are four factors (the components), each with two levels (yes or no). This is 2×2×2×2, 24, factorial design and will have 16 different experimental conditions (Table 14.2). Each experimental condition represents a different treatment protocol. To investigate the main effect of a component, you compare the mean of all conditions, including the component, with the mean of all conditions not including the component. For keeping an emotion diary, this means comparing conditions 1 till 8 with 9 till 16. Note that this is very different from a RCT with 16 arms!
Taguchi based Case study in the automotive industry: nonconformity decreasing with use of Six Sigma methodology
Published in Journal of Applied Statistics, 2021
Atakan Gerger, Ali Riza Firuzan
The levels of critical factors leading to process changes are determined and verified in this stage. At the improvement phase, the goal is to narrow down the gap between the current state of the process and the target value. Project management and other planning and administrative tools are utilised to introduce and enforce the new approach. Statistical techniques are implemented to confirm the enhancements [33]. At this stage; the differences in the process are reviewed and which factors contribute significantly to the outcomes are determined. The factors and their levels affecting the flexibility of the door glass seal in the current condition were 8]. In this practice, a full factorial experiment design would require 38] takes concern in experiments generally to estimate the main effects, trying the significance level based on the experiences of the experimenter. These experiments are not based on the potential trial combinations as a whole but rather on examination of a fraction by using vertical columns, triangular tables and linear plots [9]. ‘The goal of the Taguchi method is to find control factor settings that generate acceptable responses despite natural environmental and process variability’ [32]. In this study, a vertical column was formed in the Table 3.
Effects of hand placement, handles and support on manual holding tasks
Published in International Journal of Occupational Safety and Ergonomics, 2021
A three-factor factorial experiment was used in this study. Each factor contained two levels. Hence, there were eight (2 × 2 × 2) experimental conditions in this study. The independent variables of this experiment were hand placement, handles and support. The hand placement conditions included the left hand holding at the left proximal position and the right hand holding at the right distal position (asymmetrical hand placement condition), and both hands holding symmetrically at the middle position on either side (symmetrical hand placement condition). The handle conditions included the presence of handles (handles condition) and an absence of handles (no handles condition). The support conditions included the box held by the hands and supported against the front body of the participant while holding (hands-and-body condition) and the box being only held by the hands while holding (hands condition). The dependent variables of this experiment were muscular activities (left musculus biceps brachii, right musculus biceps brachii, left erector spinae and right erector spinae), box tilt angle (sum of roll angle range, pitch angle range and yaw angle range) and total CoP length during the holding tasks.
Sustained release formulation of Ondansetron HCl using osmotic drug delivery approach
Published in Drug Development and Industrial Pharmacy, 2020
Ramakant Gundu, Sanjay Pekamwar, Santosh Shelke, Santosh Shep, Deepak Kulkarni
Significant advantage is assured if the experiment is so designed that the effect of changing any one variable can be assessed independently of the others. One way of achieving this object is to decide a set of values, or levels for each of the factors to be studied, and to carry out one or more trials of the process with experiment, i.e. Factorial experiment. Center points are duplicated at both the low and high levels of each categorical factor. This doubles the number of center points for each categorical factor in the design. DOE screening was performed to identify the most critical formulation variables impacting the dissolution performance. Further to screening, final optimization would be taken for the most critical factors to achieve the target composition for in vivo screening.