The analysis described in Problem 1 for the posture measurement data on Shoulder Flexion (SF) may be criticized because information
The analysis described in Problem 1 for the posture measurement data on Shoulder Flexion (SF) may be criticized because information is lost when the 4 observations for a given subject on a given day are combined into an average score rather than being treated individually in the analysis. The data set shown below allows for an analysis t considers all 12 observations per subject. In analyzing this data set, we assume that the 4 observations for a given subject on a given day are true replicates (i.e., we assume that neither the time of day observed nor the rater used, factors that combine to provide the 4 observations for a given subject, is an important factor for predicting SF response).
a. How should the subject-specific scalar model for Problem 1 be modified to consider the data layout below? (You will need to add a second random effect to the model that reflects the interaction of Day with Subjects.)
b. Use the computer information provided below to test whether there is a significant main effect of the factor Day. (See the ANOVA table provided below.) What do you conclude?
c. Use the computer output provided below to test whether there is a significant interaction effect between Subjects and Day. If such a test is nonsignificant, why might you be concerned regarding the model that has been fit, and how might you redo the analysis?
a SF ij 0 b i0 1 b i1 D ij1 2 b i2 D ij2 E ij i 1 19 j 1 2 12 where E ij b i0 b i1 and b i2 are each …View the full answer
I have the expertise to deliver these subjects to college and higher-level students. The services would involve only solving assignments, homework help, and others.
I have experience in delivering these subjects for the last 6 years on a freelancing basis in different companies around the globe. I am CMA certified and CGMA UK. I have professional experience of 18 years in the industry involved in the manufacturing company and IT implementation experience of over 12 years.
I have delivered this help to students effortlessly, which is essential to give the students a good grade in their studies.
The Dupont analysis is an expanded return on equity formula, calculated by multiplying the net profit margin by the asset turnover by the equity multiplier. The DuPont analysis is also known as the DuPont identity or DuPont model.This Video will guide on how to calculate return on Equity and estimate profitability of shareholders using DuPont Analysis.