9. The data presented in Problem 7 are analyzed using muliple linear regression analysis and the...

9. The data presented in Problem 7 are analyzed using muliple linear regression analysis and the models are shown here. In the models, the data are coded as 1= new treatment and 0= standard treatment, and age greater than 65 is coded as 1= yes and 0= no.

y= 53.85- 23.54 (Treatment)

y= 45.31- 19.88 (Treatment) + 14.64 (Age > 65)

y= 45.51 - 20.21 (Treatment) + 14.29 (Age> 65) + .75 (Treatment X Age > 65)

Patients < 65 y= 45.51 -20.21 (Treatment)

Patients 65 + y = 59.80 -19.47 (Treatment)

Does it appear that there is effect modification by age? Justify your response using the preceeding models.

Based on your answers to Problem 8 and Problem 9, how should the effect of treatment be summarized? Should results be reported separetly by age group or combined? Should the effect of treatment be adjusted for age? Justify your response use the models presented in the above problem.

Problem 8 answer is 7.56>3.84 at 1 degree of freedom, so null hypothesis gets rejected. The age and treatment are not independent.

Solutions

Expert Solution

orchestra answered 1 year ago

Next > < Previous

Related Solutions

The data presented in Problem 7 are analyzed using multiple linear regression analysis and the models...

The data presented in Problem 7 are analyzed using multiple linear regression analysis and the models are shown here. In the models, the data are coded as 1 = new medication and 0 = standard medication, and age 65 and older is coded as 1 = yes and 0 = no. ŷ = 53.85 − 23.54 (Medication) ŷ = 45.31 − 19.88 (Medication) + 14.64 (Age 65 +) ŷ = 45.51 − 20.21 ( Medication ) + 14.29 ( Age...

Run a linear regression using Excel’s Data Analysis regression tool. Construct the linear regression equation and...

Run a linear regression using Excel’s Data Analysis regression tool. Construct the linear regression equation and determine the predicted total sales value if the number of promotions is 6. Is there a significant relationship? Clearly explain your reasoning using the regression results. Number of Promotions Total Sales 3 2554 2 1746 11 2755 14 1935 15 2461 4 2727 5 2231 14 2791 12 2557 4 1897 2 2022 7 2673 11 2947 11 1573 14 2980

Using the following data, conduct a linear regression analysis (by hand). In this analysis, you are...

Using the following data, conduct a linear regression analysis (by hand). In this analysis, you are testing whether SAT scores are predictive of overall college GPA. Also, write out the regression equation. How would you interpret your results? SAT Score GPA 670 1.2 720 1.8 750 2.3 845 1.9 960 3.0 1,000 3.3 1,180 3.2 1,200 3.4 1,370 2.9 1,450 3.8 1,580 4.0 1,600 3.9

The following data contains the characteristics of 30 motorcycles that will be analyzed using a Regression...

The following data contains the characteristics of 30 motorcycles that will be analyzed using a Regression model. You will study the relationship between a motorcycles' engine power (measured in horsepower) and the motorcycles' weight (measured in pounds). Power (cf): 145 215 165 85 225 87 175 210 158 86 150 150 76 170 208 150 215 225 220 153 175 130 140 165 180 150 190 110 150 86 Weight (lb): 4082 4735 3693 2310 4951 2672 4464 4382 4363...

Correlation and Simple Linear Regression Analysis Determine the following using data about "hours studying per weekend"...

Correlation and Simple Linear Regression Analysis Determine the following using data about "hours studying per weekend" and "grade point average" below. a) scatter diagram with hours the independent variable b) coefficient of correlation c) coefficient of determination d) coefficient of nondetermination e) average error for predicting grades f) .01 level of significance test for slope being 0 g) regression equation h) expected grades for people who study 5 hours Hours Grades 3 3.0 2 2.0 6 3.8 3 2.6 4...

In this problem, we will use linear regression and residual analysis to study the relationship between...

In this problem, we will use linear regression and residual analysis to study the relationship between square footage of a house and the home sales price. (a) Go to the course webpage and under Datasets, download the CSV file “homes.csv” and follow the accompanying Minitab instructions. Copy and paste the Fitted Line Plots and the Residual Plots in a blank document. Print these out and attach them to your homework. (b) Based on the fitted line and residual plots for...

Importance of linear regression in research analysis.

In a simple linear regression analysis, will the estimate of the regression line be the same...

In a simple linear regression analysis, will the estimate of the regression line be the same if you exchange X and Y? Why or why not?

A linear industry demand function of the firm’s product was estimated using regression analysis. The results...

A linear industry demand function of the firm’s product was estimated using regression analysis. The results of this estimation are as follows: Q = a + bX where X is product’s own price. The team will use the results of the model only at confidence level = 90.00 %. Dependent Variable Y R-Square F-Ratio P-Value On F Observations 10 0.5223 8.747 0.0187 Variable Parameter Estimate Standard Error T-Ratio P-Value Intercept 800 189.125 4.23 0.0029 X -2.5 0.85 -2.94 0.0187 What...

13. Linear regression analysis was performed for a standard addition data set based on this experiment....

13. Linear regression analysis was performed for a standard addition data set based on this experiment. The analysis yielded the following results: m = 0.006110, b = 0.008170. What is the unknown's riboflavin concentration (ppm) in the standard addition solutions? a) 2.0 b) 13.37 c) 1.337 d) 1.67 15. The riboflavin concentration in the unknown powder solution is 58.0 ppm. The total volume of the powder solution is 250.00 mL. What is the concentration in the tablet (mg ribo/tablet) if...

Subjects