A survey was conducted and asked: "Do you consider your health to be poor?" This was coded as 1 for "yes" and 0 for "no."The effect of age (in years) and sex (1 male, 0 = female) on the outcome was examined using logistic regression. Thefitted logistic model is:=logit(ô) = −0.544 + ß * sex + 0.0331 * age(a) What are the odds of responding "yes" for a female subject who is 60 years old?(b) What is the estimated odds ratio corresponding to the age variable? Interpret this estimate.(c) Suppose that, based on the data from the survey, the odds of responding "yes" for males are 3.79% greater than theodds for females, adjusting for age. What is the value of Â?(d) If we only wanted to assess the association between survey response (yes/no) and sex, what other method(s) (thatwe have learned in this class) could we have used (name at least one)? In your own words, explain why we cannotuse the same method(s) if we want to consider the effects of both sex and age on survey response.

According to bartleby policy I answered b, c, d subparts.

Answered: A survey was conducted and asked: "Do…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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the following multiple regression model using yearly data spanning the period 2001 to 2016: ??=?+????+????+???? Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports ($000’s) and FDI = annual foreign direct investment ($000’s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Hence test whether ? is significant. Give reasons for your answer. Perform the F Test making sure to state the null and alternative hypothesis. Given an interpretation of the term “R-sq” and comment on its value.
Data was recorded for the temperature, in degrees Celsius, of a cup of coffee over a 30-minute period. Given the regression equation, In(Temp) = 4.20 0.023(Time), what is the predicted temperature after 3 minutes? 33.45 °C 62.24 °C 65.17 °C 66.69 °C
Using the previous regression model, what salary would you expect a student with a 3.1 GPA to expect? Round your answer to 1 decimal and express in $1,000's (same format the Salary variable has in the Excel dataset).
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,815.11 +2563.46 (Education) +897.49(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make? Answer Tables Keypac Keyboard Shortcu
Consider the following model, known as the exponential regression model: Y; = BoefiXi + ui Do you think that you can estimate the model parameters using OLS? Explain. What do you suggest how to estimate the model parameters? How do you think one can proceed estimating these by trial-and-error, or iterative, process?
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,896.07 + 2755.34 (Education) + 773.89 (Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8.years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make?
Take a look at the following sample regressions (type of regression in top row), choose the type of model that best fits the data. Linear Logarithmic Intercept 6.7904 −5.6712 x 1.0607 NA In(x) NA 10.5447 se 2.4935 1.5231 R2 0.8233 0.9341 Adjusted R2 0.8013 0.9259 Linear Logrithmic Both equally Neither model explains a majority of the variation in y
The table below shows the average temperature in New York City (NYC), measured in degrees Fahrenheit (°F), where January is month 1, February is month 2, etc. Jul Jan 38.8 21.3 59.2 Using the regression, the average annual temperature in NYC is predicted to be 58.4 Jun Aug Oct Nov Feb Mar Apr 40.5 47.3 56.8 Sep 72.7 62.4 53.2 76.8 80.1 The data above can be modelled by an equation in the form y = a sin (bx+c) + d. 60.0 Ma 68.4 sin Dec 43.0
The data presented is a multiple logistic regression analysis and the models are shown below. In the models below, the data are coded as follows: p = the proportion of children with a diagnosis of ADHD, Child Exposed and Father’s Diagnosis are coded as 1 = yes and 0 = no. What is the odds ratio adjusted for father’s diagnosis? (Hint: Use only the appropriate model to find the odds ratio) (1) = –2.216 + 1.480 Child exposed (2) Father with diagnosis: = –1.665 + 1.297 Child exposed (3) Father without diagnosis: = –2.343 + 0.823 Child exposed (4) = –2.398 + 1.501 Child exposed + 0.906 Father’s diagnosis
12 A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.531 b=23.45 r2=0.378225 r=0.615 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole numbe
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Which of the following applies the concept of “layering” to increase the sensitivity of a research analysis? Group of answer choices a. Chi-square Contingency Tables b. Binary Logistic Regression c. Regression d. Answers 1 and 2 only e. Answers 1, 2 and 3

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