Suppose you estimate the equation Yit = a +b Xit + eit - Which one of the following statements is true? Within group and logit estimates of b will be identical OLS and random effect estimates of b will be identical LSDV and random effect estimates of b will be identical OLS and within group estimates of b will be the identical None of the above
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- You were asked to help with an analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers’ AGE at birth (continuous variable in years), mothers’ current HOUSING status (“own” and “not-own”; “own” is the reference group), and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”; “Manhattan” is the reference group). Write down the population model that estimates the effect of mother’s AGE on BW while adjusting for mother’s current HOUSING status. If you use dummy or binary variables, specify what they mean. Write down the population model that estimates the effect of mother’s AGE on BW while adjusting for mother’s current HOUSING status and BOROUGH. If you use dummy or binary variables, specify what they mean. Write down the population model that estimates the effect of mother’s AGE…Suppose you have access to a database with the variables listed below. Using the two variables BMI(the predictor) and diabetes(the outcome) Name two types of descriptive statistics you could report specifying the variables BMI and diabetes.A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…
- Help me pleaseSuppose you are interested in the role of social support in immune function among retired men who live alone. You ask 50 patients to record the number of days they do not see or interact with a friend or family member over a period of 1 month to see whether the number of nonsocial days in a typical month correlates with the number of new illnesses they experience per year. You decide to use the computational formula to calculate the Pearson correlation between the number of nonsocial days in a month and the number of illnesses per year. To do so, you call the number of nonsocial days in a month X and the number of illnesses per year Y. Then, you add up your data values (∑X and ∑Y), add up the squares of your data values (∑X2 and ∑Y2), and add up the products of your data values (∑XY). The following table summarizes your results: ∑X 590 ∑Y 380 ∑XY 4,887 ∑X2 10,456 ∑Y2 4,258 Find the following values: The sum of squares for the number of nonsocial days in a month is SSX=…You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). Questions: 1.Write down the population model that estimates BW based on variables AGE and BOROUGH(with the dummy variables). Make sure that it is clear what each predictor means. 2.How many parallel lines are computed by model from population model you created above? 3.Write down the population model that estimates BW based on variables AGE, MSS(with their dummy variables) and BOROUGH(with their dummy variables). Also write down the number of parrallel lines.…
- Ankylosing spondylitis is an inflammatory disease which affects the spine and sacroiliac joint and can lead to the fusing of vertebrae in the spine. Exercise is important in helping manage pain, therefore a pharmaceutical company wanted to test if their new biologic would increase the time a patient could exercise before experiencing discomfort. The following table gives the time (in minutes) seven patients were able to exercise before reporting pain, both at baseline and then again after six months of taking the biologic.Exercise Time (in minutes)Subject 1 Baseline 30 Post-treatment 40Subject 245 40Subject 350 60Subject 435 37Subject 555 60Subject 620 25Subject 775 75Assume the population(s) of all exercise times is (are) normally distributed. Use JMP to test whether the evidence suggests that the time a person with ankylosing spondylitis can exercise before experiencing discomfort increases after taking this new biologic. Validate the test statistic from JMP by computing it manually.…2. I surveyed 150 adults in the U.S. and asked them how many hours of TV the watched on average per week. I then ran a regression of # of hours of TV on whether or not they were a college graduate (=1 if yes, =0 if no), their age in years, the number of children in their household, and whether or not they live a cold climate (=1 if latitude is greater than 41.2, =0 otherwise). The results fro the regression are shown in the table below. Estimate p-value College Graduate -0.8 0.003 Age 0.1 0.150 Number of Children 0.10 0.521 Cold Climate 1.8 0.047 Intercept -1.23 0.041 (a) What is the dependent variable in this regression? (b) What are the independent variable(s) in this regression? (c) What is the unit of analysis? (d) What is the sample size? (e) What is one binary variable used in this analysis? (f) What is one ratio variable used in this analysis? (g) What is the predicted number of TV hours watched by a 50 year old, colleg graduate, with no children at home who lives in Arizona…This dataset of size n - 51 is for the 50 states and the District of Columbia in the United States. The variables are - year 2002 birth rate per 1000 females 15 to 17 years old and z- poverty rate (the percent of the state's population living in households with in- comes below the federally defined poverty level) i- 13.1 - 22.3 R- 51, Su - E(-2) - 914.7 S, - E( -2)( - 6) - 1, 256.2 Su - E(m - M) - 3, 249 SSE - E(w - - 1, 509.6 1. Find A. A and r. 2. Write the fitted linear regression model for ý, in terms of z, A, and A- For A and , use the values you obtained in problem 1. 3. Interpret the slope of the least squares line based on the context. 4. Find SST, SE and SSR. 5. Find R* and . 6. Complete a chart for ANOVA df MS pvalue Source Regression Error Total 7. Complete a chart for Parameter Estimates. t-value pvalue Parameter Intercept Slope Estimate S.e. 8. What is the residual e, for the observation (.) - (20.1,31.5)? 9. What is the conclusion for the test Ha : -0 vs Ho : +0 with a -…
- Below are bivariate data O each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is ing birthrate and life expectancy information for y = 81.87 – 0.46x. Birthrate, x (number of births per 1000 pop.) Female life expectancy, y (in years) 85- 35.7 67.7 80- 41.5 63.9 75 31.9 63.3 19.9 73.0 70 50.5 60.4 65. 24.4 72.7 60- 50.1 63.2 55 13.8 72.5 50 50.3 54.6 45.6 57.9 15.9 76.2 Figure 1 26.6 71.9 Send data to ExcelBb UTF Bb UTF Bb Sigi 2 Sta Bb E Rep 9 Nev Bb UT Rep Bb UTF Bb UTF Bb Mic * Win ent.blackboardcdn.com/5df8324563085/7628679?X-Blackboard-Expiration=1645045200000&X-Blackboard-Signature%3D BIU A A- | 三= Fill out the table below and calculate the x statistic and degrees of freedom. Blackjack Preserve Winthrop Woods Glencarin Garden Observed 54 48 24 d.f. = If you conduct this analysis in R, the output tells you the p-value = 0.002. What conclusion can you make? Explain how you reached this conclusion.