The following problems can be threats to the validity of a regression discontinuity analysis, with the exception of: a. jumps in covariates. b. manipulation of the assignment variable. c. nonlinear relationship between the assignment and the outcome Variable. d. misallocation of treatment.
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The following problems can be threats to the validity of a
| a. |
jumps in |
|
| b. |
manipulation of the assignment variable. |
|
| c. |
nonlinear relationship between the assignment and the outcome Variable. |
|
| d. |
misallocation of treatment. |
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4Discuss , in detail , ( using as many graphs and as much maths as possible ) , why the naïve estimator is unbiased. Can you propose another estimator , which is also not the linear regression estimator but is unbiased ?For which of the following sets of data points can you reasonably determine a regression line? Explain your answer.
- If there is no significant correlation between the response and explanatory variables, would the slope of the regression line be (a) positive (b) negative (c) zero?For each of the following, explain what is wrong and why. a)In simple linear regression, the null hypothesis of the ANOVA F test is H0: β0 = 0. b)In an ANOVA table, the mean squares add. In other words, MST = MSM + MSE. c)The smaller the P-value for the ANOVA F test, the greater the explanatory power of the model. d)The total degrees of freedom in an ANOVA table are equal to the number of observations n.If a new independent variable is added to a regression equation, the adjusted R2 increases only if the absolute value of the t-statistic of the new variable is greater than one. Group of answer choices True False.
- Which of the following is not an example of systematic error in an observational study? A cross-sectional study recruits participants that are willing to sign up outside of a major university and meet the inclusion and exclusion criteria to take part in the survey relating unsafe sex habits to STIs. A researcher is interested in the relationship between coffee drinking and lung cancer, and after careful multivariate linear regression modeling determines that a significant percentage of the relationship is due to another variable, cigarette smoking. An observational study recruits participants for a study looking at Alzheimer’s disease due to exposure to industrial hazards by asking participants to recall their exposure over the past 10 years. data-entry specialist responsible for adding in fasting glucose levels to a database accidentally skipped an observation during the input phase of data cleaning.Is there any multicollinearity problem in the above multiple regression model? How do you know? Risk of Stroke (%) Age Pressure Smoker (Yes=1) 12 57 152 0 24 67 163 0 13 58 155 0 56 86 177 1 28 59 196 0 51 76 189 0 18 56 155 1 31 78 120 0 37 80 135 1 15 78 98 0 22 71 152 0 36 70 173 1 15 67 135 1 48 77 209 0 15 60 199 0 36 82 119 1 8 66 166 0 34 80 125 1 3 62 117 0 37 59 207 1If a scatterplot is created in excel, and a line of regression is fit along with a derived functional form, what does it mean to describe and interpret them? What conclusions would be made about relationships between two recorded variables?
