Homework Help is Here – Start Your Trial Now!
Math
Statistics
The true data-generating mechanism for the simulated data is Y = 4Z - 0.8X1-3X2 +6X4 + Xs +error. d.) Note that the outcome of interest Y is a function of Xs, and thus balance on X5 is critical for valid causal inference. If units are matched or partitioned into subgroups according to their true propensity scores, are these subgroups expected to be balanced, on average, in terms of X5? Why or why not? Choose the best answer. Yes, because X5 is unrelated to the true propensities. Yes, because the outcome Y is still a function of Xs No, because it is impossible to know if the subgroups are balanced in terms of X5 No, because X5 is independent of all other covariates No, because X5 is not a confounding variable Now fit a single propensity score model that is overspecified. use all five covariates as well as interactions between x3 and each of the other four covariates to predict the propensities. Again, use the fitted model to predict point estimates of the propensity scores for each observation, and compare your estimates to the true propensities. e.) What is the standard deviation of the prediction errors e (X) - ê (X) for the propensities predicted by this overspecified propensity model? Choose the closest answer. 0.005 0.03 0.09 0.90 11.5

The true data-generating mechanism for the simulated data is Y = 4Z - 0.8X1-3X2 +6X4 + Xs +error. d.) Note that the outcome of interest Y is a function of Xs, and thus balance on X5 is critical for valid causal inference. If units are matched or partitioned into subgroups according to their true propensity scores, are these subgroups expected to be balanced, on average, in terms of X5? Why or why not? Choose the best answer. Yes, because X5 is unrelated to the true propensities. Yes, because the outcome Y is still a function of Xs No, because it is impossible to know if the subgroups are balanced in terms of X5 No, because X5 is independent of all other covariates No, because X5 is not a confounding variable Now fit a single propensity score model that is overspecified. use all five covariates as well as interactions between x3 and each of the other four covariates to predict the propensities. Again, use the fitted model to predict point estimates of the propensity scores for each observation, and compare your estimates to the true propensities. e.) What is the standard deviation of the prediction errors e (X) - ê (X) for the propensities predicted by this overspecified propensity model? Choose the closest answer. 0.005 0.03 0.09 0.90 11.5

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
See similar textbooks
icon
Related questions
Question
The true data-generating mechanism for the simulated data is Y = 4Z – 0.8X1 - 3X2 + 6X4 +X5 + error. d.) Note that the outcome of interest Y is a function of X5, and thus balance on X5 is critical for valid causal inference. If units are matched or partitioned into subgroups according to their true propensity scores, are these subgroups expected to be balanced, on average, in terms of X5? Why or why not? Choose the best answer. Yes, because X5 is unrelated to the true propensities. Yes, because the outcome Y is still a function of X5 No, because it is impossible to know if the subgroups are balanced in terms of X5 No, because X5 is independent of all other covariates No, because X5 is not a confounding variable Now fit a single propensity score model that is overspecified. use all five covariates as well as interactions between x3 and each of the other four covariates to predict the propensities. Again, use the fitted model to predict point estimates of the propensity scores for each observation, and compare your estimates to the true propensities. e.) What is the standard deviation of the prediction errors e (X) – ê (X) for the propensities predicted by this overspecified propensity model? Choose the closest answer. 0.005 0.03 0.09 0.90 11.5
Transcribed Image Text:The true data-generating mechanism for the simulated data is Y = 4Z – 0.8X1 - 3X2 + 6X4 +X5 + error. d.) Note that the outcome of interest Y is a function of X5, and thus balance on X5 is critical for valid causal inference. If units are matched or partitioned into subgroups according to their true propensity scores, are these subgroups expected to be balanced, on average, in terms of X5? Why or why not? Choose the best answer. Yes, because X5 is unrelated to the true propensities. Yes, because the outcome Y is still a function of X5 No, because it is impossible to know if the subgroups are balanced in terms of X5 No, because X5 is independent of all other covariates No, because X5 is not a confounding variable Now fit a single propensity score model that is overspecified. use all five covariates as well as interactions between x3 and each of the other four covariates to predict the propensities. Again, use the fitted model to predict point estimates of the propensity scores for each observation, and compare your estimates to the true propensities. e.) What is the standard deviation of the prediction errors e (X) – ê (X) for the propensities predicted by this overspecified propensity model? Choose the closest answer. 0.005 0.03 0.09 0.90 11.5
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 2 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS