-
Notifications
You must be signed in to change notification settings - Fork 0
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Week 4 #11
Comments
Hi Jestri,
Q2a: The text above the questions says this: "Run a naive model that
predict the effect of public housing assistance on health status. Include
race, education, age, and marital status as control variables. We are not
accounting for our omitted variable, healthy lifestyle, in this initial
model."
So the Naive model should be lm(HealthStatus ~ PublicHousing + Race +
Education + Age + MaritalStatus). Be sure to sure change Race and Marital
Status into Factor variables. The full model will be the 2 stage
regression you do below.
Q3a. Is asking you to list out the three criteria that are needed for a
valid instrument. It does not ask you which can be tested
Q4a This question is asking which of the three criteria you can test with
the correlation matrix.
…On Wed, Apr 20, 2022 at 11:08 AM Jestrii Acosta ***@***.***> wrote:
Hello,
I am just asking questions about the questions I got wrong in my lab,
hopefully, it helps someone else or if someone can help out that would also
be nice.
Q2a My general question would be if I am understanding the models correctly
full.model <- lm( HealthStatus ~ PublicHousing + Education + Age + Stamp )
# Full Model if we were able to measure ability
naive.model <- lm( HealthStatus ~ PublicHousing)
Naive Model where ability is excluded (omitted variable bias)
stargazer( full.model, naive.model,
type = "text",
dep.var.labels = ("Health Status"),
column.labels = c("Full Model", "Naive Model"),
covariate.labels = c("Public Housing", "Waiting Time", "Education", "Age"
),
omit.stat = "all",
digits = 2 )
Q3a I understand that we can only do characteristic 2 because we have
information omitted variable, is that what this question is asking?
Q4a would this relate to question 3a about how we can only test the second
characteristic or is it asking about the specific variables.
—
Reply to this email directly, view it on GitHub
<#11>, or
unsubscribe
<https://github.com/notifications/unsubscribe-auth/AB4EHB4XELFHKSTASI5DTALVGBBYBANCNFSM5T42VYGQ>
.
You are receiving this because you are subscribed to this thread.Message
ID: ***@***.***>
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Hello,
I am just asking questions about the questions I got wrong in my lab, hopefully, it helps someone else or if someone can help out that would also be nice.
Q2a My general question would be if I am understanding the models correctly
full.model <- lm( HealthStatus ~ PublicHousing + Education + Age + Stamp ) # Full Model if we were able to measure ability
naive.model <- lm( HealthStatus ~ PublicHousing)
Naive Model where ability is excluded (omitted variable bias)
stargazer( full.model, naive.model,
type = "text",
dep.var.labels = ("Health Status"),
column.labels = c("Full Model", "Naive Model"),
covariate.labels = c("Public Housing", "Waiting Time", "Education", "Age"
),
omit.stat = "all",
digits = 2 )
Q3a I understand that we can only do characteristic 2 because we have information omitted variable, is that what this question is asking?
Q4a would this relate to question 3a about how we can only test the second characteristic or is it asking about the specific variables.
The text was updated successfully, but these errors were encountered: