Dselby86
commented
2 years ago 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.
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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.