s*********o
发帖数: 13 | 1 Assume you have collected ten or 15 variables to use to predict a single
dependent variable using Multiple Regression. Suppose the results show
that
one of the variables does not have a strong relationship with the dependent
variable in the regression equation, but you notice that the variable has a
high bivariate correlation with the dependent variable.
Why do you think this might happen? What is there about the relationships
among some of the independent variables that might affect their |
K****n
发帖数: 5970 | 2 传说中的interaction和confounding? |
s*********o
发帖数: 13 | 3 still no answer? Is there big guy giving any hint? Thanks
dependent
a
relationships
【在 s*********o 的大作中提到】
: Assume you have collected ten or 15 variables to use to predict a single
: dependent variable using Multiple Regression. Suppose the results show
: that
: one of the variables does not have a strong relationship with the dependent
: variable in the regression equation, but you notice that the variable has a
: high bivariate correlation with the dependent variable.
: Why do you think this might happen? What is there about the relationships
: among some of the independent variables that might affect their
|
s*******t
发帖数: 4 | 4 Maybe because the word "relationship" is ill-defined?
My guess is that the interview is looking for an answer
about multicollinearity.
【在 s*********o 的大作中提到】
: still no answer? Is there big guy giving any hint? Thanks
:
: dependent
: a
: relationships
|
e*******r
发帖数: 481 | 5 this is because of after adjusted with other vaiables,
this variable has little effect. ex, school enroll rate
are high for cities than coutry side. But after adjusted
for income, this may not so high related.
dependent
a
relationships
【在 s*********o 的大作中提到】
: Assume you have collected ten or 15 variables to use to predict a single
: dependent variable using Multiple Regression. Suppose the results show
: that
: one of the variables does not have a strong relationship with the dependent
: variable in the regression equation, but you notice that the variable has a
: high bivariate correlation with the dependent variable.
: Why do you think this might happen? What is there about the relationships
: among some of the independent variables that might affect their
|
s*********o
发帖数: 13 | 6 Yes, I think you are right. Maybe there are several regressors have strong
correlation. Probably this is imperfect multicollinearity issue.
Thanks again
【在 s*******t 的大作中提到】
: Maybe because the word "relationship" is ill-defined?
: My guess is that the interview is looking for an answer
: about multicollinearity.
|
s*********e
发帖数: 1051 | 7 the question is a typical situtation of multicolinearity. if a independent
variable has high bivariate relation with dependent variable but is not
shown significant given other independent variables in the model, it implies
that this independent variable might have a high correlation with one or
some other independent variables. In a regression setting, multicolinearity
needs to be fixed. Otherwise, it will bring up inconsistency issue in the
parameter estimates.
by the way, i will take this typ |
c****w
发帖数: 35 | 8
implies
multicolinearity
just : repeat what I am writing here to your interviewer. I bet he will
keep his mouth : shut immediately after your answer.
haha,cool.
show some examples without any personal humiliation.
【在 s*********e 的大作中提到】
: the question is a typical situtation of multicolinearity. if a independent
: variable has high bivariate relation with dependent variable but is not
: shown significant given other independent variables in the model, it implies
: that this independent variable might have a high correlation with one or
: some other independent variables. In a regression setting, multicolinearity
: needs to be fixed. Otherwise, it will bring up inconsistency issue in the
: parameter estimates.
: by the way, i will take this typ
|
