i'm medical student hoping to improve in statistical methods.
now i'm working on linear regression
The problem:
------------
i was going to investigate the relation between variable Y and
variables X1, X2, X3, X4
i performed univariate analysis, using linear regression method. then
i performed multiple regression. (to compare results, for better
understanding)
assumed significance: p<0,05
Linear regression results:
---------------------------
Y-X1 Y-X2 Y-X3 Y-X4
r ,50 -,35 ,01 -,27
p ,005 ,061 ,951 ,156
my conclusions:
- there is significant dependence between Y and X1
- there are no significant dependence between Y and X2, Y and X3, Y
and X4,
Multiple regression results:
------------------------------
dependent var: Y
independent: X1, X2, X3, X4
Adj. R2 = 0,37
p=0,003
intercept: B=97,5 ; p=0,000
X1 X2 X3 X4
beta ,29 -,36 ,83 -,70
p ,09 ,051 ,011 ,034
my conclusions:
- there is a significant dependance between Y and X3 and X4
- there is no dependance between Y and X1, X2
My questions:
------------
1.
the conclusions based on linear regression and multiple regression are
totally different.
for instance: X3 seems to be completely unrelated to Y in univariate
analysis and is the most important important factor in multivariate
analysis.
obviously, there must be a mistake in my thinking. please correct me.
2.
should i trust the results from linear regression or multiple
regression?
3.
which method (univariate regression, multiple regression) should i use
when both can be used?
4.
has the parameter "intercept" any value in interpretation of the
results of multiple regression ?
.
.
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