dear Stanislav,
Your data show two slopes with a kink at around 0. Thus, yet another
approach would be to use segmented regression to fit a piecewise linear
relationship with unknown breakpoint (being estimated as part of model
fitting). While the resulting fitting is likely to be (slightly)
Thanks very much Marc and Ben for the helpful suggestions
Stan
On Sun, Jan 11, 2015 at 10:28 PM, Ben Bolker bbol...@gmail.com wrote:
If you're going to use splines, another possibility is mgcv::gam (also
part of standard R installation)
require(mgcv)
gam(DV ~ s(IV), data=
Comments in line
On 12/01/2015 13:13, Vito M. R. Muggeo wrote:
dear Stanislav,
Your data show two slopes with a kink at around 0. Thus, yet another
approach would be to use segmented regression to fit a piecewise linear
relationship with unknown breakpoint (being estimated as part of model
...
but do realize that after you have looked at the data to determine the
appropriate modeling approach, no statistical inference (significance
tests, confidence intervals, etc.) should be done on the model used.
Or more precisely, any that is done is wrong.
Cheers,
Bert
Bert Gunter
Genentech
I have the following problem.
DV is binomial p
IV is quantitative variable that goes from negative to positive values.
The data look like this (need nonproportional font to view):
o o
o o
o o
o o
On Jan 11, 2015, at 4:00 PM, Ben Bolker bbol...@gmail.com wrote:
Stanislav Aggerwal stan.aggerwal at gmail.com writes:
I have the following problem.
DV is binomial p
IV is quantitative variable that goes from negative to positive values.
The data look like this (need nonproportional
If you're going to use splines, another possibility is mgcv::gam (also
part of standard R installation)
require(mgcv)
gam(DV ~ s(IV), data= YourDataFrame, family=binomial)
this has the advantage that the complexity of the spline is
automatically adjusted/selected by the fitting algorithm
Stanislav Aggerwal stan.aggerwal at gmail.com writes:
I have the following problem.
DV is binomial p
IV is quantitative variable that goes from negative to positive values.
The data look like this (need nonproportional font to view):
[snip to make gmane happy]
If these data were
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