Fitting linear models

The variables are all in separate vectors.

-----Original Message-----
From: Dimitri Liakhovitski [mailto:ld7631 at gmail.com]
Sent: Tuesday, April 21, 2009 8:26 AM
To: Vemuri, Aparna
Cc: David Winsemius; r-help at r-project.org
Subject: Re: [R] Fitting linear models

Aparna,

I should have been more explicit. Run ?lm . You'll see this:

"lm(formula, data, subset, weights, na.action,
? method = "qr", model = TRUE, x = FALSE, y = FALSE, qr = TRUE,
? singular.ok = TRUE, contrasts = NULL, offset, ...)"

So, in addition to specifying the formula, you have to specify the
data frame in which you keep your variables. I assume they are in a
data frame? (unless for some reasons you keep all variables as
separate vectors).
So, after you wrote the formula, you have to indicate the name of the
data frame, for example "MyData":

model1<-lm(PBW~SO4+NO3+NH4, MyData)

Dimitri

On Tue, Apr 21, 2009 at 11:12 AM, Vemuri, Aparna <avemuri at epri.com> wrote:

David,
Thanks for the suggestions. No, I did not label my dependent variable "function".

My dependent variable PBW and all the independent variables are continuous variables. It is especially troubling since the order in which I input independent variables determines whether or not it gets a coefficient. ?Like I already mentioned, I checked the correlation matrix and picked the variables with moderate to high correlation with the independent variable. . So I guess it is not so na?ve to expect a regression coefficient on all of them.

Dimitri
model1<-lm(PBW~SO4+NO3+NH4), gives me the same result as before.

Bert:
?This is not homework. But I will remember to do my research before posting here.

Aparna


-----Original Message-----
From: David Winsemius [mailto:dwinsemius at comcast.net]
Sent: Monday, April 20, 2009 5:35 PM
To: Vemuri, Aparna
Cc: r-help at r-project.org
Subject: Re: [R] Fitting linear models


On Apr 20, 2009, at 7:26 PM, Vemuri, Aparna wrote:

I am not sure if this is an R-users question, but since most of you
here
are statisticians, I decided to give it a shot.

You can omit the unnecessary preambles.

I am using the lm() function in R to fit a dependent variable to a set
of 3 to 5 independent variables. For this, I used the following
commands:

model1<-lm(function=PBW~SO4+NO3+NH4)

Coefficients:
(Intercept) ? ? ? ? ?SO4 ? ? ? ? ?NO3 ? ? ?NH4
? ?0.01323 ? ? ?0.01968 ? ? ?0.01856 ? ? ? ? ? NA

and

model2<-lm(function=PBW~SO4+NO3+NH4+Na+Cl)

Coefficients:
(Intercept) ? ? ? ? ? ? ? SO4 ? ? ? ? ? ? ? ? ?NO3 ? ? ?NH4
Na ? ? ? Cl
-0.0006987 ? -0.0119750 ? -0.0295042 ? ?0.0842989 ? ?0.1344751
NA

In both cases, the last independent variable has a coefficient of NA
in
the result. I say last variable because, when I change the order of
the
variables, the coefficient changes (see below). Can anyone point me to
the reason R behaves this way? ?Is there anyway for me to force R to
use
all the variables? I checked the correlation matrices to makes sure
there is no orthogonality between the variables.

You really did not name your dependent variable "function" did you?
Please stop that.

Just a guess, ... since you have not provided enough information to do
otherwise, ... Are all of those variables 1/0 dummy variables? If so
and if you want to have an output that satisfies your need for
labeling the coefficients as you naively anticipate, then put "0+" at
the beginning of the formula or "-1" at the end, so that the intercept
will disappear and then all variables will get labeled as you expect.

--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT

--
Dimitri Liakhovitski
MarketTools, Inc.
Dimitri.Liakhovitski at markettools.com