R linear model missing coefficient
I try to implement a linear model on categorical data.
My dataset is composed of categorical predictors and my target is a quantitative value.
The linear model works :
linearMod <- lm(Y~. -1, data=df_filter)
When I extract the coefficients :
linearMod$coefficients
I get a long list of Variables-Modalities Coefficients.
Some of the modalities have a NA value ... which is just fine, and I understand it.
However, Some Variable-modalities does not appear in the output of the linearMod$coefficients.
I could understand if they were set to "NA", but not having them in this list looks strange to me.
Question : Is this behaviour is normal, and if so what is the explanation behind this phenomenon?
Alternative question : I've read somewhere that there are many ways to do dummy coding ... but no way to find it anymore... do you have any Url / link for that ?
Thanks for your answers.
r coefficients linearmodels
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
|
show 1 more comment
I try to implement a linear model on categorical data.
My dataset is composed of categorical predictors and my target is a quantitative value.
The linear model works :
linearMod <- lm(Y~. -1, data=df_filter)
When I extract the coefficients :
linearMod$coefficients
I get a long list of Variables-Modalities Coefficients.
Some of the modalities have a NA value ... which is just fine, and I understand it.
However, Some Variable-modalities does not appear in the output of the linearMod$coefficients.
I could understand if they were set to "NA", but not having them in this list looks strange to me.
Question : Is this behaviour is normal, and if so what is the explanation behind this phenomenon?
Alternative question : I've read somewhere that there are many ways to do dummy coding ... but no way to find it anymore... do you have any Url / link for that ?
Thanks for your answers.
r coefficients linearmodels
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
2
the default is to use one of the levels as the baseline, so it doesn't need its own variable - the model is telling you how things change with respect to a level of your categorical variables. Generally, you would need a strong justification to remove the intercept as you have done
– jenesaisquoi
Nov 17 '18 at 14:50
you could refer tomodel.matrixorcontrastsor others, my R is a bit rusty, I think dummy encoding, aka. one-hot encoding is a pretty standard procedure, you just just have columns of 0/1 for absence/presence of variables, but you are probably right that people have variations with weighted factors or some such thing
– jenesaisquoi
Nov 17 '18 at 14:53
Should I understand that some "modalities" have no impact ? - If this is true, then I'm a bit surprised as the missing modalities are very often present. This looks strange. In between I've tryed a one hot encoding and then run the linear model, and the missing coeffs are much less present. Note: I've removed the intercept for test. Originally the "-1" was not there !
– G. Xib
Nov 17 '18 at 15:13
Thanks "Je ne sais quoi" :) I'm gonna dig on the Model.matrix / contrast feature in the lm model.
– G. Xib
Nov 17 '18 at 15:17
well, no, that's not what it means. The impact of the "missing" levels is the baseline, eg. all other variables zeroed out. It would probably benefit you to read a quick tutorial on anova's or regression on categorical variables, eg. sthda.com/english/articles/40-regression-analysis/…
– jenesaisquoi
Nov 17 '18 at 15:25
|
show 1 more comment
I try to implement a linear model on categorical data.
My dataset is composed of categorical predictors and my target is a quantitative value.
The linear model works :
linearMod <- lm(Y~. -1, data=df_filter)
When I extract the coefficients :
linearMod$coefficients
I get a long list of Variables-Modalities Coefficients.
Some of the modalities have a NA value ... which is just fine, and I understand it.
However, Some Variable-modalities does not appear in the output of the linearMod$coefficients.
I could understand if they were set to "NA", but not having them in this list looks strange to me.
Question : Is this behaviour is normal, and if so what is the explanation behind this phenomenon?
Alternative question : I've read somewhere that there are many ways to do dummy coding ... but no way to find it anymore... do you have any Url / link for that ?
Thanks for your answers.
r coefficients linearmodels
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
I try to implement a linear model on categorical data.
My dataset is composed of categorical predictors and my target is a quantitative value.
The linear model works :
linearMod <- lm(Y~. -1, data=df_filter)
When I extract the coefficients :
linearMod$coefficients
I get a long list of Variables-Modalities Coefficients.
Some of the modalities have a NA value ... which is just fine, and I understand it.
However, Some Variable-modalities does not appear in the output of the linearMod$coefficients.
I could understand if they were set to "NA", but not having them in this list looks strange to me.
Question : Is this behaviour is normal, and if so what is the explanation behind this phenomenon?
Alternative question : I've read somewhere that there are many ways to do dummy coding ... but no way to find it anymore... do you have any Url / link for that ?
Thanks for your answers.
r coefficients linearmodels
r coefficients linearmodels
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
asked Nov 17 '18 at 14:45
G. XibG. Xib
12
12
2
the default is to use one of the levels as the baseline, so it doesn't need its own variable - the model is telling you how things change with respect to a level of your categorical variables. Generally, you would need a strong justification to remove the intercept as you have done
– jenesaisquoi
Nov 17 '18 at 14:50
you could refer tomodel.matrixorcontrastsor others, my R is a bit rusty, I think dummy encoding, aka. one-hot encoding is a pretty standard procedure, you just just have columns of 0/1 for absence/presence of variables, but you are probably right that people have variations with weighted factors or some such thing
– jenesaisquoi
Nov 17 '18 at 14:53
Should I understand that some "modalities" have no impact ? - If this is true, then I'm a bit surprised as the missing modalities are very often present. This looks strange. In between I've tryed a one hot encoding and then run the linear model, and the missing coeffs are much less present. Note: I've removed the intercept for test. Originally the "-1" was not there !
– G. Xib
Nov 17 '18 at 15:13
Thanks "Je ne sais quoi" :) I'm gonna dig on the Model.matrix / contrast feature in the lm model.
– G. Xib
Nov 17 '18 at 15:17
well, no, that's not what it means. The impact of the "missing" levels is the baseline, eg. all other variables zeroed out. It would probably benefit you to read a quick tutorial on anova's or regression on categorical variables, eg. sthda.com/english/articles/40-regression-analysis/…
– jenesaisquoi
Nov 17 '18 at 15:25
|
show 1 more comment
2
the default is to use one of the levels as the baseline, so it doesn't need its own variable - the model is telling you how things change with respect to a level of your categorical variables. Generally, you would need a strong justification to remove the intercept as you have done
– jenesaisquoi
Nov 17 '18 at 14:50
you could refer tomodel.matrixorcontrastsor others, my R is a bit rusty, I think dummy encoding, aka. one-hot encoding is a pretty standard procedure, you just just have columns of 0/1 for absence/presence of variables, but you are probably right that people have variations with weighted factors or some such thing
– jenesaisquoi
Nov 17 '18 at 14:53
Should I understand that some "modalities" have no impact ? - If this is true, then I'm a bit surprised as the missing modalities are very often present. This looks strange. In between I've tryed a one hot encoding and then run the linear model, and the missing coeffs are much less present. Note: I've removed the intercept for test. Originally the "-1" was not there !
– G. Xib
Nov 17 '18 at 15:13
Thanks "Je ne sais quoi" :) I'm gonna dig on the Model.matrix / contrast feature in the lm model.
– G. Xib
Nov 17 '18 at 15:17
well, no, that's not what it means. The impact of the "missing" levels is the baseline, eg. all other variables zeroed out. It would probably benefit you to read a quick tutorial on anova's or regression on categorical variables, eg. sthda.com/english/articles/40-regression-analysis/…
– jenesaisquoi
Nov 17 '18 at 15:25
2
2
the default is to use one of the levels as the baseline, so it doesn't need its own variable - the model is telling you how things change with respect to a level of your categorical variables. Generally, you would need a strong justification to remove the intercept as you have done
– jenesaisquoi
Nov 17 '18 at 14:50
the default is to use one of the levels as the baseline, so it doesn't need its own variable - the model is telling you how things change with respect to a level of your categorical variables. Generally, you would need a strong justification to remove the intercept as you have done
– jenesaisquoi
Nov 17 '18 at 14:50
you could refer to
model.matrix or contrasts or others, my R is a bit rusty, I think dummy encoding, aka. one-hot encoding is a pretty standard procedure, you just just have columns of 0/1 for absence/presence of variables, but you are probably right that people have variations with weighted factors or some such thing– jenesaisquoi
Nov 17 '18 at 14:53
you could refer to
model.matrix or contrasts or others, my R is a bit rusty, I think dummy encoding, aka. one-hot encoding is a pretty standard procedure, you just just have columns of 0/1 for absence/presence of variables, but you are probably right that people have variations with weighted factors or some such thing– jenesaisquoi
Nov 17 '18 at 14:53
Should I understand that some "modalities" have no impact ? - If this is true, then I'm a bit surprised as the missing modalities are very often present. This looks strange. In between I've tryed a one hot encoding and then run the linear model, and the missing coeffs are much less present. Note: I've removed the intercept for test. Originally the "-1" was not there !
– G. Xib
Nov 17 '18 at 15:13
Should I understand that some "modalities" have no impact ? - If this is true, then I'm a bit surprised as the missing modalities are very often present. This looks strange. In between I've tryed a one hot encoding and then run the linear model, and the missing coeffs are much less present. Note: I've removed the intercept for test. Originally the "-1" was not there !
– G. Xib
Nov 17 '18 at 15:13
Thanks "Je ne sais quoi" :) I'm gonna dig on the Model.matrix / contrast feature in the lm model.
– G. Xib
Nov 17 '18 at 15:17
Thanks "Je ne sais quoi" :) I'm gonna dig on the Model.matrix / contrast feature in the lm model.
– G. Xib
Nov 17 '18 at 15:17
well, no, that's not what it means. The impact of the "missing" levels is the baseline, eg. all other variables zeroed out. It would probably benefit you to read a quick tutorial on anova's or regression on categorical variables, eg. sthda.com/english/articles/40-regression-analysis/…
– jenesaisquoi
Nov 17 '18 at 15:25
well, no, that's not what it means. The impact of the "missing" levels is the baseline, eg. all other variables zeroed out. It would probably benefit you to read a quick tutorial on anova's or regression on categorical variables, eg. sthda.com/english/articles/40-regression-analysis/…
– jenesaisquoi
Nov 17 '18 at 15:25
|
show 1 more comment
0
active
oldest
votes
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53352278%2fr-linear-model-missing-coefficient%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53352278%2fr-linear-model-missing-coefficient%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
2
the default is to use one of the levels as the baseline, so it doesn't need its own variable - the model is telling you how things change with respect to a level of your categorical variables. Generally, you would need a strong justification to remove the intercept as you have done
– jenesaisquoi
Nov 17 '18 at 14:50
you could refer to
model.matrixorcontrastsor others, my R is a bit rusty, I think dummy encoding, aka. one-hot encoding is a pretty standard procedure, you just just have columns of 0/1 for absence/presence of variables, but you are probably right that people have variations with weighted factors or some such thing– jenesaisquoi
Nov 17 '18 at 14:53
Should I understand that some "modalities" have no impact ? - If this is true, then I'm a bit surprised as the missing modalities are very often present. This looks strange. In between I've tryed a one hot encoding and then run the linear model, and the missing coeffs are much less present. Note: I've removed the intercept for test. Originally the "-1" was not there !
– G. Xib
Nov 17 '18 at 15:13
Thanks "Je ne sais quoi" :) I'm gonna dig on the Model.matrix / contrast feature in the lm model.
– G. Xib
Nov 17 '18 at 15:17
well, no, that's not what it means. The impact of the "missing" levels is the baseline, eg. all other variables zeroed out. It would probably benefit you to read a quick tutorial on anova's or regression on categorical variables, eg. sthda.com/english/articles/40-regression-analysis/…
– jenesaisquoi
Nov 17 '18 at 15:25