# Questions tagged [intercept]

The intercept in regression-type models is the value of the Y variable when all X variables are 0.

59 questions
Filter by
Sorted by
Tagged with
171k views

### When is it ok to remove the intercept in a linear regression model?

I am running linear regression models and wondering what the conditions are for removing the intercept term. In comparing results from two different regressions where one has the intercept and the ...
67k views

### Removal of statistically significant intercept term increases $R^2$ in linear model

In a simple linear model with a single explanatory variable, $\alpha_i = \beta_0 + \beta_1 \delta_i + \epsilon_i$ I find that removing the intercept term improves the fit greatly (value of $R^2$ ...
68k views

### When forcing intercept of 0 in linear regression is acceptable/advisable [duplicate]

I have a regression model to estimate the completion time of a process, based on various factors. I have 200 trials of these processes, where the 9 factors being measured vary widely. When I perform a ...
8k views

### Removing intercept from GLM for multiple factorial predictors only works for first factor in model

I am running a binomial logistic regression with a logit link function in R. My response is factorial [0/1] and I have two multilevel factorial predictors - let's call them $a$ and $b$ where $a$ has 4 ...
66k views

### Intercept term in logistic regression

Suppose we have the following logistic regression model: $$\text{logit}(p) = \beta_0+\beta_{1}x_{1} + \beta_{2}x_{2}$$ Is $\beta_0$ the odds of the event when $x_1 = 0$ and $x_2=0$? In other words, ...
6k views

### The difference between with or without intercept model in logistic regression

I like to understand the difference between with or without intercept model in logistic regression Is there any difference between them except that with the intercept the coefficients regard the log(...
3k views

### Why is the intercept in multiple regression changing when including/excluding regressors?

I have a seemingly naive question regarding the interpretation of the intercept in multiple regression. What I found several times is something like this: The constant/intercept is defined as the ...
6k views

### Regression through the origin

We have the following points: $$(0,0)(1,51.8)(1.9,101.3)(2.8,148.4)(3.7,201.5)(4.7,251.1) \\ (5.6,302.3)(6.6,350.9)(7.5,397.1)(8.5,452.5)(9.3,496.3)$$ How can we find the best fitting line $y=ax$ ...
14k views

### Reason for not shrinking the bias (intercept) term in regression

For a linear model $y=\beta_0+x\beta+\varepsilon$, the shrinkage term is always $P(\beta)$. What is the reason that we do not shrink the bias (intercept) term $\beta_0$? Should we shrink the bias ...
128 views

### Both variables of my GLMM output are significant. Don't know how to interpret it?

This is more of an interpretation question than anything. I have run a GLMM with two fixed factors (both of which have two levels) and two random factors. The outputs from the model are as such: <...
4k views

### Ways of comparing linear regression intercepts and slopes?

I'm a little bit confused about this, so any help would be appreciated! Let's say I have a repeated-measures design in which participants take part in a task where they have to rate the ...
16k views

### Importance of the bias node in neural networks

I'm curious to know how important the bias node is for the effectiveness of modern neural networks. I can easily understand that it can be important in a shallow network with only a few input ...
10k views

### Why would one suppress the intercept in linear regression?

In a number of statistical packages including SAS, SPSS and maybe more, there is an option to "suppress the intercept". Why would you want to do that?
3k views

### Use squared correlation in regression without intercept [duplicate]

If I want to compare the goodness-of-fit of two regression models, with and without intercept, is it valid to compare the squared correlation coefficient between the fitted values and the data? Since ...
3k views

### Should I keep a non-significant intercept in a GARCH model?

I've estimated an ARMA-GARCH model. All the parameters except the intercept ($\omega$) in the GARCH part are significant. So I tried to estimate the model again imposing that $\omega = 0$. I compared ...
8k views

### Deliberately fitting a model without intercept [duplicate]

Is there a situation in which the mean of a Y variable is not 0 (e.g. not standardized), but we would still fit a regression model without intercept? It would yield a worse fitting model, so is there ...
3k views

### What are the uses and pitfalls of regression through the origin? [duplicate]

Spuriously high R-squared is one of the pitfalls of regression through the origin (i.e. zero-intercept models). If the predictors do not contain zeroes, then is it an extrapolation? What are the uses ...
55k views

### Why are bias nodes used in neural networks?

Why are bias nodes used in neural networks? How many you should use? In which layers you should use them: all hidden layers and the output layer?
11k views

### How to treat categorical predictors in LASSO

I am running a LASSO that has some categorical variable predictors and some continuous ones. I have a question about the categorical variables. The first step I understand is to break each of them ...
7k views

### Convert 'intercept/drift' term to 'constant' term in arima/auto.arima functions, in case of higher orders - R

suppose for a time series, the auto.arima output is: ...
12k views

### Logistic regression intercept representing baseline probability

In a linear regression, when you standardize your numeric variables, the resulting intercept has the same value as the mean of your sample. Is there any way in a logistic regression, with numeric ...
6k views

### What is the reason for not including an intercept term in AR and ARMA models?

In econometric literature it is usually argued that in case of estimating an equation, an intercept term must be always included regardless of its statistical importance because removing the constant ...
3k views

### Confused about 0 intercept in logistic regression in R

I'm exploring the effects of removing the intercept in a logistic regression model. Assume a model: $$logit(Y = 1) = \beta_1 x + \beta_2z + 0$$ with $x$ and $z$ being categorical variables with 2 ...
291 views

### Is it possible to interpret regression output omitting the intercept?

Is it possible to interpret regression output when omitting the intercept? Can this omission be justified?
2k views

### a regression through the origin

Why do a pair of variables with no significant correlation and no significant regression intercept and slope, have a highly significant regression with high adjusted $R^2$ when the regression is ...
97 views

### Computation of the intercept in logistic regression model

I'm trying to understand the way the odds of the reference groups are computed. Let's consider an example from this paper. Data can be summarised in the table: The reference group is Older and New. ...
10k views

### Understanding the intercept value in a multiple linear regression with categorical values

I'm failing to understand the value of the intercept value in a multiple linear regression with categorical values. Taking the "warpbreaks" data set as an example, when I do: ...
6k views

### What does the formula y ~ x + 0 in R actually calculate?

What is the statistical difference between doing a linear regression in R with the formula set to y ~ x + 0 instead of ...
2k views

### VAR models in R: Constant, Trend, Constant+Trend, None

I currently apply a VAR models with the vars package in R. There are the options to select "both", "none", ...
251 views

### Different usage of the term "Bias" in stats/machine learning

I think I've seen about 4 different usages of the word "bias" in stats/ML, and all these usages seem to be non-related. I just wanted to get clarification that the usages are indeed non-...
405 views

### Significance of intercept (as portrayed via an R formula)

I'm new to statistics in general (but a very seasoned developer). I'm trying to grasp why it seems like there's a lot of consideration given to intercepts, at least where it comes to models. For ...
23k views

### What exactly is the standard error of the intercept in multiple regression analysis?

I understand that in multiple regression analysis, for each independent variable, you would graph dependent variable vs independent variable and you would make a line of best fit and calculate the ...
2k views

### Fitting simple linear regression with no intercept

Say we fit a simple linear regression without the intercept term. I know this is inadvisable for the most part, unless there are some situations where it is reasonable to assume that when $x=0$, $y$ ...