Questions tagged [intercept]

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

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89 views

Extreme estimated coefficients

Below is a part of my summary(lmfit). It shows a very extreme intercept. I can successfully calculate some fitted values based on the coefficients. However as ...
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0answers
94 views

How to obtain OLS estimators of the slopes using the deviations from their means

In my econometric course we were given the exercise to show that the OLS estimators of the slopes can be derived by converting the data to deviations from their means. Furthermore, I'm also supposed ...
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1answer
1k views

Conjoint Analysis - Incorporating individual-specific intercept

We are new here, and have recently gotten a question that we have very much been struggling to answer. It is concerning a question regarding a conjoint analysis in which we have to incorporate an ...
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4answers
914 views

Does the intercept in a logistic regression capture the unobserved effects?

Theoretically, does the intercept term in a logistic regression model capture all unobserved effects? In other words, in a logistic regression model with a perfect fit (i.e. all relevant variables ...
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1answer
899 views

Determine the original standard error of the intercept in a regression estimated with standardized covariates

The present question is related to these two questions: Converting standardized betas back to original variables and Intercept from standardized coefficients in logistic regression The R package I am ...
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Linear regression with constraint [duplicate]

Can someone explain how to mathematically perform linear regression on some data while constraining the fit line to pass through the $(0,0)$ point?
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127 views

What is the role of an intercept in testing the linear hypothesis b1 = -b2?

EDIT2: Possibly the short version of the question is just how would I test cat2 = cat3 in the STATA example in the link below I would like to test the hypothesis that $\beta_{typeprof} = -\beta_{...
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2answers
9k 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 ...
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1answer
764 views

What is the meaning of the intercept in regression with binary explanatory variables?

I have the following model: $y_t = \alpha + \beta_1 x_{t-1} + \beta_2 z_{t-1} + \varepsilon_t$, where my dependent variable $y_t$ is the log return of a stock (e.g., GM) and $x_{t-1}$ and $z_{t-1}$ ...
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2answers
5k 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 ...
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2answers
16k 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 ...
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1answer
125 views

Meaning of Intercept and what the intercept should be with no measurement error?

I'm going into University this year, Engineering to be more specific and I was given an assignment over the summer about regression. (Something I have no knowledge about) Basically, in my questions I ...
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376 views

R - Manually Adding Intercept to glmnet Ridge Regression [closed]

Is there a way to manually add an intercept term manually into the glmnet function of R rather than using the built-in intercept ...
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1answer
277 views

fixing the intercept in multiple regression

I am interested in using OLS regression to model the relationship between two predictors (X1 and X2) and a response variable (Y). However, for theoretical reasons I know that when X1 = 0, Y must also ...
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3answers
15k 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 ...
4
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1answer
346 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 ...
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1answer
54 views

How to adjust lm Estimates and SE relative to the Intercept

I have a question regarding the output from lm in this table below: ...
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854 views

standard error of slope and intercept estimate

In the linear model $\mathbf{Y} = \mathbf{X}\beta + \epsilon$, where $\epsilon \sim N(0, \sigma^2 \mathbb{I})$, it is known the the standard error of the estimator $\hat{\beta}$ is given by $$Var(\...
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Slope testing for regression lines between non-normal explanatory and response variables

I would like to estimate a regression line between my explanatory and response variables. The explanatory and the response variables are (paired) instrumental measures of the same thing under ...
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1answer
59k views

Doing multiple regression without intercept in R (without changing data dimensions)

I am trying to calculate multiple regression in R without intercept. My data is as follow: ...
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1answer
668 views

Newey West standard errors in regression model without constant

I'm estimating $y_i= \beta_1 \times x_{1i} + \varepsilon_i$ on a time series on $y$ and $x$, so in presence of heteroskedasticity and autocorrelation. My model does not include any intercepts. Are ...
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1answer
1k views

How to Estimate the Error Term in a Heteroscedastic Model with Regression Through the Origin

Suppose we have a NO INTERCEPT model, $$y_i=\beta x_i+e_i$$ where $e_{i}$ follows a N(0,$\sigma^2 x_i^h$), so $e_i$ is equal in distribution to $e_{0i} x_i^{\frac{h}{2}}$, where $e_{0i}$ follows a N(...
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1answer
88 views

Get overall tendency in the dependent variable, beyond the effect of the independent variable [closed]

Hypothetical data-set: There's a dependent binomial variable 'happiness', with $0 = unhappy$ and $1 = happy$. Then there's an independent categorical variable 'color' with the levels $blue, red, ...
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470 views

What does intercept means in multiple glm?

I am wondering what exactly means the intercept in the following? Is it a mean? I was told that is the mean of first category. is it? ...
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1answer
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 ...
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1answer
2k views

How do you set your own intercept in SPSS? [duplicate]

I am trying to specify the constant in a regression model using SPSS. Does anyone have an idea on how to do this?
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1answer
245 views

Zero-intercept poisson regression model predicts better than a model with an intercept?

I have read some blogs/articles saying that intercept should not be suppressed. Recently, I used glmm.admb to model a ZIP (Zero-inflated Poisson) model which is giving better results without an ...
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156 views

Unit Root Confirmed- How generate the new series with Diff, Trend,Intercept

I have a data series that became stationary at first difference and including both Trend and Intercept. I know how to generate a new variable using first differencing (Eviews) but how should I cater ...
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586 views

Produce a GLM intercept that does not include reference levels for categorical variables? [duplicate]

I realize that a similar question to this has been asked, but it was not ultimately resolved. I have tried the suggestions posted to that question here, but have had no success. I am using the ...
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1answer
4k views

impose an intercept on lm in r [duplicate]

I am converting a high-dimensional model to a lower dimensional model by fitting a sliding window of it to a linear (parametric) model and looking at the evolution of parameter values over time. I'm ...
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1answer
2k views

What does the intercept correspond in the Anova() function in R?

I've been struggling to understand what the intercept sums of squares and p-value correspond to when I run a one-way ANOVA with Type "III" sums of squares using the Anova() function in the car package....
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1answer
908 views

GMM estimation of linear regression with intercept restriction

Say I have a time series regression as follows: $$y_t = a_i + \beta_i x_t + \varepsilon_t^i \ \ ; \ \ t = 1, 2, \cdots, T \ \ \text{for each } i$$ Now say I impose the following restriction on the ...
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1answer
56 views

Size for Beta Coefficient

I have one variable (x), I am simply trying to understand the relationship between (x,y). I run two regression models, first model is predicted by removing the intercept and the second including the ...
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1answer
2k views

linear regression intercept does not match

I have done a linear regression in R, using glm function. The calculated intercept says 0.98, but when I plot it, it does not seem to hit the estimated intercept on Y axis. Its far below. Here are my ...
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2answers
2k views

Why does the adjusted r-squared of this model improve with addition of a statistically insignificant variable?

I stumbled on this while doing MLR, and was curious as to why this happens. The adjusted R-squared is (if I understand correctly) supposed to be a way of comparing the predictive quality of models ...
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3answers
3k views

How does the inclusion of an intercept change the variability of the residual?

I want to use the variability of the residual as a measure M and then test whether M is higher or lower after some event. However, I estimate separate regression before and after the event to obtain ...
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1answer
864 views

Why and how does the inclusion of random effects in mixed models influence the fixed-effect intercept term?

The question is best illustrated by this example which uses a dataset (in library faraway) and lme4 library (both in R). This ...
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2answers
1k views

Removing the intercept term in a dynamic regression justified?

I'm trying to build a cross-sectional prediction model (dynamic panel) with the following form: (including a LDV) $Y_{i,t+1}=a+bY_{i,t}+cX_{i,t}+e_{i,t+1}$ As the sample contains for example ...
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0answers
35 views

Does it make sense to only drop a specific level of a categorical variable? [duplicate]

I don't have SAS and the dataset with me, so I made up this table (from my memory). Basically this is what I got: After deciding to leave the variable $age$ and $risk$ in my model, I created this ...
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0answers
179 views

Groups in linear regression with different intercepts. How do I find the differing variable?

This is more of a conceptual question. I have a coefficient estimate of .80 in a linear regression model with one IV and one dependent variable. However, plotting the data I see distinct groups, ...
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1answer
1k views

Intercept from standardized coefficients in logistic regression

I have fit a logistic regression model with original y and standardized x variables. Slope coefficients can be easily converted back to their original scale by $\beta^*_j/\sigma_{x_j}$ where $\beta^*...
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8answers
57k 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 ...
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3answers
23k views

Interpreting coefficients in a logistic regression model with a categorical variable having more than 2 levels

There is quite some content online interpreting odds in a logistic model with a dichotomous predictor. My problem is understanding coefficients when there are more than 2 levels for a categorical ...
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1answer
2k views

Logistic regression: Strange standard errors from glm() in R

To my surprise I found that standard errors and thus Wald confidence intervals became smaller when I removed the intercept from a simple logistic regression model, using ...
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1answer
2k views

Two intercept coefficients in glmnet output

I am not sure I understand why glmnet returns 2 intercepts in its result. If model matrix already has intercept column, why do we need another intercept for the model? ...
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2answers
2k views

Confidence interval for the intercept in logistic regression

Some major commercial statistical packages (e.g., SPSS) do not report a CI for the intercept term in logistic regression. [Based on answer below R does provide CI for intercept] Why might confidence ...
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3answers
54k 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, ...
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0answers
111 views

Interpretation of coefficient sign change and order of terms

I have a logistic regression with data that are kind of like this: ...
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1answer
12k views

Interpretation of intercept of a regression line in time series data

Does the intercept value of a regression equation have meaning in a time series dataset? Suppose I have a dataset: the intercept is 27.512, but we are 95 percent sure that the intercept is between -...
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1answer
608 views

What does it mean to have two intercepts? [closed]

Suppose I am modeling the sales for multiple products for multiple stores. What is the difference between: \begin{align} \text{Sales} &= \beta_{0}(\text{Intercept × Store}) +\beta_{1}(\text{...