We changed our privacy policy. Read more.

Questions tagged [intercept]

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

Filter by
Sorted by
Tagged with
0
votes
0answers
23 views

Logistic Regression, ''Intercept'' instead of a Category

I am currently trying to analyse the effect of an ilness (0= no infection, 1= infection) on 9 different Genotypes in plants. My Dataframe consist of 2 colums Genotyp and Infection. I have 459 rows for ...
0
votes
1answer
36 views

Understanding fixef() output of fixed effects coefficients

I have a panel data set with several ID's and each has a certain number of year observations. When I fit a fixed effects ...
1
vote
0answers
39 views

When you are running an analysis with only an intercept, does it make sense to include random subject and item intercepts?

Lets image a study where people get two shapes and are told to pick one. They each get 40 trials, each with a different shape/colour. There are 40 different pairs of shapes. There are 100 participants....
1
vote
1answer
22 views

Is computing the average of a ratio the correct approach, and how to do it with nested data?

In general, is computing the average of a ratio appropriate? And secondly, is the nested model below appropriate for doing this? Here is a data set created from the Iris data that resembles my ...
1
vote
0answers
35 views

How to decide if I should fit SARIMAx with or without intercept

I am trying to find the best SARIMAX model for my data, I am using auto_arima to find the order(ARMA and Seasonal) of the model. How do I decide whether or not I ...
0
votes
1answer
34 views

Compare intercept of logistics (mixed-effects) model to value other than 0

Is it possible to compare the intercept of a logistic mixed-effects model to a value other than 0? Specifically, I have two choice alternatives and try to predict choices. My intercept would then tell ...
0
votes
0answers
17 views

How to calculate the intercept (b) of a gaussian kernel support vector regression

I know the dual problem of an SVR problem is given as: where \alpha_i and \alpha^*_i are dual variables and they are also decision variables in the above problem. \epsilon specifies the epsilon-tube ...
2
votes
1answer
129 views

If I consider the fixed factor as a random slope, the p-value changes from p<0,05 to p>0,05

I'm having a hard time trying to understand the differences between these two models and why the first one shows correlation (p-value < 0,05) but the other one doesn´t (p-value > 0,05). I would ...
4
votes
1answer
64 views

Consistency of OLS when no intercept

Suppose I have a model $y_i = \beta_0 + \beta_1 x_i + e_i$ but instead I estimate $y_i = \beta_1 x_i + u_i$ using OLS. That is, I ignore the intercept. Working out the algebra, based on this post, we ...
0
votes
0answers
22 views

What is the difference (if any) when talking about bias from a ML point of view and from a DL point of view

I'm reading around Machine Learning and Deep Learning and can't seem to understand the difference or similarity between bias in both. If we look at the simplest linear regression formula y = b0 + b1x1 ...
2
votes
1answer
31 views

How to obtain a 0 intercept in quantile regression

Quantile regression models are a type of models that provide estimates of the quantiles of a response variable $y$ given a set of covariates $X$ in the form of a linear equation such as $$ y = \beta_0 ...
0
votes
0answers
38 views

VAR-model include constant or not?

I am estimating a var model with four variables: GDP, investemnt, inflation and unemployment. (all in growth rates). Now I estimated it once with a constant and one without. The model is not changing ...
0
votes
0answers
27 views

Simple linear regression model without intercept

I am a new beginner at linear regression. So here is my question: given that we have simple linear regression without the intercept: $$y_{i}=\beta x_{i}+\varepsilon_{i}$$ the question assumes that $\...
0
votes
0answers
13 views

Intercept in 2nd-stage Error Correction Model (ECM) regression -- yes or no?

When doing a two-step ECM regression, do we add an intercept in the 2nd stage regression? I've seen course notes that add an intercept in the ECM, but some do not, so I'm confused if I should include ...
0
votes
0answers
23 views

Is there a way to use the covariance matrix to find coefficients for multiple regression WITHOUT intercept?

Given: $$ y=\alpha + \beta x $$ The problem on how to get regression coefficients $\alpha, \beta_0, \beta_1,...,\beta_n$ from the covariance matrix is solved here: Is there a way to use the covariance ...
2
votes
1answer
47 views

Concerns about pre-trend stability testing

In this discussion, @Thomas Bilach well explains the equation to test pre-trend stability. $$ y_{kt} = \alpha_k + \lambda_t + \delta_{-2} d_{k,t-2} + \delta_{-1} d_{k,t-1} + \delta d_{kt} + \delta_{+1}...
0
votes
0answers
18 views

Different values for intercept estimate in linear regression

I'm reading about linear regression from two sources. In here: https://online.stat.psu.edu/stat415/lesson/7/7.3 the estimate for the intercept is just $\bar y$. However over here: https://www....
0
votes
0answers
11 views

Collinearity between the intercept and (logged) continuous variable: centering to fix it?

I have found a lot of information when there is collinearity between intercept and dummy variables. However, my collinearity diagnostics is showing a condition index > 30 (36) and it indicates ...
4
votes
1answer
45 views

Why is the intercept different in an AR(1) model compared to a lagged endogenous variable model? [closed]

In other words, why is that when estimating in EViews y = c ar(1) yields a different coefficient for c when compared to ...
0
votes
0answers
20 views

Simple linear regression without intercept - Expected Value and Variance Estimator (Slope) [duplicate]

I'm solving an exercise while studying for exam, I have been asked to find the estimator of simple linear model without intercept estimator, its expected value and variance. I got for the Estimator B1 ...
1
vote
1answer
56 views

Mixed model fails to converge - do I delete the random intercept or the random slope, and what does the variance of the random effects say?

I'm in the process of building my mixed models, and unfortunately I encountered a problem when creating the random effects structure. I have two random effects: ResponseId (i.e., participant number) ...
0
votes
1answer
42 views

Interpreting constant in regression with an interaction term

In a regression model with a single categorical exposure and no interaction term of the form: $y = \beta_0+\beta_1x_1$ the $\beta_0$ can be interpreted as the result in the reference group. So for a ...
0
votes
0answers
18 views

Confidence interval x-intercept

The x-intercept of a linear regression is -y.intercept/slope. If I wanted to obtain a confidence interval (CI) for a x-intercept of a linear regression, coud it be wrong to find the CI of y-intercept ...
2
votes
0answers
31 views

In R there is a problem of intercept and without intercept ,Pearson's Correlation does not follow! Why? (see the bolded resuls)

Xvec <- rnorm(200) Yvec <- 2.6*Xvec + rnorm(200) lmodxy <- lm(Xvec ~ Yvec) lmodyx <- lm(Yvec ~ Xvec) summary(lmodxy) Output ...
2
votes
2answers
149 views

How to correctly use I-Splines for monotone non-decreasing/ increasing regression?

I have the following data to which I want to fit a monotone non-decreasing spline. ...
0
votes
1answer
76 views

Test for comparing x-intercepts of two linear regression

I would like to know how to compare, and then calculate significant differences, if any, between the x-intercepts of two regression lines. Practially, I shoud compare the values of x when y=0. I know ...
2
votes
1answer
23 views

Uncovering the make up of the intercept in a generalized linear mixed model

I could use some help Finding the make up of the intercept in a generalized linear mixed model. FYI, I use a 2013 Macbook Pro with a 2.4 GHz dual-core intel chip, 8 GB of ram, macOS big sur 11.2.2, ...
14
votes
1answer
560 views

Why the does the intercept of my null model not equal the mean when I log transform the outcome variable? How do I interpret it?

I have an outcome variable that is right skewed, so I log transformed it. I made a null model with only the log-transformed outcome variable, but when I exponentiate the estimate, it does not equal ...
13
votes
5answers
232 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-...
0
votes
1answer
31 views

Logit model intercept use

I want to estimate a Logit model where the independent variables are binary and one of them is categorical, so the whole data set consists of dummy variables. First of all, I am puzzled whether I ...
0
votes
0answers
82 views

Using LIME without intercept term?

I'm playing with LIME to explain the prediction of a machine learning model. LIME trains a (locally weighted) linear surrogate model around a point of interest. The weights of that surrogate model are ...
0
votes
0answers
24 views

Ordinal regression model in R - multiple coefficients appearing for only one dependent variable. Can someone help me analyze?

I am running an ordinal logistic regression model in R (with an ordinal dependent variable). For my model I am also only including one primary independent variable (which is also ordinal). However, ...
2
votes
1answer
24 views

What does c refer to in AR(p) and MA(q) model mathematical definitions?

What exactly does c represent in these formulas defining AR(p) and MA(q) models? MA(q): (https://otexts.com/fpp2/MA.html) AR(p): https://otexts.com/fpp2/AR.html
0
votes
0answers
12 views

Interpret significant intercept

I performed Wald tests on my GEE model (in fact, using anovas on nested models) and got no significant variables. Since I could not run a model without any independent variable I left distance in the ...
0
votes
0answers
19 views

Syntax for a random effect in an R regression - not sure if nested, and how to express?

I am running an ordinal regression for an experiment I have conducted, where the DV is ratings on a 5-point scale, and the predictors are the type of item, the type of participant (native speaker/L2/...
1
vote
1answer
35 views

Random effect coefficient: actual coefficient or deviation from main fixed effect?

This is a very simple question, but I'm starting to doubt myself: I have a mixed model which I estimate in Matlab with fitglm ...
0
votes
0answers
15 views

Problems with multicollinearity tests of no intercept models

i have an $\mathrm{AR}(1)$ model in R, $y_t \sim y_{t-1} + X_{1,t}+ \cdots+ X_{n,t}$ with no intercept and i want calculate some individual multicolinearity tests for each variable in the model. The ...
4
votes
2answers
434 views

Why does removing the constant term prevent the dummy variable trap? [duplicate]

I understand that if you have a dummy variable with $m$ categories that you should include $m-1$ categories in order to avoid perfect collinearity between regressors. However I don't understand why ...
0
votes
1answer
46 views

Adding drift to an ARIMA(0,1,1) (0,1,1) model in R

I'm trying to add drift to my ARIMA(0,1,1)(0,1,1) model in R, however R is giving me the error message, Warning message: In Arima(insample, order = c(0, 1, 1), seasonal = c(0, 1, 1), include.drift = ...
4
votes
4answers
167 views

Why is the intercept different from the mean of Y when X=0?

I was hoping to find here a solution to some aspects of linear regression I had trouble understanding. Let's take an example of regression with the following variables: $y:\:$ depression (continuous)...
1
vote
0answers
32 views

Components of the intercept within regression and colon interaction (:)

I'm trying to figure out which elements are part of the intercept within a regression model characterized by colon interaction (:). This is the model: Y ~ A*B + A:B:C The independent variables are: <...
0
votes
0answers
34 views

Independent variable is correlated with intercept, creating singularities

I am building a logistic model with about 20 variables. I have used the following code: `fullmod = glm(cancer ~ B_SEX+BLINE_AGE_AT_BASELINE+B_BMI+B_chro+B_fdrc+B_hrt+B_LMET+ B_MET+B_FV+B_EDU+B_INC+...
2
votes
2answers
846 views

When forcing intercept to zero, how R-squared is changed? [duplicate]

I have some questions. In a linear model, I want to force intercept to zero. The program (I used JMP) does not provide R-squared when intercept becomes zero. So, I calculated R-squared by myself by ...
1
vote
0answers
42 views

Understanding the intercept in an unadjusted logistic regression

I have performed an unadjusted logistic regression using weights (obtained via genetic matching) as below. I am using the survey package to make working with the ...
0
votes
0answers
24 views

Intercept in a dynamic panel model

I have been taught that including fixed/random effects in a dynamic panel model yields inconsistent estimates when using OLS and hence motivates the usage of other estimation methods. However, does ...
-1
votes
1answer
44 views

Is the intercept fit differently for each regressor in Multiple Linear Regression?

is the intercept B0 in y = B0 + B1X1 + .... fit differently for every feature x1. Is it different for every feature coefficient or the same for all feature coefficients and why so?
0
votes
0answers
33 views

Interpreting estimates in a Poisson regression

I know similar questions have already been answered but in this particular case I need some additional help. I am working with this data set: https://github.com/proback/BeyondMLR/blob/master/data/...
2
votes
1answer
90 views

A queston regarding the meaning of the intercept in regression

Suppose we have a dataset where the indepedent variable $x$ is the work experience in years of an employee and $y$ is his salary in dollars. Such a dataset could consist of the following elements $$(...
5
votes
2answers
535 views

'Size' of intercept at linear regression

I have a question about this table. Why does the constant (intercept) change so dramatically from Model 1 to Model 2?

1
2 3 4 5
7