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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Extremely high intercept from Elastic Net

I am using the ElasticNet library from sklearn. I am using one predictor which takes values in the range [827.559, 827.5625]. When I fit the model using this ...
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Why are the intercept values of my QR non-monotonic?

I was led to believe that when conducting quantile regression you would expect intercept values to increase as you go up quantiles. However, I have run a quantile regression and the intercepts are as ...
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Back calculate intercept from multivariable COVID-19 logistic regression model

I am interested in creating a web tool to predict the absolute risk of in-hospital death from a published risk model of COVID-19 patients. Is it possible to estimate the intercept from the ...
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I don't understand RidgeCV's fit_intercept, and how to use it for my data

Alright, I have an assignment that makes me calculate weights for a function with different terms. At first, I thought I might just leave the weight for the term $1$ out, and instead use the intercept....
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Is the random slope for a binary, categorical variable in a mixed model also reported in reference to one of the categories?

I'm wondering if I should be interpreting an estimated random slope for a binary categorical variable in the same way that I should be interpreting it if it were a fixed effect. That is, is it ...
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Meta-analysis using mixed-effects model with moderators where response variable is effect size - is it appropriate to remove the y-intercept?

Greetings fellow statisticians, We're working on a meta-analysis looking at the effect of mindfulness based interventions [MBI] on self-compassion. We've computed Hedges' ...
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Calculate/understand the total sample mean of a binary dependent variable from the fixed effect estimates of a model?

was hoping you could help me to understand the model that I have just fit; in particular, I'm interested in the calculus of how the fixed estimates fit back together to make estimates for total sample ...
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Test if intercepts in ancova model are significantly different in R

I ran a model explaining the weight of some plant as a function of time and trying to incorporate the treatment effect. weight ~time + treatment The model looks ...
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Why does using the pnorm function on the intercept estimate of a binomial regression recover the mean of the dependent variable?

I've fit a series of mixed effect models with the lme4 package in r on a set of binomial outcome variables (1: the event happened, 2: it did not). The fixed effect specification is intercept only, and ...
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2answers
30 views

Linear regression when a non-zero intercept is theoretically implausible

How should I think of a linear model with a positive intercept when, theoretically, the intercept has to be zero? Think of the following example: we are modeling how many birds does a feral cat hunt ...
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How to obtain a distribution of the unobserved time-invariant fixed effects in a fixed-effects regression?

I am running a fixed-effects unbalanced panel regression using the plm package: ...
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26 views

When using Lasso and calling coefficients (.coef_) which is the coefficient of the constant? [closed]

By calling .coef on the Lasso model built, there are only numbers corresponding to the coefficients. These coefficients are supposed to match, say, the columns of the pandas dataframe given as input. ...
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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. ...
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Issue about confidence interval on OLS intercept

Let us assume this simple linear model: $Y|X=\beta_0+\beta_1X+\epsilon $ where $X \sim N(\mu,\sigma^2)$ and $\epsilon \sim N(0,\sigma_{\epsilon}^2)$ Suppose also that $X$ and $\epsilon$ have all ...
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Can an random walk ARIMA model have a nonzero constant term?

From what I'm reading it seems like a nonstationary ARIMA model can have a nonzero constant term. I'm not understanding how this can happen. Suppose we have an AR(1) model where $\phi_1=1$. If p is ...
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Why does the constant term have a P value in statistical programs?

I notice when running regressions in programs such as Stata that the constant term has a p value. Why and what does this p value represent?
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265 views

nonsensical intercepts for regression models

Let’s say that I have performances in 9 sports as predictor variables and the total points of those sports as the DV. So I am making three regression models(non-nested) with three predictors each (...
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When to include intercept in logistic regression? [duplicate]

I see on this page following statement regarding a function for logistic regression: An intercept is not included by default and should be added by the user. See statsmodels.tools.add_constant. ...
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Is the intercept term in a linear regression model the intercept term?

Currently working through some notes on linear regression and they say the following: In the linear model: $$Y=\alpha+\beta x$$ the intercept term is the mean value of the response." However, I've ...
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glm with two interactive factors

I've run a glm (gaussian family) with a*b as independent variables. At first, I run two separate models (like glm(y~a) and ...
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1answer
50 views

multiple regression coefficients - Standard error of intercept

I am implementing an R-type summary() function in python with the restriction to exclude use of scientific libraries. (assignment) I found this http://www.nd.edu/~rwilliam/stats1/x91.pdf material ...
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Comparing two populations with high dropout, best tests and interpretation of intercept significance

I am analyzing some single cell data and was trying to pick the best test. I first tried logits and found that all three genes of interest were significantly across populations. I also found that the ...
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Interaction term btw. binary and continuous variable - dropping the intercept?

I run a linear regression with many dummy variables (in total 10). Thus to avoid the dummy variable trap, I dropped the intercept and included all dummy variables. Now I'd like to have a look at the <...
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What is the relationship between average of a rolling intercept and the intercept from a regression over the entire period?

If i calculate rolling (e.g. 3 periods back) intercepts for a time series using OLS, is the average of these rolling intercepts then in some way related to the intercept from an OLS of the entire ...
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Linear Regression - with or without intercept [duplicate]

Difference between linear regression with or without intercept? Why and when to use which one?
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268 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 ...
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119 views

What test can I use to compare intercepts from two or more regression models when slopes might differ?

I wish to test whether intercepts in linear regression models differ between two or more groups, when group-specific slopes might themselves differ (i.e., an interaction term may be present). ...
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120 views

Significance of intercept only in Logistic Regression analysis

Having performanced a logistic regression in R with the glm function, I'm not sure how to interpret the results for the Intercept (as shown below). So I found that my intercept is significant but all ...
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139 views

How to interptet Jensen Alpha statistical significance?

When you regress portfolio excess returns against relative benchmark excess return you get a model in which the beta (slope) could be interpreted as the one you get from the CAPM, that is systemic ...
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54 views

Regression in different regimes

I am interested in studying the intercept of a multivariate linear regression model such as: $y_t = a + b_1x_{1,t} + b_2x_{2,t} + ... + b_mx_{m,t} + u_t$ with $t = 1, 2, ..., n$ Under two possible ...
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Intercept meaning in group lasso

I have a database with categorical and continuous variable. My response variable is dichotomous and the indipendent variables are 4 factors (2 of them with roughly 10 levels and 2 dichotomous) and 20 ...
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1answer
26 views

logistic regression with conflicting results, so to speak

I was trying to duplicate values by running the same set of data, and my coefficients were different. there is one 0-1 dependent variable, and there are four 0-1 independent variables. I found out ...
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Formula for type III sum of squares of the intercept term in linear multiple regression

assume we have the regression model: $$Y = b_0 + b_1 x_1 + \dots + b_k x_k + \varepsilon $$ I know the formulas for all type III sum of squares for the regression terms except the formula for SS of ...
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170 views

Intercept in a Bayesian model with categorical predictors (with brms)

I have a Bayesian logistic model fitted in R with brms. The predicted variable is binomial, the predictors are categorical. The model uses bernoulli family and a ...
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146 views

Calculate the intercept from lm

I would like to understand how I can compute by hand the intercept from lm. The following example is a fractional factorial design (3^3) and the variables are factors. ...
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64 views

Adjusted r-squared and regression without an intercept

I am using R^2 and then computing the adjusted R^2 in cases like linear regression that use an intercept and the regression line does not necessarily passes through the origin. Lately, I've been ...
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96 views

How to report variance components of random intercept model?

I have used: model1 <- glmer(binary~ X1 + X2 +(1|MAINCATEGORY/YEAR), data = mydata, family = binomial(link = 'logit') To get the variance components of the ...
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My intercept is negative for a logit prob regression and I can't interpret

This is my first time building a model outside of school. I cleaned the data and ran Cohen's Kappa and cutoffs/ROC as well as did random forest. The accuracy of predicting the 1 outcome is about 37% ...
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49 views

Running model without intercept term? [duplicate]

I have the true model set as $y = b_0+b_1 x+u$. Now supposing that I'm running the model without the intercept term, Under what circumstances would the coefficient term in the model (without the ...
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30 views

Why is my regression intercept too low ? (General question)

Im currently trying to solve the following regression problem. Since my results for the first column are correct, im sure im on the right way but: For the second column i tried the realized variance ...
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4answers
94 views

Should I remove the intercept when regressing against one variable (country income)?

I understand that one should not remove the intercept, unless there is a very special circumstance. (see: When is it ok to remove the intercept in a linear regression model?) However, if I am running ...
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42 views

What's the difference between drift, intercept, and mean? [duplicate]

In R, stats::arima has a parameter named include.mean, and its result can contain a component named "intercept". For example, <...
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Interpretation of the intercept in a multiple logistic regression? [duplicate]

I have fitted a model by means of a multiple logistic regression, but it turns out that the only significant parameter is the intercept. Therefore, I decided to model only taking this parameter into ...
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Comparing fixed intercepts of different mixed models R

Given 3 variables: y is continuous, x is continuous, z is a repeated measures factor, nested within subjects. I have two models from different data sets a and b: fitm1 <- lme(y ~ x + z, random = ~...
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41 views

Data normalization in ridge regression when there is no intercept

I would like to have a linear model without an intercept and also without the target being centered. How should my data then be normalized when using ridge regression? If I standardized the variables ...
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1answer
33 views

glmm (poisson or negative binomial) which explain the significance of each single level [closed]

I'm using the function glmer.nb of the library MASS to analyse the effects of two fixed factors (temperature: 2 levels and salinity:3 levels) and nested random factor (Individual ID/room) on parasite ...
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42 views

Why shifted predictor value would not change OLS estimator except intercept term?

This question comes from MånsT's answer of question The least squares estimators of $β_1$,$β_2$,… are not affected by shifting. The reason is that these are the slopes of the fitting surface - ...
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181 views

Does dummy code a variable affect the intercept in a linear regression model

My colleague and I were both using R to fit a linear regression with the same dataset and same variables. The outcome variable is test grade while the independent variables are gender, age, and times ...
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590 views

Why is the intercept typed in as a 1 in stats packages (R, python)

When using statistics software, When defining your linear models, why is the intercept typed in as a 1, rather than "const" or "intercept" or something. What significance does 1 have? Is there some ...
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59 views

Fitting model without the intercept [closed]

Suppose I collected data of crop yield at a location for mutliple years and constrcut a model of the form lm(yield ~ drought_index + solar_radiation + heat_stress) ...

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