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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1answer
16 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, ...
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5answers
109 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-...
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0answers
15 views

Finding the make up of the intercept in a generalized linear mixed model [duplicate]

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
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1answer
501 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 ...
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1answer
62 views

Interpreting estimates of a bivariate regression model with a categotical and a numeric variable

How to interpret the intercept in a bivariate regression with one numeric and one categorical variable? The following model has a numeric variable (log10(N_Total_e)), namely the log transformed ...
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2answers
85 views

Alternative to R$^2$ in linear regression without intercept

It has been extensively described in this website the reason why one cannot properly calculate the $R^2$ - neither the Adjusted $R^2$ - in regression models fitted without an intercept. What is a good ...
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1answer
25 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
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1answer
359 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 https://www.nd.edu/~rwilliam/stats1/x91.pdf material ...
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0answers
34 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 ...
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0answers
12 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, ...
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1answer
679 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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4answers
102 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)...
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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
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0answers
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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 ...
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1answer
110 views

AMOS: CFA testing invariance, but cannot name intercepts

I'm using AMOS to run a 2-factor model with 5 indicators each (10 in total). I'm assessing the invariance. So I'm assessing the invariance for sex. While the configural and metric invariance worked ...
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1answer
419 views

Re-calibrating Intercept on logistic regression models for unbalance data

I have data-set that I’m modelling using logistic regression as land.cover~H1+H2+H3+H4+H6+H8+H14. My response and categorical variables are binary. However the number of 0 and 1 in my response ...
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0answers
136 views

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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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/...
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1answer
26 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 ...
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0answers
9 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 ...
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2answers
63 views

Why does removing the constant term prevent the dummy variable trap?

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 ...
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1answer
18 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 = ...
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1answer
356 views

Logistic model output when all inputs are zero

Consider a case where I have developed a predictive model using logistic regression. Now the logistic models gives a probability even when all the inputs are zero (because of the intercept). Now ...
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0answers
26 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: <...
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0answers
32 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+...
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3answers
58k 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
29 views

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 ...
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0answers
30 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/...
4
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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
148 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 ...
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0answers
31 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 ...
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0answers
17 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 ...
3
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1answer
429 views

Calculating variance components and ICC of a random intercept model by hand

When I really want to understand a measure or parameter, I tend to do the calculation by hand with simplified data. Today I have attempted to do the same with the ICC, but somehow keep failing. I was ...
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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?
2
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1answer
53 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 $$(...
0
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1answer
290 views

Adjusted $R^2$ 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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0answers
30 views

Variance of intercept in multiple regression

I'm calculating a variance of coefficients in a multiple regression with three predictors. I have built matrices necessary for calculation of variance of independent variables, for example, for b1 I ...
5
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2answers
498 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?
3
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1answer
50 views

Interpreting the intercept in logistic regression with a binary variable

I am using R to run a logistic regression to analyze how a categorical variable ("population") correlates with a binary variable ("response") and am having some trouble ...
0
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0answers
30 views

Logistic Regression with dummy variables? [duplicate]

I am working on a problem where response variable is binary and my features are dummy variables. I observed when I include intercept to model all the dummy variables' p-values are equal to 1. When I ...
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2answers
61 views

How do I interpret the regression output using Artificial Neural Network in R? [closed]

I'm working on a covid-19 dataset, and I'm interested in using the Artificial Neural Network (ANN) to measure the effect of some independent variables namely: confirmed cases, new cases, and total ...
0
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1answer
26 views

Weighted average, then adding an intercept term

I am working with a problem where we are calculating the weighted average of DNA modifications. Modified sites are placed into four different groups and the average weight is calculated from there. ...
6
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2answers
6k 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 ...
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0answers
28 views

Why the OLS parameters of a linear regression are correlated? [duplicate]

I found that in a simple regression model y=β0+β1x+ε, the parameters β0 and β1 are negatively correlated. Is there a explanation for this correlation? I found this property here, but I would like to ...
0
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0answers
7 views

Mixed Effects Logit Intercept

When I run a simple model using the ordinal package from R. model1 <- clmm(A~ B*C+ (1| Subject), data = df, threshold = "flexible") summary(model1) I ...
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0answers
55 views

Likelihood Ratio Test for Intercept in Simple Linear Regression?

I’m trying to construct a test statistic for the likelihood ratio test for the following hypotheses about the intercept of a simple linear regression: $$y_i = \alpha + x_i\beta$$ $$H_0: \alpha=0$$ $$...
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0answers
30 views

Logistic Regression with unbalanced data, intercept effect

In several papers I have read that when doing a logistic regression with unbalanced data, the entire effect of the imbalance is carried by the intercept. However, I cannot understand why this occurs, ...
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0answers
30 views

Should I give up the intercept when calculating general trend of time series?

I have a time series of customers. Say, every customer has 30 observations of how may items he purchased over a period of 30 months. I would like to add a feature indicating what the general trend of ...

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