Questions tagged [intercept]
The intercept in regression-type models is the value of the Y variable when all X variables are 0.
286
questions
2
votes
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, ...
7
votes
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
votes
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 ...
3
votes
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 ...
2
votes
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 ...
0
votes
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
votes
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 ...
0
votes
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 ...
0
votes
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, ...
1
vote
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 ...
4
votes
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)...
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
7 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
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 ...
0
votes
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 ...
2
votes
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 ...
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
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
...
0
votes
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 ...
1
vote
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 ...
0
votes
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 = ...
5
votes
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 ...
1
vote
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:
<...
0
votes
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+...
16
votes
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, ...
0
votes
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 ...
0
votes
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
votes
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?
...
2
votes
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 ...
1
vote
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 ...
0
votes
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
votes
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 ...
-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?
2
votes
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
votes
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 ...
0
votes
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
votes
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
votes
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 ...
gung - Reinstate Monica
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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 ...
1
vote
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
votes
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. ...
4
votes
1answer
79 views
How does the interpretation of a binomial-logit GLM change when an offset term is included?
My GLM is as follows:
...
3
votes
1answer
1k views
6
votes
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 ...
0
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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
votes
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 ...
0
votes
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$$
$$...
0
votes
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, ...
0
votes
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 ...
