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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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Intercept estimates VERY different comparing glm and glmm

Can anyone explain the following puzzling phenomenon? I'm fitting a binomial glmm using glmer from the lme4 package of R. The mean of the binary response variable in the dataset is about 0.1. When I ...
Andrew Robinson's user avatar
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1 answer
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Interpretation of Poisson regression model (outcome variable - dietary diversity)

I would like to get some insights on how to interpret the Poisson model using the results shown in the picture. This is how I interpreted it: For every one unit increase in the number of cooked food ...
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Meaning/interpretation of intercept_ in partial least squares

After using sklearn library for Partial Least Squares, I have doubts about the interpretation of the "intercept" of the model. As you can see in the code that follows, and its corresponding ...
Francisco Angel's user avatar
3 votes
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Intercept significant, but confidence intervals around its standardized β include 0

I ran a HC (‘robust’) regression. The intercept is significant, which is reflected in the confidence intervals around the unstandardized betas. However, the CIs around the standardized β are quite ...
mbp's user avatar
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In Regression Through the Origin, why do the CIs of the slope depend on datapoints with zero x value?

I'm working with a Regression Through the Origin model as described in this reference. The model is $Y_i = \beta X_i + \epsilon$ and the least squares estimate of $\beta$ is $\hat\beta = \frac{\sum ...
Ryan Moulton's user avatar
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1 answer
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Interpreting GAM intercept (mccv's bam() function in R)

I am very new to GAMs (and, frankly, regression models in general), and I am struggling to understand the model summary I get when using the bam() function from the mgcv package in R, more ...
aevilok's user avatar
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Setting the intercept to zero in this linear regression results in unbiased and less variable estimates - but is it theoretically justified?

Based on feedback I got from our statisticians, and having seen this post, I was pretty sure that one almost never sets the intercept to zero in a linear regression. However, I recently came across ...
user6376297's user avatar
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2 answers
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Estimate a GLM where the intercept is known

I have some x and y values. The y values have some random error. ...
Dan's user avatar
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Force GLM through zero [duplicate]

I am working on a glm model using a binomial distribution. I want to force the intercept through zero, as I know that biologically this makes sense. I have used the formula to ...
Squan Schmaan's user avatar
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1 answer
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Estimate of the intercept is off in a simulated AR(1) model

I've been working with a SARIMAX model for forecasting and found myself struggling to accurately interpret its long-term forecasts. To better understand the underlying mechanics and perhaps pinpoint ...
Quant In Spe's user avatar
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NA for p value of intercept in permutation test through permutes package in R [closed]

I am looking for how FROH (inbreeding level) change with age, island and year are random. I got the following result and got NA for p value of intercept, what might be the cause of it and how to ...
Nitya Shrestha's user avatar
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1 answer
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Intercept or trend in a VAR model for stationary percentage changes [closed]

I am estimating a VAR model in R, using the vars package. There is an argument in VAR() function called ...
Alfonso's user avatar
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1 answer
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auto.arima results in R has no intercept

After fitting an ARIMA model with a covariate using the auto.arima function in R, I get the following results What could be the reason as to why my results do not ...
Wagathu's user avatar
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1 answer
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Interpretation of Intercept in mixed model with repeated contrasts

I am running the following logistic mixed model in lme4: ...
SilvaC's user avatar
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190 views

Warning: Hauck-Donner effect detected in the following estimate(s): INTERCEPT

This is a quick question because I could not find an answer online. I ran a truncated Poisson model and I got the warning in the title (perfect separation?) affecting my intercept. The output is: <...
Giovanna's user avatar
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What's the interpretation of the intercept of a linear mixed effect model with only one group

I'm trying to understand the meaning of the intercept term in a linear mixed model. The caveat here is that the dataset the LME will be built upon will only consist of subjects from a single class (...
Syuma's user avatar
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1 answer
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Fitting regression where data is concentrated at the origin

I'm doing an exploratory data analysis which is looking at a number of character-level features of Chinese writing. The association I am looking at currently is that between the complexity of the ...
Shawn Hemelstrand's user avatar
3 votes
1 answer
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Interpreting intercept with centered predictors in logistic mixed model

I am running a logistic mixed model in lme4. The model is as follows ...
SilvaC's user avatar
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1 answer
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Can we have intercept in this model: mutually non-exclusive factors

Imagine we have an experiment, where each subject consumes 2 out of 3 different kinds of chocolate bars (Mars, Snickers, Bounty) and we measure blood sugar subsequently, that is, after 2 of the bars ...
GAMer's user avatar
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3 votes
1 answer
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Should I remove the intercept when I have one dummy variable that covers all the categories in a categorical variable?

I have a categorical variable that has $4$ categories, and I have two dummy variables, $x_1$ and $x_2$, that cover this categorical variable. The $x_1$ variable has values of only $1$ without any ...
user400487's user avatar
2 votes
1 answer
134 views

How to interpret the p-value associated with the intercept?

I ran a gamlss to predict my response variable Y with 2 categorical factors PROTECTION and JOUR ...
Marie Guittonneau's user avatar
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1 answer
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Interpretation of estimates for 2 categorial factors and their interaction

I selected the best fitted gamlss model for my data : gamlss(formula = Ratio ~ PROTECTION * JOUR, nu.formula = ~JOUR, family = BEINF, data = D_E1, trace = FALSE) I want to interpret the output of ...
Marie Guittonneau's user avatar
2 votes
1 answer
153 views

What to set "intercept factor" and "slope factor" as in model?

I was struggling a bit with understanding what exactly the intercept factor and slope factor is in a model. I need to estimate these in an a priori power analysis I am trying to do. My understanding ...
Matt W's user avatar
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1 vote
1 answer
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Interpreting an estimated bivariate VECM

I have used the tsDyn package in R to estimate a VEC model for the data in the graph, and I am unsure about my interpretation of the output. ...
Richard Hardy's user avatar
1 vote
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Lmer R: linear mixed model with random intercepts and nested variables [closed]

I want to write a model for my data on cell counts in specific brain regions. The multilevel structure of the data is as follows: Measurements within subregions with axes within animal Subregion and ...
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Intercept change issues in growth curve model in R

I am currently analyzing data using a growth curve model, and I have one question that puzzles me. I wonder why the intercept values keep changing when I add random effects or higher-order terms to ...
Roy Kang's user avatar
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Simple linear regression for market size estimation - understanding the existence of the intercept constant [duplicate]

Background/Context: Over the last year ServiceY has slowly rolled out across the city. The city is divided into geographic divisions of different sizes which all have different levels of demand for ...
SoccerDadExcel's user avatar
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1 answer
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Latent growth curve model - can I talk about an effect over time if I only have my outcome at the last timepoint?

I have a latent growth curve model with two variables. X (exposure to media) was measured at 5 time points over several years. Y (misinformation proneness) was measured only at the last time point (...
Maria Medeiros's user avatar
1 vote
1 answer
48 views

How to interpret intercept in linear mixed effects with two categorical predictors with three levels?

I'm having a bit of a hard time interpreting the results of this linear mixed-effects model: happy_prob ~ height_shuffle * height_original + (1 | template) Where <...
Marco B's user avatar
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1 vote
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93 views

Calculating R-squared (coefficient of determination) from WLS linear regression with zero intercept

I need to calculate the R^2 for a weighted least squares (WLS) regression model which is also a regression through the origin (RTO). I'd like to use it for comparing the quality of the fits for the ...
Virag's user avatar
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303 views

GAM plots: partial effects, shifted y-axis, or predictions - which representations/interpretations are correct/accurate?

I have two GAMs fitted with a Gamma distribution, with the same model structure with a continuous response variable and one continuous covariate, two categorical covariates, and one random effect: <...
mto23's user avatar
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Intercept in Quantile Regression

We all know that for the OLS model, if you center both $X$ and $Y$, the estimated intercept would be 0. I was curious if we can do a similar thing for Quantile Regression. Would it be possible if we ...
momo's user avatar
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1 vote
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covariance terms for random effects model

I have a random effects model with two groups. $$ y_i = \alpha_{j[i]} + \gamma_{k[i]}+\epsilon_i $$ Where $j[i]$ and $k[i]$ denotes the group memberships for individual $i$. In R, I can estimate $\...
Tordir's user avatar
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109 views

What does a non-significant intercept mean in a meta-regression using rma.mv ? Does it indicate problems? If so how to solve them?

I am conducting a meta-analysis using the metafor package in R. More specifically I use a random effects model applying the rma.mv function. When I run my meta-regression with moderators, I always get ...
meta1000's user avatar
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Interaction term's significance changes by including the intercept. How to decide if intercept is to be kept or not?

I am working on a model (non-linear) of the form: Should I have the intercept in the equation, as having one gives a different outcome (level of significance) to my interaction term 1, compared to ...
Jyoti Nair's user avatar
5 votes
1 answer
296 views

Poisson regression intercept downward bias when true intercepts are small

When fitting a Poisson regression on data with low expected values, the intercept term has a small bias even when the model is perfectly specified. Below, I simulated data just using $y \sim rPois(exp(...
Nick Link's user avatar
2 votes
2 answers
182 views

Is it possible to calculate x-intercept from a mixed model?

I understand that the x-intercept can be calculated using $y = mx + b$ for a linear model. I am unsure if this is statistically appropriate for a mixed model with count data, given that counts cannot ...
Ahsk's user avatar
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1 answer
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Dummy coding of linear regression, intercept and constraint

Let the following multilevel problem, where we try to predict the credit card balance of individuals $y_i$: $$ x_{i 1}= \begin{cases}1 & \text { if } i \text { th person is from the South } \\ 0 &...
glouis's user avatar
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3 votes
1 answer
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Plotting a regression line with a different fit than the model it is supposed to illustrate

I am currently at a dilemma concerning a model describing the allometric relationship between body size and mass. After carefully checking model assumptions and selecting the model that best fits the ...
Hake98's user avatar
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1 vote
1 answer
116 views

Regression analysis with constant dependent variable

Can someone explain to me what's going on in the following? Suppose we have data with constant dependent variable: ...
4twobi's user avatar
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0 answers
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Should I include a constant term when testing the significance of variables against a null model?

I have a one-hot vector $y \in \{0,1\}^{n}$ giving the case/control status of a group of genetic samples. I also have a genetic vector $G \in \{0,1,2\}^{n}$ and a vector of covariates $K \in \mathbb{R}...
Jeff's user avatar
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1 vote
0 answers
121 views

OLS - The relationship between "minimizing SSR" and "the ration between cov(X,Y) and Var(X)" [closed]

Question What would be the intuitive explanation for the slope of Ordinary Least Squares(OLS), which is $\frac{cov(X,Y)}{var(X)}$ contributes minimizing the sum of squared residuals? In the same ...
Eiffelbear's user avatar
2 votes
1 answer
301 views

What does the intercept mean in a car ANOVA output?

I've just carried out an ANOVA using the Anova function in the package car, with type III sums of squares and got the following ...
timeywimey's user avatar
2 votes
1 answer
542 views

Logistic regression that has intercept and coefficient of 0

I created logistic regression model, however my data is very imbalanced (92% vs 7%) so I created both balanced and imbalanced version using sklearn. For my version on the left, I used: ...
Sam333's user avatar
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3 votes
1 answer
522 views

Intercept changing after adding an interaction

Quite a basic multiple linear regression question. I know that the intercept should describe the predicted value when all predictors equal 0. Then, why does adding a paired interaction term (X1X2) ...
Ido Ben Artzi's user avatar
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0 answers
130 views

The use of tau cuts from an ordered logistic regression

I runned several ordered logistic regression using the polr function from the MASS package and interpreted the odds ratios for each model. However, I'm in doubt how to use the intercepts/tau-cuts from ...
rr19's user avatar
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2 votes
1 answer
536 views

What's in a name: bias (intercept) [duplicate]

In linear regression, $y = w_0 + w_1x_1 + w_2x_2 + \cdots$. The intercept term is called 'bias'. Why is it called bias? And how is this different from the 'bias-variance' trade-off?
cgo's user avatar
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Running a glmer to find if the difference between two proportions is significant

I'm running a study wherein participants classify some faces they see. And I aim to examine if the probability for accurate categorization for a face is larger than a baseline probability I've got for ...
Anjana Lakshmi's user avatar
3 votes
2 answers
1k views

GLM without intercept

I`m using a GLM to determine the influence of climate variables in the incidence of a disease in 6 different cities across time (2007-2020). I'm using a negative binomial regression, since the ...
Álvaro Souza's user avatar
1 vote
1 answer
21 views

Go to models for assessing accurate slope and intercept of model for simluation [closed]

What are your go to models for assessing as ACCURATELY as possible the slope and intercept of given predictor and predicted random variables? The goal is to use simulated predictors + outputted ...
ADAMS zequi's user avatar

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