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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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 ...
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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 ...
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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
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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 ...
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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 ...
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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.
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Lmer R: linear mixed model with random intercepts and nested variables
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 the 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 ...
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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 ...
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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 (...
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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 <...
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Use centered variables or include an intercept in time series analysis?
I have read that analogous to univariate AR(p) models, there are two possibilities to allow for a non-zero mean with VAR(p) models:
a) either use centered variables in the model:
Φ(B)(Xt − μ) = Zt
b) ...
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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 ...
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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:
<...
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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 ...
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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 $\...
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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 ...
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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 ...
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What is the formula AUTO ARIMA (Python's pmdarima) uses?
References
https://otexts.com/fpp3/non-seasonal-arima.html
https://otexts.com/fpp3/seasonal-arima.html
Question
According to the webpages, the formula of ...
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Questions about the summary of auto ARIMA (Python pmdarima)
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I trained two models by using two different data sets.
model = pmd.auto_arima(data, trend='ct')
What is intercept in ...
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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(...
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Catgeorical variable coefficients interpretation
if I have the following regression model in gamlss (or if it's a general concept)
Y ~ var1
Where Y ~ beta, and var1=(g1,g2,g3) g1 is the reference level, what does it mean that the intercept is ...
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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 ...
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How to interpret intercept of mixed model with time
I am trying to understand the meaning of the intercept in my glmm model summary. I get that is is the prediction when all predictors are 0. The reference levels can be specified so that this is ...
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Intercept term of a GAM with smooth and factor smooth
I am modeling time-series data (30 measurements) at the individual-level by a grouping factor (5 levels) and I have the following model specification from a generalized additive model (GAM):
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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 ...
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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:
...
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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}...
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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 ...
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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 ...
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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:
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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) ...
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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 ...
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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?
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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 ...
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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 ...
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Regress some count data with specifically residents count of different race--Is it reasonable to drop intercept? [duplicate]
I know it's rarely good to drop intercept and I have read the posts here. But I want to ask about this specific case where resident population was the sole independent variable in my study.
I'm ...
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Interpreting intercept and coefficients in multiple regression with categorical variables
I started doing a regression analysis of how long a person watches a video according to their profession and I got this equation:
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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 ...
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Can I specify a random intercept in a conditional logit model?
In conditional logit models, global intercepts cannot be estimated as they do not influence the conditional probability of a positive outcome within groups. I understand the intercept term gets ...
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How does an item intercept in CFA relate to the difficulty parameter in IRT?
I am having difficulty clarifying in my mind how item intercepts in Confirmatory Factor Analysis or SEM manifest, and how they are graphically represented in an IRT ICC plot. I understand that multi-...
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How do you set up multiple variable regression with no intercept term?
Can anyone help with the set up of a multiple variable regression function that does not have an intercept (no beta hat 0)? I've tried to figure it out based on class notes for one variable regression ...
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Significant intercept but non-significant coefficients in hierarchical linear modeling (hlm)
I am a beginner in statistics. I am using hierarchical linear modeling (hlm) to predict the effect of centrality on voice. The intercept is significant, but the random effects are not significant. ...
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interpretation of the Intercept
I'm writing since I have doubts on how to interpret the output posted at the beginning of this thread, since i have a similar one. Our friend wrote that the predictor "country" has 3 levels, ...
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Can a random intercept act as moderator in a mixed-effects model ? (Lmer - R)
This post is related to my previous ones, but now I'm looking at each year separately (i.e, this is not a repeated measures design). My data set looks like this:
...
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Whether to use an intercept for spline regression
I'm using the function ns() and bs() in the R package spline. By default, there is no intercept. I know using an intercept will ...
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How to interpret linear mixed model with/without random intercept fitted in nlme
I fitted two models using the Oats data from nlme:
...
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Interpreting intercept with a categorical predictor
I have a categorical predictor (segment) and continuous DV (income). 'segment' is a factor with 6 levels. I ran a simple regression in R and got the following results:
Deviance Residuals:
Min 1Q ...
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Can slope variance be greater than ICC in lmer results
My question is can variance of the random slope be larger than random intercept variance? And if so, what would it mean in terms of group level variation?
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What is the intercept in a regression model with demeaned dependent variable?
Suppose you have a regression model
$\tilde{y}$ = $X\beta$ + $\varepsilon$,
where
$\tilde{y}$ = $y$ - $\bar{y}$
and $X$ contains a constant.
If you estimate the model by OLS, does the estimated ...
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