# Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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### Regression models after PCA

My understanding of principal components regression (PCR) is that it is a linear regression performed on all or a subset of predictors obtained via PCA. All the resources I've read only apply linear ...
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### Study of an experimental regression with a percentage as the dependent variable

I am trying to estimate the effect of an experimental intervention (random assignation to treatment and control groups) with the percentage of people in each group assisting to government services as ...
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### What model should I use for this weird dataset? (Survey Response attributes)

Above is a snippet of a dataset I am working with. It is a pull from a research tool presenting a set of many different and distinct attributes that have been sorted into numerous "categories&...
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### Test and Train AUC are almost exactly the same

I am trying to build a logistic regression model. My test and training sets are generating almost the same AUC. Ideally- this means that the model is performing very well. But since, I got this result ...
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### Computing gradients of Gaussian Process Regression [closed]

I have a dataset with 2 features in it, I would like to obtain gradient for this case. Can anyone help me with this. I am looking for 2D solutions, partial derivatives with respect to x1 and x2. def ...
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### How to analyze the interaction between variables when the number of explanatory variable is large

I am interested in the analysis of interaction between variables in a regression model. First, the context : I work in marketing and the explanatory variables corresponds to marketing channels, ...
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### Visualizing Multicollinearity: How does overlapping region of IVs contribute to R²?

I have trouble understanding how R² in a regression analysis makes sense visually in Ballantine diagrams. For instance: Obviously the red region is ignored when estimating the coefficients for x on y ...
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### Does binomial regression weight some observations more heavily than other?

I am performing a quasibinomial regression, where each subject has an unfixed number of trials. So one subject may have had 5 trials while another had 90. In R the regression equation follows: glm(...
1 vote
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### Analysis of causal relationship of within-subject choice patterns among different groups using R - emmeans / hlm / Mixed Effects Logistic Regression

I am conducting a research and investigate the relationship between persona type (independent variable; a vs. b vs. c vs. d) and luxury perfume choice (dependent variable; niche vs prestige)(H1), ...
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### How to test for size (Typ one error probability) on Breusch-Pagan Test in R?

The data i created contains heteroscedasticity. I already calculated the power so my idea was to basically do the same but switch the hypothesis so that H0: Heteroscedasticity and H1: Homoscedasticity ... 63 views

### Parameter distribution of $\theta$ from a rectangular matrix multiplication $C\theta$

I am struggeling to see where this problem fits - i.e. what topics this problem relates to, so I am not able to find the right literature. I want to use some particular information as a prior to a ...
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### Seeking for help! About conducting hierarchical linear regression with categorical variable as moderator by using SPSS [closed]

In my thesis, I have made the following hypotheses... IV--> Perceived Risk of COVID-19 (Continuous variable) DV --> Anxiety (Continuous variable) Possible moderators--> age, education level, ...
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### Estimating and fitting a GARCH model

By far I've become really familiar with the concept of GARCH but I'm still confused on how to go on with the implementation especially that I've seen multiple sources using different approaches: ...
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### Non-linear regression. Need some help implementing a model from a paper

I found this paper very useful for my research, however, I'm not familiar with non-linear regressions and I'm finding it tricky replicating it. Using the first f=model for example: ...
I am trying to use linear least squares regression to extract the coefficients of a model. Specifically, I am looking at a model with two independent predictor variables $x_1$ and $x_2$, and an output ...
Lets say my model is : $y=\beta_0+\beta_1x_1+\beta_2x-2+\beta_3x_3$ Now lets say I know for sure that $\beta_2 = 4$. My teacher said I should create $y’ = y-4 X_2$ and ordinary least squares (ols) ...