# Questions tagged [regression-coefficients]

The parameters of a regression model. Most commonly, the values by which the independent variables will be multiplied to get the predicted value of the dependent variable.

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### What do changes in regression coefficients indicate about correlations among predictors?

How do you tell if there is a strong, weak, or no correlation between two predictors if you are only given the regression coefficients from two models. One model contains one predictor and the other ...
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### Can we visualise regression results through diagram?

I read a journal article, in which the authors made a diagram based on regression results (beta weights). Pretty much looks like a path analysis: I'm very sure that path analysis/SEM was not employed ...
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### How to interpret regression coefficients for a variable with takes positive and negative values?

I am running a GEE negative binomial regression to see how predictors affect the onset of violence through time. I have an $X$ variable (vegetation cover) which is calculated as whether an ...
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### Understanding simplification of constants in derivation of variance of regression coefficient

In looking over TooTone's answer in Derive Variance of regression coefficient in simple linear regression, there's a step in line 3 below where $(\beta_0 + \beta_1x_i + u_i )$ is simplified to $u_i$ ...
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### Updating regression solutions for a new regressor without the original dependent variable

Note: This question is analagous to the question I asked here except instead of a removing column, I am adding it. I am interested in a linear regression on the model; $Y= X\beta + \epsilon$ And I ...
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### Interpreting regression coefficients when the outcome variable is an inverse hyperbolic sine function

I just learned that when there are zero or negative values, a good alternative to using a logged function is the inverse hyperbolic sine function. When using log transformation on the dependent ...
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### Back transform mixed-effects model's regression coefficients for fixed-effects from log to original scale

I am running a mixed-effects model with the lme4 package. The model specifications are: ...
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### Excluding predictors with small effect sizes: not worth it to obtain data?

Suppose I have the following completely-made-up logistic regression model: ...
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### Coefficient equality test for multinomial logit (preferably in R)

If I want to test the equality of the coefficients of two IVs in the same regression (same DV) I can do a Wald test. If I want to test the equality of the coefficients of the same IV in two different ...
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### Diagnosing coefficient estimates through Ridge Regression

I want to use Ridge Regression to find out whether my estimated coefficients in a linear regression are stable (as the variance inflation factors tell me that there is multicollinearity). But I'm not ...
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### How does case-resampling bootstrap work for positive-value estimators?

I've looked at some other questions on bootstrap significance testing: Non-parametric bootstrap p-values vs confidence intervals Computing p-value using bootstrap with R p-value vs. confidence ...
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### Is logistic regression a valid way of analyzing A/B testing results?

I'm very new to the idea of A/B testing and I want to see if my train of thought here makes sense. Suppose that I run an experiment with two designs. I get two sets of resulting data, one for each ...
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### Coefficients linear and log-linear regression model

I performed both a linear and log-linear regression to predict the price of a smartphone based on its characteristics. Now I have a question concerning the coefficients between the two models. In the ...
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### What is the relationship between regression analysis, LASSO, and coordinate descent?

I'm a complete newbie and trying to understand what exactly LASSO is, how coordinate descent is used with LASSO, and how all of that factors into regression analysis. I'm totally confused about the ...
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### Finding the Coefficients of regressors

I understand how to find the coefficients of a bivariate regression and univariate regression w/o an intercept, i.e: Univariate: Y = BX + e ...
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### How can my regression coefficients be so far from the underlying model? [duplicate]

I'm performing regression on data derived from a known underlying model with normally distributed errors, and I don't understand how the fitted regression coefficients can be as far as they are from ...
I want to perform a univariate regression but with substantial measurement error in both $x$ and $y$. I therefore want to try orthogonal regression with R. The best answer to my question so far have ...