# 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.

1,311 questions
Filter by
Sorted by
Tagged with
5k views

### Multiple regression, full and restricted model

So I have a data set that looks like this. I want to write a full and restricted model which would evaluate the null hypothesis that latitude - controlling for continent and sex - has a significant ...
86 views

### Regression Interpretation conundrum

I am running an OLS regression of the form $$\log\left(Y\right)=x_0 + \left(\frac{x_1}{Y}\right)\beta_1+\log (x_2)\beta_2 + \epsilon$$ I have one covariate as $\left(\frac{x_1}{Y}\right)$ which is a ...
183 views

### How to interpret my coefficients?

I have the following model: $$Gini_{it} = \alpha_i + \beta_1\ln(BNP_{it}) + \beta_2trade_{it} + \epsilon_{it},$$ where $Gini_{it}$ is the Gini-index from 0 to 100, $\ln(BNP_{it})$ is $\ln$ of the ...
4k views

### Standard error for the sum of regression coefficients when the covariance is negative

I have a question about appropriately calculation the standard error for the sum of two coefficients in a linear regression model. My question is similar to this and this, but I can't seem to solve ...
2k views

### Interpret interaction effect of 2 continuous variables

My dependent variable is house prices. And my interaction term contains two continuous variables 1) log of employment at the nearest firm 2) log of distance to the nearest firm. House price = b0 + b1 ...
97 views

2k views

1k views

### How to interpret regression coefficients when outcome variable was transformed by Box-Cox

I try to do a linear regression of a positive continuous dependent variable (outcome) with several independent variables (all of them are categorical / binary). I had many troubles to get Gaussian ...
1k views

### Beta coefficients from stratified analysis when there are covariates?

Suppose I have a regression model shown below Model 1: $$Y = \beta_0^\ + \beta_1SEX\ + \beta_2ALCOHOL\ + \beta_3SEX*ALCOHOL\$$ The predictors I am interested in are SEX (binary: 0 female, 1 male) ...
9k views

### Interpreting regression coefficients and economic significance

I am having a difficult time understanding how to discern whether the regression coefficients I am getting are large or small relative to the data. I have one regression that is cross-sectional. For ...
58 views

### Forcing smoothness of regression coefficients

I'm building regression models on spectral datasets: the predictors are the intensites of signal at the different frequencies. In this case the intensities at close frequency values are highly ...
290 views

### Perfect Multicollinearity

If 2 independent variables $x_1$ and $x_2$ in a hypothetical linear regression model $y = \beta_0+\beta_1 x_1 + \beta_2 x_2 + \varepsilon$ are perfectly multicollinear, which of the 2 independent ...
2k views

189 views

### Is Omitted Variable Bias Always Bad? What are the implications of omitting variables from a regression that aren't easily obtained in the real-world?

Say I'm using multiple logistic regression to help caterers in a large city predict the probability invited adults will come to a wedding. Say I have a proprietary dataset of likely relevant predictor ...
61 views

### Find Feature Weighting in Deep Learning

If I train a deep neural network on standard tabular data (csv file etc. with labeled features) is there a good way to gauge how important each feature is in a particular new instance's prediction ...
437 views

### Multinomial Logistic Regreesion with Lasso penalty in R

I am applying regularized logistic regression (in R) to the handwritten digits data set. I have fitted a logistic multinomial model with lasso penalty to the training data. I am asked to obtain the ...