# 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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### Testing for coefficients significance in Lasso logistic regression

[A similar question was asked here with no answers] I have fit a logistic regression model with L1 regularization (Lasso logistic regression) and I would like to test the fitted coefficients for ...
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### Cox proportional hazard model and interpretation of coefficients when higher case interaction is involved

Here is the summary-output of the Coxph-model I used (I used R and the output is based on the best final model i.e. all significant explanatory variables and their interactions are included): ...
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### High dimensional, correlated data and top features/ covariates discovered; multiple hypothesis testing?

I have a dataset with about 5,000 often correlated features / covariates and a binary response. The data was given to me, I didn't collect it. I use Lasso and gradient boosting to build models. I ...
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### Interpreting coefficient in a linear regression model with categorical variables

I will give my examples with R calls. First a simple example of a linear regression with a dependent variable 'lifespan', and two continuous explanatory variables. ...
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### Interpreting logistic regression coefficients with a regularization term

I understand the coefficients of a logistic equation can be interpreted as odd ratio. If a regularization term is added to control for over-fitting, how does this change the interpretation of the ...
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### How do I reference a regression model's coefficient's standard errors? [closed]

Estimate Std. Error t value Pr(>|t|) (Intercept) 10.2758 0.5185 19.817 < 2e-16 *** rprice2 -1.8581 0.5139 -3.616 0.000696 *** ...
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### How can $R^2$ have two different values for the same regression (without an intercept) [duplicate]

My question is multifaceted. So I'll start by asking my question and then explain what has caused me to ask this question. How can I calculate the coefficient of determination for a linear ...
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### Regression: What is the utility of R squared compared to RMSE?

Suppose I'm doing regression with training, validation, and test sets. I can find RMSE and R squared (R^2, the coefficient of determination) from the output of my software (such as R's lm() function). ...
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### Contribution of each covariate to a single prediction in a logistic regression model

Say, for example, that we have a logistic regression model which outputs the probability that a patient will develop a particular disease based on many covariates. We can get an idea of the ...
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### How to manually calculate dfbetas

I am trying to replicate what the function dfbetas() does in R. dfbeta() is not an issue... Here is a set of vectors: ...
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### Are t tests of coefficients in multiple regression post hoc tests?

In multiple regression, if a global F test is significant, then are t tests (or Wald tests) for the coefficients considered to be multiple comparisons and post hoc tests and should they be adjusted?
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### What is the correct way to determine which features most contributed to the prediction of a given input vector?

I am using logistic regression for binary classification. I have a big data set (happens to be highly unbalanced: 19 : 1). So I use scikit-learn's ...
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### Is the average of betas from Y ~ X and X ~ Y valid?

I am interested in the relationship between two time series variables: $Y$ and $X$. The two variables are related to each other, and it's not clear from theory which one causes the other. Given ...
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### What is the difference between least square and pseudo-inverse techniques for Linear Regression?

I am wondering the difference between them. Basically they do the same job at the end finding coefficients of parameters, but they look just different the way we find the coefficients. To me, Least ...
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### Explicit solution for linear regression with two predictors

I have some samples of data of the form $x,y$ and $z=f(x,y)$. I wish to fit a plane $$z = Ax + By + C$$ to the data with the smallest mean square errors. I have found an "answer" in section 3 of this ...
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### Significance of individual coefficients vs Significance of both

This was a question I read from google quantitative analyst interview on glassdoor: If each of the two coefficient estimates in a regression model is statistically significant, do you expect the test ...
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### Testing whether two regression coefficients are significantly different

I'm hoping somebody can help me out with this question. For a study I did a path analysis, which looks like this: IV --> Mediatior --> DV IV --> ...
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### Converting the beta coefficient from matrix to scalar notation in OLS regression

I've found for my econometrics exams that if I forget the scalar notation, I can often save myself by remembering the matrix notation and working backwards. However, the following confused me. Given ...
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### When to use Ridge regression and Lasso regression. What can be achieved while using these techniques rather than the linear regression model

I am looking forward to learning more about the regularized regression techniques like Ridge and Lasso regression. I would like to know what can be achieved by using these techniques when compared to ...
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### How to interpret log-log regression coefficients for other than 1 or 10 percent change?

I have read many threads here on how to interpret coefficients in a regression where the predictor and the dependent variable are log-transformed. Most give an answer for a one or ten percent change. ...
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### Can the coefficients of dummy variables be more than 1 or less than 0?

Can coefficients of dummy variables be more than $1$ or less than $0$? I am getting coefficients ranging from $-6$ to $-16$. I am specifically asking about the coefficients of dummy variables, not ...
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If granted omniscience and we know that $\beta_1$ in a multiple linear regression model is truly 0, what does that mean in words (and math notation)? The model is: $Y = \beta_0 + \beta_1X_1 + \... 2answers 670 views ### What is the intuition behind getting a slope distribution in linear regression? If I understand it correctly, linear regression finds one best fitting line for the given data. It can do it either by using calculus and solving for intercept and slope equations or it can solve it ... 3answers 33k views ### How to interpret a logistic regression model with all negative coefficient? I have 4 predictors, and 1 binary response. I fitted a logistic regression model. A strange thing is that all the coefficient of the model are negative. Is that possible? Probably I did something ... 1answer 5k views ### How can I interpret coefficients of categorical predictors in the negative binomial regression model? I used some categorical variables as predictors to a negative binomial model. The dependent variable is numerical. I used glm.nb in R and the results show relative coefficients of one category ... 2answers 35k views ### How to interpret Quadratic Terms I'm answering a practice exam questions, and having trouble with one on quadratic terms. Could someone give me a quick summery of 1) why they are sometimes included? 2) How to interpret them? In ... 2answers 6k views ### What is the interpretation of scaled regression coefficients when only the predictors are scaled? I'm running a model with 2 continuous predictors (x1, x2) and 1 continuous outcome variable (y). The results show that both of the slopes are significant, as well as the intercept, with no significant ... 2answers 343 views ### Positive Poisson regression: what is the effect on the model of shifting vs truncating? Let's say that you were wanting to model how many times someone had to take a certain test before passing (depending on a range of predictors like practice, mock tests taken, classes attended, etc.). ... 2answers 202 views ### Inference and predictive models Some people in my line of work are interested in the coefficients that results from developing predictive regression models(prm). I’m somewhat reluctant to use these coefficients to explain an ... 1answer 800 views ### why does R rlm {MASS} return different coefficients almost each time it is called? I'm noticed that the rlm {MASS} returns almost every time different coefficients, even though I'm using the same parameters and the same data set I'm calling: <... 1answer 756 views ### R: regression coefficients and lubridate I'm getting some odd coefficients when I apply lm to dates that have been processed and rounded using the lubridate package. ... 1answer 2k views ### Cohen's d from regression coefficient? Is it appropriate to calculate Cohen's d (effect size) from the regression coefficient of an independent categorical variable? My coefficient represents participation in an intervention (treatment ... 2answers 761 views ### How do I examine biasedness in nonlinear regression? I have the nonlinear regression model $$y_i=\beta_0+\beta_1 x_{1i}+e^{\beta_2 x_{2i}}+u_i,\quad i=1,2,\ldots,n,$$ and the least squares assumptions are satisfied (see below). Let$\beta=(\beta_0,\...
Say I have the true linear model with normal errors: $y = \beta_1 X_1 + \beta_2 X_2 + \epsilon$ However, I only observe $Z = X_1 + X_2$, so I estimate instead: $y = \delta (X_1 + X_2) + e$, can I ...