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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3k views

Obtaining significance for variables in a linear discriminant function analysis

I have run a linear discriminant function analysis using the lda() function in the MASS library to determine which of 6 ...
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How to determine the significance of an interaction?

My question is simple: How do you determine the overall significance of an interaction (i.e. the marginal effect of $X$ on $Y$ for different values of $Z$)? But the background is a bit long-winded,...
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Finding standard error of beta coefficients in ridge regression using lambda

I need to get the standard errors of coefficients with Ridge Regression, by calculating the SE of the beta estimates after I choose the right lambda. ...
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532 views

Normality violations in multiple regression - report bootstrapped CIs, p values & t values?

I have analysed some data for a research project using multiple linear regression. However, normality assumptions for this method were not met in my data (and could not be resolved using ...
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Why signs of coefficients change when doing multivariate vs. univariate logit regression? [duplicate]

Excuse my dumb question, but I did an univariate logistic regression where the sign of the coefficient of my variable was negative (and it was significant). Once I have input it into a multivariate ...
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Comparing nonlinear regression coefficients from independent datasets

I performed enzyme kinetics experiments on a three independent preparations of an enzyme and produced the following three datasets which I separately fit to the Michaelis-Menten equation: $$ V= \frac{...
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241 views

Test regression parameter against a constant in SPSS

This is a pretty basic question, but I can't find an answer by searching for different statements of the same problem. Is there a straightforward way to test if a regression parameter is different ...
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Getting spline coefficients in R

I'm fitting a natural basis spline on a data set of the form: splineModel=lm(dist~bs(speed, df=3), data=cars) using bs ...
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932 views

Large coefficients and std. errors

I run a fixed effect model with Stata and because my dependent variable is a large number (max of 12 million and min of - 4 million), I got large coefficients for ...
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795 views

R lm output - t values and Pr(>|t|) don't correspond

I have just run a lm in R and here is the output: ...
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1answer
265 views

Logistic regression coefficient in not-so-good classification result

I did a Logistic Regression (LR) on a 2-class problem (77.3% negative, 22.7% positive), and the results are as follow: $\text{logit} (p) = -2.0 + 1.4X_1 + 1.3X_2 + 0.2X_3 - 0.3X_4 - 0.7X_5$ The ...
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Any test methods to show the linear behaviour of a data set?

I have a data set that has been collected by a set of empirical experiments. Having plotted them on a graph, it seems that the data behavior is linear. On the other hand, some colleagues claim that ...
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Why does the OLS-intercept not just “de-mean” the residuals of the same model without intercept?

The answer here explains, why the residuals of an OLS-regression have mean zero if an intercept is included. Problem: Intuitively, i would assume that including an intercept just "de-means" the ...
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If a variable is found with p-value greater than 0.05, why is it also taken for calculation in the regression equation Y=a+b1*X1+b2*X2?

Suppose, I have performed multiple regression analysis on the following data set where X1 and X2 are independent variables and Y is the dependent variable. And achieved the following multiple ...
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Should the final R glm include only significant levels of factors

I am running a glm in R on data with quite many predictors (~50), both initially continuous and factors. The response is binary and the volume of the data is OK (~100K rows), in order to model non-...
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2answers
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Log-Log Regression - Dummy Variable and Index

I have the following log-log regression equation (natural log was used): ln(Sales Index) = B0 + B1 * ln(advertising spend) + B2 * (January) .... + e where ...
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Postive correlation but negative coefficient in regression [duplicate]

I'm trying to understand the effects of the explanatory variables of my logit regression. ...
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1answer
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Interpreting percentage units regression

log(sales) = beta_0 + beta_1 * GDP The usual process of transforming a variable such as price into log(price) to measure an approximate percentage change means ...
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Coefficients and significance of lasso/ridge

Coefficients and significance of lasso/ridge I had 628 predictors after forming dummy of all categorical variables. When I ran lot many iterations traditional logistic regression iteration, I came ...
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R lm simultaneous parameter tests

Using R, I'd like to test whether multiple parameters in a regression model are equal to specific values (by default, are multiple parameters equal to 0). For example, in this regression model: ...
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1answer
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Comparing coefficients between two linear regressions: justifying insignificant difference when the predictor is significant only in one group

I have the following question, any hint would be really welcome: I am trying to conduct a two-country comparison by running two separate regressions, one for each country, and testing $H_0:\,b_1=b_2$ ...
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1answer
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Inclusion of standard error in regression equation

$$ \begin{alignat}{14} P = 11&.32 &+ 0&.71 \,\text{PASN} &+ 1&.54 \,\text{DIS} &- 1&.02 \,\text{DIS}^2 &+ 3&.44 \,\text{FUEL} &+ 1&.36 \,\text{FIRST} &...
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Interpreting regression coefficients when the dependent variable is in percentages?

I have a dependent variable that is % of students graduating, but the explanatory variables are all absolute numbers, such as number of applicants and college fees. How would I interpret a coefficient ...
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In linear regression, why is the T-value the same whether or not I standardize the dependent and independent variables?

I standardized my x and y variables by subtracting by the mean and dividing by the standard error. I thought that was "fixing" my data, but I noticed the regression t-value that's produced in R is ...
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329 views

continuous vs categorical logistic regression for marks and admission

I have a list of marks scored by students in Science (X, between 0 to 100%) and whether they went to college to or not (Y). High marks in science showed a higher concentration of college admits and ...
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2answers
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Comparing coefficients in logistic regression, with different samples

I have a problem comparing the coefficients of my logistic regression models, in Stata. I have a dependent variable (DV) 'being an entrepreneur' and multiple independent variables (IV) such as age, ...
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3answers
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How do I calculate standard errors for sums of OLS coefficients?

I'm estimating a simple OLS regression model of the type: $y = \beta X + u$ After estimating the model, I need to generate a weighted combination of coefficients (e.g. $w_1 \beta_1 + w_2 \beta_2$) ...
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2answers
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Regression with random X

Suppose we have a standard regression model $$Y= X\beta + \epsilon$$ with $$\epsilon \sim \sigma^2$$ $$X \sim N(\mu,\gamma^2)$$ Are the estimated coefficients the same as if $X$ was fixed? Is ...
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1answer
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REGRESSION :A log-linear interaction term

How do I interpret a log-linear interaction term, is it possible? My model: $Y= B_1 + B_2\log X_1 + B_3X_2 + B_4(\log X_1 X_2) + u $
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1answer
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Does regularization in regression help with numerics when the data matrix is not full rank?

I am trying to get some intuition around regression when the data matrix $A$ is not full rank in the following regression/least squares problem: $$y=Ax+b$$ where $y \in \mathbb{R}^n$, $A \in \mathbb{...
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2answers
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standardized coefficients from glm logit

I am trying to create a coefficient plot from multiple logistic regression models, which all have the same predictors, but different sample sizes. This is a pre-test to a multilevel model. My question ...
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4answers
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Dummy variable in regression analysis (problem with result output and plotting)

I want to run the following model: Weight ~ Height*Sex, where * sign means interaction. I got the following result: ...
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1answer
101 views

Estimation of regression coefficient problem(hint)

I know, that the variance of OLS $\beta = \sigma^2 (X^TX)^{-1}$. Then I did calculations of $ (X^TX)^{-1}$ and I need the inverse in order to complete my proof. But the inverse of 3*3 matrix is a pain(...
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Statistics: Regression hypothesis test of slope, given sample correlation

Consider two data series, $X = (x_1, x_2, ..., x_n)$ and $Y = (y_1, y_2, ..., y_n)$, both with mean zero. We use linear regression (ordinary least squares) to regress $Y$ against $X$ (without fitting ...
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1answer
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Standard errors of regression coefficients in a Dummy Variable regression model

A dummy variable regression is equivalent to an ANOVA, and the beta coeffns are equal to the means of particular category with respect to the base category. However, I am unable to interpret the "...
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1answer
162 views

Understanding the meaning of the parameters in the linear regression model

When I first time learn multiple linear regression, I remember the interpretation of the regression coefficient is that: the marginal contribution of a specific predictor. Now I am rethinking this ...
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1answer
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VAR model interpretation: Coef vs Impulse response functions

In courses such as time series analysis, we learned that the relationships derived from impulse response functions or Granger causalties are more interesting than the estimation output. I was ...
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2answers
851 views

derive importance of feature by its coefficient (multiple linear regression)

In my test there was a false/true question: Your estimated model for predicting house prices has a large positive weight on 'square feet living'. This implies that if we remove the feature 'square ...
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2answers
836 views

Prove Estimated Regression Coefficients are the same with or without an intercept term

I am mostly having trouble with this question in that I don't think I know where to start and I am not confident in my answer that I have at the moment. The answer I have currently is mostly just ...
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1answer
430 views

How do you read the coefficients in Structural Equation Model for prediction?

I understand that in regression, the beta weight can be used for prediction. For example: Depression =~ 1 + 0.5*Loneliness Suppose that depression and loneliness are measured with Likert Scale from 1 ...
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1answer
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Backtransform coefficients of a Gamma-log GLMM

I am analysing data from an exclosure experiment, this means for several years, goats were kept outside a fence and inside the fence, plants could grow without being grazed. Outside the fence, grazing ...
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1answer
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Interpretation of coefficient in log-linear model with share predictor

There are several questions on the interpretation of coefficients in log-linear models such as Interpreting regression coefficients of log(y+1) transformed responses Log linear model interpretation - %...
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1answer
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Why is there no intercept in a regression model equation with standardized coefficients?

Let's say my model is this: $y = -0.372 + 0.045x_1 + 0.03x_2 - 0.205x_3 + 0.114x_4$, and my standardized model is this: $y = 0.635β_1 + 0.618β_2 - 0.466β_3 + 0.232β_4$. Why is there no intercept in ...
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1answer
203 views

Why are the signs of my coefficients are different?

My code is: library(survival) attach(veteran) survreg(Surv(time,status)~karno+diagtime+age+prior+trt ,dist="w") My analysis and the one in a book are as follows: ...
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2answers
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The variance of linear regression estimator $\beta_1$

Can we say $$\text{Var}(\beta_1) = \text{Var}\left(\frac{\sum (x_i-\bar x)y_i}{\sum (x_i- \bar x)^2}\right) = \left(\frac{\sum (x_i-\bar x)}{\sum (x_i- \bar x)^2}\right)^2 \text{Var}(y_i) \;\;??$$ ...
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1answer
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Compare coefficients from two separate panel regressions in Stata

I am trying to compare the coefficients of two panel data regressions with the same dependent variable. What I am aiming at is the following: ...
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2answers
649 views

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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3answers
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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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2answers
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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 ...