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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Interpreting interaction effect with ln(time) in Cox regression

I am fitting a Cox proportional hazards model with the interaction effect dummy:ln(time). How would you interpret the result? Is it a simple exp(x)-1)*100 to receive the percentage increase in y? Coef:...
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Linear regression's (OLS) coefficient interpretation with heteroscedasticity

To use OLS for inference, is it necessary in all cases that the premise of homoscedasticity is met? I need to check the influence of some features (eg age, income...) on a variable y (whether or not I ...
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Transforming ordinal logistic regression coefficients to beta weights

Ordinal logistic regression analysis result in coefficients which are log odds, and not b or beta weights, like in a linear regression. For example: How can I compare the log odds of the DVs? Is it ...
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Partial effect of numerical variable for a fixed level of categorical variable in regression

I have a regression model (in R) as follows: lm(price ~ time + color + brand) where, price be the second hand price of sth (numerical), time be number of years ...
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Help with Excel's Regression Output

I'm a junior engineer at a small biotech company and have some (real) data from a fractional factorial DoE (3 factors, 2 levels, 4 test conditions with six replicates each). Currently, we use excel to ...
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What could cause regression linear models to predict exactly the mean of train set while random forests perform worse?

Data set: I'm working on a linear regression problem where my train set $X$ is of shape $(703 557, 53)$. Each row is a client's features, which could be its age, its gender, how many calls we received ...
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Back-transformation of confidence intervals

I have read that I can simply back-transform my confidence intervals from my (mixed) linear models, which seems very handy for model interpretation. What I don't understand is why log-transforming the ...
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Lspline and bs produce very different coefficients for linear splines - which is preferred?

In the vignette for the lspline package in R it says that the package computes Linear splines with convenient parametrisations ...
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Test for equal parameters of two regression models: compare coefficients directly or check if interactions are zero?

I have two data sets and obtain regression models with coefficient vectors $\beta_1$ and $\beta_2$. I want to test $$H_0: \beta_1 = \beta_2$$ against the alternative that the two vectors are not equal....
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Difference In Differences with Daily Numbers

I ran a DID regression and found my estimate on the DID coefficient to be .022. The units of time I am using are days, and at a certain day around halfway through my data, the treatment group was ...
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Regression coefficients do not match conditional means

In a nutshell, I want the regression coefficients of a model to match several differences in conditional means. You can download the data from this repo. I have a data set that has a dependent ...
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why the sum of two variables is insignificant while each of them are?

When I regress stock returns of period $t$ on stock ownership of period $t-1$, the coefficient on this lagged stock ownership is insignificant. However, when I disaggregate the lagged stock ownership ...
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Regression - fitting with linear combination [duplicate]

Consider a linear regression model with two regressors x1 and x2. Suppose, I fit a new model with regressors x1+x2 and x1-x2. Are these two models equivalent? What is the relationship between the ...
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Why are the estimates of three mixed models so different from each other?

so I conducted an experiment in which I am trying to model the relationship between my response yield [dt/ha] and the predictors soil moisture [%] + weed coverage [%]+ treatment + distance + date and ...
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How to obtain the standard errors in Mean Group (Pesaran, 1995) estimator for panel data?

My question is very specific. I want to know how to obtain the standard errors of the Mean Group coefficients obtained by the Mean Group estimator developed in "Estimating long-run relationships ...
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How to compare two methods using regression

In the above question, I am supposed to compare method 1 (pre-use current) to method 2 (post-use current), using linear regression, I know you can use hypotheses testing to check if the difference ...
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Regressing on a variable, and then regressing the residuals on another variable

Consider observations on three variables $X1, X2,$ and $X3$. Suppose that $X1$ is regressed on $X2$. When the residual of the above regression is regressed on $X3$, the regression coefficient of $X3$ ...
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p-values of standardized vs non-standardized regression model coefficients - are they the same?

I made the following simple regression model and used stargazer to output a table that plots the standardized vs non-standardized regression model coefficients. ...
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A faster way of finding unbiased estimators for this linear model

No access to computers or calculators is available for this problem. Consider the following linear model $$Y_1 =\theta_1 + \theta_2 + \theta_3 + \theta_4 + \theta_5 + \theta_6 + \epsilon_1\\ Y_2 =\...
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Find the correlation coefficient of X and Y

Suppose X and Y have a joint pdf f(x,y)=x+y, 0<x<1, 0<y<1 Find p(x,y) (rho) aka the correlation coefficient of X and Y. ρ=Cov(Z,X)/σZσX = {E(XY)-E(X)E(Y)}/{sqrt(Var(X))*sqrt(Var(Y)}
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Can I use zscore to calculate pvalue of coefficients in polynomial regression model?

Recently I am trying to reproduce results from this paper. The author performed microassay to detect gene expression in mutiple overlapping time window. Take time window 1 for example, let's say there ...
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Inverse scaling of coefficient using SkLearn

I had constructed a simple Multiple linear regression model, where I have 2 independent variables and a target (dependent variable). Now, I transformed my independent variable using ...
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How to interpret log a share in a log-log model

my dependent variable Y is a percentage number and I have transformed it additionally into a logarithmic form. How do you interpret the resulting coefficient on log(I(X^2)) in this log-log model? A 1% ...
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Linear Regression: Minimizing proposed changes to the response variable with a goal of statistical insignificance?

I am performing a linear regression for a pay equity analysis. That regression will typically look something like this (where yearsOfExperience is a stand-in for one or many controls that may be ...
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Controlling for covariates in fixed effects regression

I have a panel dataset of students with their test scores and certain characteristics like student gender and parents' education. Let's call the main regressor of interest "x". If I control ...
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coxph() ran out of iterations and did not converge

Am relatively new in conducting survival analyses in R. I wanted to perform an univariate cox regression on my data set. For some of my variables this worked, but for the variable “white blood cell ...
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Interpreting Logistic Regression Coefficients Under Collinearity

I thought this would be an easy question to find an answer to, but for the life of me I am having trouble finding anything that fully addresses my current problem: Consider a situation where we are ...
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Can a natural logged control variable drastically change a regression?

Hello I am writing my undergraduate accounting & finance dissertation so my statistical knowledge is quite basic. So one of my OLS regressions has Firm value as the dependent and CSR as the ...
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If "conditional to random effect" in mixed models a kind of averaging or calculated differently?

I read practically every discussion in this forum, and still I don't get it. I'm sorry, but all the explanations still don't tell me how to interpret it. Please don't cite other articles, as I saw all ...
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How to assess the "reliability" of standard errors?

I am studying linear regression and in particular, I am trying to solve an exercise from my book. The model I am focusing on is about wages and education and the text gives me the output of the ...
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Is cross-validation necessary when computing significance of coefficients?

I'm unclear on if its important to perform cross-validation when determining if a dependent variable has a significant effect on my independent variable in multilinear regression. Specifically, I'm ...
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What is mathematical relationship to be able to determine number of times higher an even occurs in a logistic regression coefficient

I'm working through material on logistic regression and I'm trying to understand how the mathematical relationship works to be able to make a certain claim. This excerpt comes from Beyond Multiple ...
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Parameter Estimation on S1 model

I have the following model of creating a random graph on the circle: First, N nodes are uniformly distributed on the circle of radius $N/(2\pi)$ to give a node density of $1$. We sample the expected ...
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Help Understanding Polynomial/Least Squares Regression

I have a dataset of 2 variables (called x with shape n x 2 values of x1 and x2) and 1 output (called y). I am having trouble understanding how to calculate predicted output values from the polynomial ...
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How to interpret a regression with both time and individual fixed effects?

Let's say we have the following regression $Y = \alpha + \beta X + \gamma W + u$ the way I interpret $\beta$ is "the effect of $X$ on $Y$ keeping $W$ constant". Now let's say that I have ...
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Logarithmic regression with three constants (or coefficients)?

Looking for a method, model, or program that can assist with logarithmic regression of the (apparently unusual) form: y = a + b*log(x - c). In other words, assuming a data subset from the middle of a ...
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Coefficients interpretation after recovering raw coefficients from a regression which used orthogonal regressors

I have an unbalanced panel of 747 observations and 15 years. After testing for Pooled, FE and RE, FE is the "best" model. However, I have multicollinearity problems. I can either remove one ...
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How does censoring an observation at baseline impact regression coefficients in survival analysis (e.g., Cox proportional-hazards model)?

I have a dataset with 28000 patients at baseline, of which approximately 1100 have had only a baseline visit. A logical choice would be to censor these observations (0) at time 0. However, I wonder ...
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Addding a categorical variable to existing regression model generates strange coefficients

I have a regression model with numerical variables only. I created a new feature, categorical variable with options A, B, C. The means of the dependent variable are, by the categories from above are: ...
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How does one calculate the significance of the coefficients of a linear regression? [duplicate]

When I run a linear regression in the form of $y$ = $\hat{β}_0$ + $\hat{β}_1x$, I not only can calculate the values and SE of $\hat{β}_0$ and $\hat{β}_1$, but also their z-scores. Now what I don't ...
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Should you include the ratio of two variables in survival analysis?

Suppose I have the following (Rossi recidivism) dataset: ...
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How are random effects being included in the linear mixed model along with the concept behind their calculation

I'm having difficulty in understanding the "process" that is going on behind how we are calculating all of our parameter estimates and how the random effects are used in our models. To begin ...
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Is the PARTIAL regression coefficient always smaller than the SIMPLE regression coefficient (when all variables are positively correlated)?

Suppose we have three variables: X1, X2, and Y. X1 and X2 are the independent variables (IVs) and Y is the dependent variable (DV). Suppose that each IV is positively associated with the DV. Suppose ...
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the coefficient of a variable is the average of the coefficients of its two parts in generalised estimating equation models

I used the z-score of each variable in generalized estimating equation models. one independent variable A was divided into two parts, and the z-score of each part was taken as an independent variable. ...
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Parameter estimation in a Berkson error model

I study Mathematics and I want to use a Internet game to practice what I learn. In the game I am the manager in a basketball team. Players have a salary. I want to estimate the coefficients in the ...
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Simple linear regressions among three pairs of variables

Let the "ordinary-least-squares regression of $Y$ on $X$" be given by $$\hat{y}_i = \hat{\beta}_0 + \hat{\beta}_1 x_i\text{.}$$ Suppose I run the following: The OLS regression of $Y$ on $X$ ...
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Why can't OLS estimates be used to obtain regression parameters when dealing with high dimensional data?

Suppose I have a data set consisting of $n$ observations: ${\displaystyle \left\{\mathbf {x} _{i},y_{i}\right\}_{i=1}^{n}}$. If I apply linear regression :${\displaystyle \mathbf {y} =\mathrm {X} {\...
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X intercept of a log-log linear model in R using lm ()

A linear regression on dependent and predictor variable was run on simulated data after log transformation. ...
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Propensity score matching in difference-in-differences

I have a data set in which I have treatment, event, and treatment*event vectors, along with other variable vectors that I have computed. I ran my regressions and find my coefficients and their ...
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Effect of zero-variance variables on logistic regression

Imagine that due to pipeline/workflow issues a logistic regression model that's in production has some binary variables in it that are positive or negative for all observations in the modeled ...
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