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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cents per gallon to gallons per person - regression intepretation

Equation: fuel = B0 + -7.441gatax fuel: motor fuel uses in (gallons per person) gatax: state gas tax in (cents per gallon) How would you explain a 1-unit increase in the gas tax? thanks for any ...
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Calculating the standard errors of the standardized regression coefficients from an article

For a systematic review I want to calculate a confidence interval around the standardized regression coefficients for a multiple linear regression model, e.g. using the following effect size ...
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Combined Versus Split Regression Model Coefficients

I am working on a semi-unsupervised model, where the model itself takes coefficients of a regression as inputs. I have a criteria for separating the data within one regression (indicator variable), ...
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Can you use the inverse normal probability of a variable as the dependent variable? [closed]

And then regress this variable on your independent variables? And then obtain the normal distribution function on your estimated values and use this as your estimated value? Is this econometrically ...
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Find highest scoring yet most consistent performer

I have several measurements with a mean and a standard deviation (but I believe that the coefficient of variation is more useful here). For example: A: Mean (in regards to the total): 90%, CV: 25% ...
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Help in Maximum Likelihood Estimation for ARIMA Model in R

help in maximum likelihood estimation I used seasonal arima model on my univariate data set with order ...
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Linear Regression with coefficient of a, b, c and d?

First I am a beginner and am trying to understand linear regression. I was reading an article and saw a formula: ...
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lme4 mixed model output coefficients seem incorrect

I have some data for carbon assimilation vs tree size for a range of tree species. I'm running a mixed model analysis using lme4 in R, with the random effect being ...
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Calculating simple effects from standard regression output

This question seems so basic I am almost embarrassed to ask it, but my need for clarity has finally exceeded my need to pretend like I know everything. I am testing the effect of prior training on ...
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Equivalence of ANCOVA and alternative model

Consider an RCT with individuals i in 2 arms (group, with 0 = control and 1 = treatment) in which one metric outcome (score) is collected at baseline (pre) and after some treatment (post). In an ...
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How can I compare incremental-r2 between groups?

0 I have a dataset (n=6000) of individuals belonging to three different ancestry groups (african (n=2000), native american (n=2000), european (n=2000)). I am studying how well a predictor (x) ...
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Testing if coefficients are statistically significantly different across models

I will be building two zero-inflated negative binomial (ZINB) regression models, where each model is aiming to predict different disease count outcomes based on the exact same independent variables ...
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R choose which element of factor variable to throw out to produce only positive coefficients [duplicate]

How to manually choose which element of factor variable to throw out? Or how to automatically throw out the element with the least coefficient so that in the final model we have all the coefficients ...
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estimation of polynomial regression: bootstrap approach

Assume, one deals with polynomial regression, i.e. $$ y_{i} = \beta_{0} + \beta_{1}x_{i} + \beta_{2}x_{i}^{2}+ \dots + \beta_{m}x_{i}^{m} + \varepsilon_{i}, $$ where $i = 1, \dots, n$, with $m < n$...
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Difference in regression coefficients of sklearn's LinearRegression and XGBRegressor

Using the Boston housing dataset as example, I'm comparing the Regression Coefficients between Sklearn's LinearRegression() and xgboost's XGBRegressor(). For XGBRegressior, I'm using ...
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Linear regression $Y=X\beta+e$ with random coefficients $\beta$

Consider a linear regression model $Y=X\beta_0+\epsilon$. Here $Y$ is the response random vector of length $n$, $X$ is an $n\times p$ matrix, $\beta_0$ is a constant vector of length $p$, and $\...
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How to find coefficients for Logistic Regression [duplicate]

How do you find the coefficients for logistic regression? Is it a case of just transforming the samples from the dependent variable and preceding to fit it like a linear regression?
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Normal equations for multiple linear regression using covariance matrix [duplicate]

I find in many textbooks the normal equations for multiple linear regression: $$\hat{\beta} = (X^\prime X)^{-1} X^\prime y$$ However, I am interested in estimating the regression coefficients using ...
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Bootstrapping logistic regression coeffs with z-scored predictors in logistic regression

Hoping someone can help clarify why there is a discrepancy in regression coefficients when applying bootstrapping to z-scored vs. raw data. There is probably a simple explanation but in all my ...
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Correct interpretation of coefficient estimates from GLM on binary outcome data [duplicate]

I'm currently analysing an experiment where animals were presented with a stimulus under two different treatments (Po & Br) ...
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Different Formulas for the Standard Error of Regression Coefficient

Premised that I am no expert in stats or algebra (but I am trying to learn), I have found these two different formulas for the standard error of the regression coefficient. \begin{align} \...
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Regressions - variable effect

This is more of a theoretical question than concerning a specific data set. Say that I have a dependent variable Y and want to check if 4 different explanatory variables X1, X2, X3 and X4 has an ...
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Test for difference of coefficients in two logit regressions

I have the following problem. I have a sample of $n$ observations and divide it into two non-overlapping subsamples with size $n_1$ and $n_2$ correspondingly. Then I run logit regression for both ...
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Negative relationship but regression analytics gives positive correlation coefficient

I've been trying to look for a question like this but I simply see positive correlation coefficients. I'm new to this so forgive me if I'm not really familiar with the terms. I'm doing an analysis on ...
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The lines on my scatterplot for ANCOVA results doesn't look right, personal error or model error?

I ran an ANCOVA model, to test the effect of treatment on the relationship between two continuous variables (elephant number and plant density) - please see more details in my last question (What ...
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Why is odds ratio used when interpreting logistic regression?

I am fairly certain when interpreting logistic regression output, the odds ratio should be used instead of the estimated coefficients; however, I am unable to figure out why this is the case. So my ...
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When using Lasso and calling coefficients (.coef_) which is the coefficient of the constant? [closed]

By calling .coef on the Lasso model built, there are only numbers corresponding to the coefficients. These coefficients are supposed to match, say, the columns of the pandas dataframe given as input. ...
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Variable Importance sorting by absolute value of x or fully standardized coefficient?

I am looking at the output of a linear regression model and would like to sort the IVs by feature importance. In this case I want to use the absolute value of the standardized coefficients since my ...
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Comparing Regression Coefficients from a “log-log” to an Alternative De-meaning Procedure

Consider two regression models: $log(y_i) = \log(x_i)\alpha + \epsilon_i \,\,\,\,\,$ (Model 1), $log(y_i) = (\frac{x_i}{\overline{x}})\beta + \varepsilon_i \,\,\,\,\,\,\,\,$ (Model 2), ...
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Is there a difference between $\beta$ and $\theta$?

I've seen both $\beta$ and $\theta$ used to indicate model parameters in different publications. For example, Andrew Ng uses $\theta$ in his ML course and Gareth James et al use $\beta$ in ISLR. My ...
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Multiple regression when the dependant variable is unmeasured or hidden

Say I was measuring the individual performance of each of a group of athletes every week. I measure things like running speed, jumping height, grip strength etc. I want to use these scores with ...
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Where are the Wald p-values and where are the LRT ones in the resulf of mixed models? [closed]

I read, that there are many methods of determining the degrees of freedom, thus calculating the p-values for fixed effects in mixed models. I read, that the worst is the Wald test and the Log-...
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Linear Regression: P-values of t-test of significance of regression coeficients are same as p-values of F-test about submodel

Suppose we have regression problem: $$Y = \beta_{0}+\beta_{1}X_{1} + \beta_{2}X_{2} + \epsilon \text{, } \epsilon \sim \mathcal{N}(0,1),$$ where $X_1 \sim U(0,1)$,$X_{2} \sim U(1,2)$, and we suppose ...
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Interpret Coefficeint as change in Percentage-point or Percentage

Having carried out the regression below, I'm struggling to determine what the correct interpretation of the predictor variable would be. Given that the dependent variable is binary, where 1=...
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What is a reason that in Lasso Regression we can force all coefficients positive & intercept =0?

I have a regression problem where I need all coefficents to be positive and the intercept to be zero. I can do this in sklearn but i don't understand how the algoritm can force this conditions through ...
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Marginal means vs. marginal effects. What is the difference?

In R, there are two packages: emmeans and margins. The first implements the LS-means known from SAS, here called estimated marginal means, the second implements the margin command from Stata. I ...
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In which paper did this formula appear? [closed]

I want to use this formula in my paper, but I don't know which paper or book to cite. Can anyone tell me which paper I should cite?Thank you! The formula is related to linear regression. $\hat{Y}_i =...
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Relating Two Derivatives (and Elasticities) of a Log-Log Regression

Consider a standard "log-log" linear regression model like this: $\log(y_i) = \log(a_i + b_i)\delta + \epsilon_i$, where $y$ is the dependent variable, $a$ and $b$ are two independent variables, and ...
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How to interpret coefficients of parametric terms in comp.risk?

I am trying to fit a flexible competing risks semiparametric regression model with the timereg package. My primary goal is to estimate the effect of Z on the cumulative incidence of the event of ...
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Multiple regression and partial correlations with more than 3 predictors

I need to estimate slopes of a multiple regression that has 5 independent variables: $$y = \alpha + \beta_1 x_1 + \beta_2 x_2 + \beta_3 x_3 + \beta_4 x_4 + \beta_5 x_5$$ The challenge is to estimate ...
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Why do regression estimates provide lower relative error than averaged values?

I am trying to estimate the per-cell protein concentration for some samples. I have performed a series of protein extractions for each of my samples, with each extraction using an increased (and known)...
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Interpreting the Odds Ratio of a logistic regression model

I'm currently working on building a logistic regression model with the aim of predicting whether a given stock index will go up or down the following day. The table below shows the 3 models I've ran ...
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How to identify weak predictors from financial data

I have a financial data.frame that contains quarterly data for each stock in S&P500 - 16 quarters for each stock, a total of 8000 rows. What I am trying to do is to explain 30-day volatility (...
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Using the autohotencoder in PySpark for a linear regression but no reference category

I created dummy variables using the autohotencoder and as I have learned dummy variables you also need to have a reference category. However I have 7 dummy variables for the weekdays for example, so I ...
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R: How to create equation from logistic regression glm() model coefficient estimates? [closed]

I am trying to create a formula from the published glm() model coefficients estimates, i.e. I don't have raw data to reproduce the model. Further, I want to apply ...
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Regression coefficient problem

The question asks that when the case is $X_1 = 1$ (when I am an asian instead of other ethnicity, a dummy variable), then what is the value of $Y$? As the $b_1$ has a P-value much larger than $0.05$, ...
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Insignificant coefficient in a regression

To simplify the question, for example, the interception, which is Beta 0, is +500 and the predictor X1 being 1, Beta1 being negative 100 and other predictors Xi are all 0. i.e. Y = 500 -100 X1. The ...
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fitting suitable regression model to identify predictors from contingency table

so a study was conducted for some game and the probability of success of the game was noted in a contingency table. I have a 5x5 contingency table which is age group by task difficulty(split into ...
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Significance test for coefficients of elastic net

I have a 150x41 dataset, on which I performed variable selection and regression with Elastic Net. The response variable is continuous. I'd like to test the significance of the coefficients that I ...
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multiple regression coefficients - Standard error of intercept

I am implementing an R-type summary() function in python with the restriction to exclude use of scientific libraries. (assignment) I found this https://www.nd.edu/~rwilliam/stats1/x91.pdf material ...

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