# 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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### Interpretation regression coefficient percentage points

I have a simple linear regression model, where the independent variable is defined in percentages (%) while the dependent variable is in percentage points (difference between two yoy %-rates). How ...
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### Interaction effects and insignificant main effects - Back to basics

Imagine the following regression model: $\text{Abnormal Returns} = b0 + b1*SENT + b2*SIZE + b3*SENT*SIZE + e$ SENT is a standardized variable. SIZE is equal to 1 for "uncertain" firms, and 0 for ...
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### Quantitative and categorial predictor in one model

This is what I would like to know, due to some logical problem behind! I have a model as: Crown radius = Diameter at breast height + Location DBH is quantitative, like 30cm, 40cm... Location is ...
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### Interpreting what this means in a paper - significantly different at the .05 level? [duplicate]

I am having a hard time interpreting what something means in a paper I'm trying to get through. If you care, this is the paper: Gender Differences in the Effect of Education on the Slope of Experience-...
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### Java and R: Least Squares Coefficient Estimation - Start at time Zero?

This is the data set I have: vector <- c( -7.459981, 13.26651, 12.10128, 2.380662, 26.42393) Doing an estimation of the coefficient with a linear regression ...
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### Running all possible additive combinations of a linear model and averaging the coefficients

I have nine predictor variables and one response and when I run a linear model in R I'm getting negative coefficients and non-significant p-vales for essentially all the estimates. I've examined the ...
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### Multiple Regression - Converting Standardized Coefficients to Unstandardized

I recently performed a multiple linear regression using a standardized set of data, and I was wondering if it possible to convert the standardized coefficients from the regression into usable ...
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### Simple linear regression and sampling

I have a small dataset (60 elements) for which I fit a simple linear regression model, and obtain a small coefficient of determination ($R^2 = 3\%$). I'm a beginner in statistics so I'm trying to ...
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### Positive coefficient but negative marginal effect in mlogit

Is it plausible to have a positive coefficient with a negative marginal / impact effect after running multinomial logit model?
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### Imputation model: Pooled model is insignificant. How to interpret?

I have ordinal data on three IVs ranging from 1 to 5 as below: IV1: Not at all Important - Very Important IV2: Not at all Satisfied - Very Satisfied IV3: Performs much Worse - Performs much better ...
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### main effect significant while interaction insignificant in moderation analysis?

Please help with the following output. I have two IVs Example: (happiness IV1) (genderIV2) say on performance (Dv). question 1- I ran simple regression for happiness and performance as well as gender ...
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### Impact of individual features under multi-collinearity

Assume the following scenario: I have four features: $x_1$, $x_2$, $x_3$, and $x_4$ There are non-negligible multi-collinearity among the features. I want to predict $y$ (response variable) with ...
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### Removing multi-collinearity with PCA for regression analysis

I'm interested in studying the impact or importance of each feature on the response variable. I'm thinking running multiple linear regression with multiple features, and running regression analysis ...
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### R quadprog for coefficient constraints

I have the model that I need to estimate, Q = B0 + B1*Q1 + B2*Q2 + B3*Q3 + B4*Q4 + B5*Q5 with the coefficients constrained to: B2 * B5 - B3 * B4 = 0; I believe I can use the quadprog package to ...
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### simulate data for multiple regression based on standardized coefficients and covariance among predictors

I want to simulate data for multiple regression based on standardized coefficients (denoted $\beta^{'}$) and covariance structure among predictors. My problem is that I don't know how to determine the ...
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### SpatioTemporal regression

I have a data-set containing rain value for 6 stations and station coordinates (lat,lon). I used lm function taking lat,lon,day, their interaction and rain as below: ...
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### Identifying most significant variables in multiple regression

Imagine that the total cost for 100 patients undergoing the same procedure in a hospital, is further broken down into 10 cost categories (such as the surgery fees, room charges, consumables cost etc). ...
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### Dealing with oversized effects in Linear Regression

I'm learning about GLMs and interpreting regression coefficients and so I'm experimenting with simulated data and pymc3. I've synthesised a dataset where X is an array of 5 normally distributed ...