# Questions tagged [multiple-regression]

Regression that includes two or more non-constant independent variables.

3,497 questions
1answer
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### Can I use predictor variable in percentages in multiple linear regression?

The situation is as follows: Outcome variable is numeric, and values are indicating salary of a subject. And I have 3 independent variables: Age (in years) Experience (in years) Skill in percentages (...
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### LME/Multiple regression with many predictors and limited DV range

For a single-case patient study (case profile), I have 20 IVs such as medication intake, amount of sleep etc; and one DV representing the severity of the symptom reported by the patient in each of k=...
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### Different error weighting for positive and negative residuals for OLS?

For OLS-estimators in multivariate regression analysis, it logically doesn't matter whether an error is positive or negative. I was wondering if in some situations it might make sense to weight a ...
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### Including or excluding a variable and what about the p-values when VIF = 5.2?

I'm writing my master thesis and run into a question about multicollinearity. I have two interaction effects which have a high VIF (5.2, 4.8). Both are interaction effects between categorical ...
1answer
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### Can i use an independent variable in % units in a probit regression

I want to do a probit regression and one explanatory variable is given in % units. Do i have to transform it in decimal units or can i use it in % units in my probit regression?
1answer
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### A question about the Least Squares Estimation: what motivates its definition in the general case?

Let $Y_{1},Y_{2},\ldots,Y_{n}$ be independent random variables with expected values $\mu_{1},\mu_{2},\ldots,\mu_{n}$, respectively. Suppose that the $\mu_{i}$'s are functions of the parameter vector ...
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### Partial Collinearity in Regression

I had a doubt about the effect of multi-colinearity in regression analysis. I understand if two variables are co-related we cannot disentangle the effects of one from the other on the target variable ...
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### How to calculate the coefficient of a dummy variable reference category?

I am currently building a regression model with numerous continuous, categorical (employing dummies) and interaction variables. I understand we must use k-1 dummies with one variable becoming the ...
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### How can I fit a multiple linear regression model in R if the value for beta coefficient of each predictor is given? [closed]

I've got an exercise question asking me to fit a multiple linear regression model in R when the values of coefficients are given. I don't know how to do it. specifically, I have 5 predictors in my ...
2answers
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### Adjusted R2 for model with only one independent variable?

Adjusted R2 is said to be more unbiased than ordinary R2 as it takes the number of explanatory variables into account. Can adjusted R2 be used in a model with only an intercept and one independent ...
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### Partailling out approach in multiple linear regression [duplicate]

Assume I run the following regression: $$sales = \beta_{0} + \beta_{1} price + \beta_{2}advert + \beta_{3}advert^2$$ Now I regress sales, price, and advertising separately on advertising_squared ...
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### Interpretation of p-values in multiple regression output

I have data from a survey where I collected demographic information and quiz scores from college students. I ran backward model selection to determine which of my variables affect knowledge. My best ...
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### Regress in two variables against basis functions when one of them might be “sparse”

I'm tasked with the problem of fitting a series of functional forms $\{f_t(S,K)\}$ along the time axis. At each time $t=0,1,\cdots,T$, there are $N_t$ samples (F_{t,i}, S_{t,i}, K_{t,i}),\quad i=1,2,...
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### Control variables not significant

Study: The impact of satisfaction and loyalty on image dependent variable: loyalty independent variables: satisfaction, destination image control variables: age, sex, nationality, number of visits I ...
1answer
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### How to interpret the predicted gender difference in interaction [duplicate]

In my model: Gender=Male, school =education, position =lecturer (ref categories) Model: Score (y) =4.215 + 0.646(logcitations) + 0.299(female) + 1.457 (Seniorlecturer) + 1.804 (AssProf) + 2.620 (...
0answers
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### Complementary log-log or log-log transformation when combining estimates from multiple imputation after cox regression

Can anyone give me an argument for or against using the complementary log-log transformation as opposed to the log-log transformation on survival estimates after cox regression in multiple imputation ...
0answers
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### What's the difference between loadings from partial least squares (PLS) regression and beta coefficients from multiple linear regression?

I have a set of independent variables (X1, X2, ..., X10) and I have run a PLS to find a combination of the X1, X2, ..., X10 that best predicts an outcome Y (a single-variable outcome). As a result, I ...
0answers
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### Logistic regression - binary to continuous - how to interpret?

Given data with a binary outcome, i.e.: $0$ = no event, $1$ = event which can be modeled with logistic regression, how then do we understand the following logic: ...
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### Negative coefficient in model caused by weak multicollinearity

I performed multiple regression and obtained the following model: Q = (0.33495)P + (-76.89321)G + (6.31424)P・G - 3.36334 P = precipitation; G = groundwater; Q = stream discharge The coefficient of (...
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### Multivariate Generalized Least Squares

I'd like to use the generalized least squares (GLS) in the multivariate version. I have a response variable $\boldsymbol{Y}$ with dimension $n \times m$, where $n$ indicates the number of observations ...
0answers
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### Cross-Validation on a multiple linear regression model, negative values?

I'm trying to demonstrate that, using a linear model with too many predictors, that the correlation can be artificially inflated, and that k-fold cross validation can expose overfitting. To do this, ...