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

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Comparing changes in coefficients of two (or more) regression models

I am trying to check for 'significant' changes in the coefficients of two or more regression models. To put this into context, I am trying to perform rolling regression using an auto-regression ...
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1answer
20 views

Is it possible to do a proper demand forecasting through microsoft excel? [on hold]

Is it possible to forecast demand of beverage sales including factors like schemes, temperature, sales of previous period and year etc as independent variables in excel?
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23 views

Interpretation of log transformed coefficients, OLS regression [duplicate]

I have a question about how to interpret or use the result of an OLS regression w a log transformed DV. Due to non-normal distribution of the Dependent variable, I used a log10 transformation to coax ...
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1answer
17 views

Deriving Pearson correlation from regression results

If the common regression results as typically reported in an empirical primary study (sample size n, regression coefficients (Betas), t-statistic, p-value, R^2, adj. R^2) are given in the case of more ...
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2answers
34 views

Heavy-tailed residuals for OLS regression with large n. Implications?

I am trying to fit a multiple regression on a dataset with n=8619. First of all, using an untransformed Y as the response variable (ie Y = aX + bX +..) resulted in a residual plot with increasing ...
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1answer
18 views

Should I keep or eliminate an insignificant confounding variable?

Let's say that I am fitting a logistic regression model for a binary outcome and I have two covariates: $x_1$ and $x_2$ (both quantitative). I am confused as to what the correct course of action ...
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1answer
57 views

Prove that the regression sum of squares can be written as [on hold]

If the intercept is included in the model show rhe regression sum of squares can be wrtitten as $$RSS= \hat{\beta}Z^{T}y-n\bar{y}^{2}$$ where $Z$ is the design matrix, I am having trouble with this ...
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1answer
27 views

How to relate water quality scores to land use percentages?

I have a question related to application of a linear mixed effect model. I have land use data in percentage, which is the predictor, and a water quality score (e.g. 100) as response variable for 100 ...
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7 views

Predicting individual treatment effects as the difference between predicted outcomes with and without treatment

To provide some context, I am trying to (a) identify the best ad to increase support for a particular issue among a large group of people, and (b) identify the people most likely to respond positively ...
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8 views

Difference between calculating partial correlation from multiple regression and regression?

So I am in a bit of a pickle. The way to calculate partial correlation from regression is through the formula \begin{equation} \rho_{x\cdot y\cdot z} = r_{x\cdot y\cdot z} = \frac{r_{XY} - ...
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1answer
9 views

How to test that two covariates have the same impact on dependent variable?

Given the model $y =\beta_0 + \beta_1 x_1 + \beta_2 x_2 + u $ where $x_1$ and $x_2$ have completely different scales and units, is it possible to test whether their impact on $y$ is the same? i.e. ...
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1answer
30 views

High R-squared although many insignificant coefficients

I just did a regression based on the gravity model where I try to identify the most important factors that determine the trade flows. In total I have 18 variables and 363 observations. In fact I would ...
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18 views

calculating goodness of fit and choosing the right model without plotting (R)

I'm trying to evaluate the value of an object, depending on his characteristics. In order to do this, I'm building the following regression model price ~ ., using ...
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0answers
8 views

Problem with model with multiple data points per subject and a covariate

I'm trying to build a general linear model to test a really simple hypothesis: a Behaviour (continuous variable) I observe in 64 Children depends upon Condition (a manipulation I did, two-level fixed ...
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1answer
17 views

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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1answer
14 views

Maximum and minimum penalty in lasso regression family

I am trying to adjust the penalty $\lambda$ in group lasso regression, but I have no idea about it. Just to clarify, group lasso regression is a kind of multiple linear regression which use penalties ...
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23 views

Interpretation of results from PCR models and their comparison to MLR

I believe that my question is really simplistic, but I am completely confused. I am doing regression between experimental parameters and computational descriptors. My task is to find such set of ...
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2answers
85 views

How to tell the difference between linear and non-linear regression models?

I was reading the following link on non linear regression SAS Non Linear. My understanding from reading the first section "Nonlinear Regression vs. Linear Regression" was that the equation below is ...
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1answer
44 views

For the model $y_i=\beta_0+\beta_1x_{1i}+e_i,\quad i=1,\ldots,n$ , does $e_1=e_2$ imply $y_1=y_2$?

Which one notation is correct and why ? $y_1=\beta_0+\beta_1x_{11}+\epsilon_1$ or, $y_1=\beta_0+\beta_1x_{11}+e_1$ or, $Y_1=\beta_0+\beta_1x_{11}+\epsilon_1$ or, ...
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1answer
41 views

How should one assess model fit for non-linear regression?

I am looking at non linear regression. Below is some example output from a non linear regression using MATLAB. There are also two links below this output from the Minitab website. The links explain ...
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4 views

repeat measures, continuous/scale data, 3 dependent variables, 7 independent

Children played a comprehension game on an iPad and their attentional patterns were observed and coded for using video coding software. The duration of 7 different behaviors were coded for. Pupils ...
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Longitudinal data analysis where meaning and metric of response variable varies over time

Determining what factors predict change over time is a topic of investigation in many fields and there are a variety of readily implemented methods for analysing repeated measures in the same metric. ...
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1answer
20 views

Multiple Regression with Predictors that Restrict other Predictors

I'm not even sure if the title of my question makes sense at first sight, so let me try to explain it. I'd like to fit a parametric multiple regression model to data. But depending on the value chosen ...
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1answer
59 views

Modeling a proportion using longitudinal data

To illustrate my question I'll make a (very) fictional example. I have a set of 17 year old people that every year report how many cigarettes they smoked and how many miles they ran. Very few of ...
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11 views

Multiple regression summary for different predictor classes

One question on regression: Following model: M1 <- lm(y ~ x1 + x2 + x3) x1 and x2 are in ratio scale, x3 is a nominal variable, they have values as x1= 1.4, 1.3, 1.2,... x2= 2.1, 2.2,2.3,.... ...
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1answer
27 views

Choosing weights for regression

I want to weight observations for a regression. I'm worink in R and I'm using the method lmrob from the package ...
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33 views

Hypothesis testing on multiple regression coefficients

In the simple linear regression setting, in order to determine whether there is a relationship between the response and the predictor we can simply check whether $\beta_1=0$. In multiple regression, ...
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30 views

Which type of Regression model do I need and what do I need to do to my variable to allow it to work?

thanks for taking the time to read this! A little background, I'm pretty enw to doing most statistical analysis; I've only ever done linear regressions and I tried doing research online but was ...
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31 views

Regression with dependent variable which ranges from -1 to 1

I performed a series of Pearson correlations which give me as expected values between -1 and 1 (actually very few below zero). I'd like now to see if some factors are linked to these correlation ...
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1answer
21 views

Evaluating goodness-of-fit in sequential multiregression [closed]

I am doing a sequential multiregression analysis where I look at how four independent variables (porosity, permeability, sandstone thickness and sandstone depth) labeled $x_1, x_2, x_3, x_4$ influence ...
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17 views

Hierarchical Regression Moderator Analysis

I ran a 2-block hierarchical regression to test for moderation. In the first block I entered the centered IV and centered moderator variable (MV) and in the second block I entered my centered ...
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14 views

Calculation of coefficients in multiple regression [duplicate]

I am trying to calculate the coefficients of a linear regression using 2 or more independent variables. Case for 1 independent variable: Using one independent variable X and one dependent variable ...
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1answer
43 views

Creating an interaction term with 2 continuous variables: What to do?

I want to create an interaction term in SPSS on two continuous variables (ticket price and household income) in order to use this interaction term in a multiple regression model and test whether my ...
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heteroscedasticity in residuals in regression

How to deal with heteroscedasticity in residuals after running regression? if log transformation or any other transformation is applied to the model then it should be applied on actual values of ...
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1answer
42 views

How to calculate the prediction interval for an OLS multiple regression?

What is the algebraic notation to calculate the prediction interval for multiple regression? It sounds silly, but I am having trouble finding a clear algebraic notation of this.
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1answer
31 views

Definition of 'Model Diagnostics'

Can anyone help me out with explaining what the term 'model diagnostics' refers to when applied to multiple regression please? In particular, what tests are necessary to check whether your estimated ...
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11 views

Interpreting results of multiple regression with two categorical predictors

I ran a multiple regression model with 2 categorical predictors: X1 and X2, each getting values 0 or 1 (two factors with two levels each). Both variables were statistically significant. The ...
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2answers
39 views

Linear regression scaling independent variables

I am trying to do a linear regression. My $y$ variable is typical pretty small approx 0 to 0.3 I have some $x$ variables (regressing them individually on $y$ to start with) though that are very ...
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2answers
41 views

Regression analysis or Structural Equation Modelling

I have a 26 items questionnaire refined by running Common Factor Analysis. As a result, I got 4 factors (f1, f2, f3, f4). Each factor is measured by 6-7 items in the questionnaire. These four ...
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How to apply diagnostics to regression model from FactoMineR

Many diagnostics to assess regression models are listed on this page: http://www.statmethods.net/stats/rdiagnostics.html ...
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Standard multiple regression and multiple dependent variables. and bonferroni correction?

I have a question regarding running multiple regression equations with multiple dependent variables. Three independent variables and 3 dependent variables. A colleague advised me to conduct three ...
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13 views

Comparing models using coefficient of determination

What guidelines are there for when we want to compare different models using $R^2$?
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1answer
184 views

Why not robust regression everytime?

Examples of this page show that simple regression is markedly affected by outliers and this can be overcome by techniques of robust regression: ...
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1answer
28 views

Logistic regression model: interpretation of average marginal effect

This is more a beginner question but I am having trouble finding helpful information. Could someone explain to me how to interpret the "average marginal effects" of independent variables from a ...
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2answers
88 views

Interpretation of continuous variable in dummy-continuous interaction

Similar questions have been asked before, but all of them focus on the dummy or interaction term. Say run an OLS regression on the model: $\ln( housePrice )= \beta_1 \times pollutionLevel + \beta_2 ...
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1answer
53 views

Multiple Linear Regression coefficents

I'm doing a linear regression, in R. The values are like this - ...
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2answers
56 views

multiple regression advice on results

I am testing to see if there is a relationship between my dependent variable Y and any of 4 explanitory variables x1, x2, x3 or x4 First I started by doing simple linear regression and got these ...
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1answer
21 views

ANOVA Table for Model In R

I'm trying to figure out how to produce an ANOVA Table in R for a multiple regression model. So far I can only produce it for each regressor, and the Mean Square is calculating as the same as Sum Of ...
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Standardized Coefficients and Partial r

Ive looked over a few of the posts here on regression coefficients and partial regression coefficients but haven't seen an answer to this question, which maybe easily inferred from the other answers ...