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

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K-fold Cross Validation. R squared value?

I am using multiple linear regression with a data set of 72 variables and using 5-fold cross validation to evaluate the model. I am unsure what values I need to look at to understand the validation ...
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13 views

Fitting a good model in multiple linear regression cases

We assume to have multiple features and we would like to fit a good model through multiple regression. in the following case I can't graph all the features in a graph because we have many features and ...
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12 views

Repeat measures regress

I have a question about using regression for repeat measures analysis. I have a design in which each participant viewed 4 sets of pictures. 2 sets were positive and 2 were negative. There were 2 ...
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21 views

Regression without intercept [duplicate]

I saw that here explain how to get the formula for getting a regression without intercept but I already know it (for example in R you get it outomatic with ...
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1answer
17 views

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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1answer
23 views

Rearrange regression equation that includes a dummy variable

This is my regression equation: $10 = 5.44 + 0.26X_1 - 3.19X_2$ $X_2$ is a dummy predictor with two levels. Assume that the value of $X_2$ is 1 therefore regression equation is: $10 = 5.44 + ...
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2answers
132 views

Binary outcome in randomized controlled trials — OLS or logistic?

I'm running a randomized controlled trial which has good balance in the co-variates. I'm unsure whether to use: OLS: $P(Y_i=1) = \beta_0 + \beta_1 \text{Treat} + \epsilon_i$. This is problematic ...
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1answer
39 views

Matrix Inversion Error

I a Multiple linear regression model, from published literature, I am implementing a spreadsheet to generate new predictions based on the published model. the literature stated Coefficients and the ...
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15 views

how to handle dummy variable in variable using stepwise

I created 2 dummy variables for educational level that is edu1 and edu2 for multiple linear regression. After using the stepwise method only edu1 was select with other variables. Should I include a ...
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1answer
40 views

Mediation model: is it wrong?

From time to time it crosses my mind that the mediation model so widely used in psychology area of research is not a good model, because it 'works' when two variables are correlated. During my ...
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17 views

Will a pooled coefficient be bounded by the coefficients from the group regressions? [duplicate]

Consider the linear regression model, $y = \beta_0 + \beta_1x_1 + \beta_2x_2 + u, u \sim N(0, \sigma^2 )$ If we estimate the model twice using OLS on two mutually exclusive groups (say, group 1 and ...
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11 views

Creating a new (dependent) variable with several indicators

I'm studying political science and my aim is to test whether foreign aids have effect in improving governance. I want to measure governance by World Governance Indicators (WGI). But the problem is, ...
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24 views

Multiple Regression - effect size

I want to calculate the effect size of a multiple regression. So far, I used Cohens f^2. Somehow, I wonder, if the effect size expressed by Cohens f^2 is an appropriate measurement. Let's assume ...
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1answer
30 views

Practice problems for linear and non linear regression [closed]

I am new to statistics and am developing an interest in learning regression analysis. To be more precise, can you point me to some online resources where i can find real world data sets and regression ...
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105 views
+50

Modelling mortality rates using Poisson regression

I'm examining trends (between 1998 and 2011) in mortality rates among patients with Crohn's disease. Each patient (case) have been included during 1998 to 2011. At inclusion, each patient have been ...
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21 views

Finding standard error of beta coefficients in ridge regression using lambda

I need to get the standard errors of coefficients with Ridge Regression, by calculating the SE of the beta estimates after I choose the right lambda. ...
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1answer
70 views

Why do we use the term multicollinearity, when the vectors representing two variables are never truly collinear?

When two vectors $a$ and $b$ are collinear, then $a = xb$, (where $x$ is a scalar) so in linear algebra, collinearity is a narrowly and clearly defined (and binary) concept. Two vectors -- in my ...
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1answer
16 views

Modelling ordered data which violates proportional odds assumption

I have a dependent variable which describes how many pounds an individual contributed to a cause. The amount is in whole pounds and out of a maximum of 5 (ie. 0,1,2,3,4,5). I have 2 independent ...
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26 views

understanding of p-value in multiple linear regression

Regarding the p-value of multiple linear regression analysis, the introduction from Minitab's website is shown below. The p-value for each term tests the null hypothesis that the coefficient is ...
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2answers
78 views

Do I need to take out any predictors from multiple regression if I put in some principal components as additional predictors?

I have an assignment which involves one area-level dataset made of $366$ scale variables. I have to perform PCA, compare it with rates of an additional response variable $X$, and comment on its face ...
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1answer
33 views

How to compute robust standard errors of the coefficients in multiple regression?

So I know that to find the coefficients of the BLP of some data is to use the formula, $$\vec{\beta} = [{\bf X}^{T}{\bf X}]^{-1}{\bf X}^{T}{\bf Y}.$$ However, I also want to find the variance, and I ...
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1answer
60 views

Multiple regression or anova or bestglm or forestplot or Boruta

I have data on a continuous health variable and following others: age, gender, height, weight, waist, city and season. I applied multiple regression and got following output: (age, gender, height, ...
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2answers
91 views

Multiple regression analysis - using all possible interactions

I have data on about 8000 persons and I am trying to find independent predictors of a health outcome variable (yvar). The predictor variables are age, gender, height, city and 3 other predictor ...
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3answers
71 views

Can I use regression to predict a binary variable based on 35 variables?

I try to build a model behind a dating website which gives an optimal match between two people, based on 35 variables such as: age location interests characteristics car yes/no etc My ...
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1answer
9 views

Wald test to compare equality of regression weights (MR) - correct for multiple testing?

Suppose I have a linear regression with 5 predictors (x1 to X5) and 1 outcome (y). I want to see whether the effects of X1 to X5 on Y differ between boys and girls. A possible answer may be: the ...
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1answer
13 views

Prediction on Interaction Terms in Multiple Linear Model

I have created a MLR model where my predictor variables are continuous and categorical. I am interested in the interactions between the categorical variables. Let's say I have the response variable ...
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1answer
50 views

Added interaction term, standard errors inflated

I am running a simple regression of an index of cardiovascular health (Heart Rate Variability) on Age and Gender (as a dummy variable), n=430. I first ran: $$HRV \sim \beta_0 + \beta_1Age ...
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1answer
21 views

Retrieving the Unstandardised coefficients from a Standardised Regression

Is it possible to retrieve the Unstandardised Regression Coefficients from a Standardised Regression? If so, how is does one do this in order to use the coefficients to make predictions on new data? ...
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34 views

Is this analysis prudent? Running several multiple regressions to gain insights

I'm concerned that I may not be conceptualizing/applying multiple regression correctly; I would greatly appreciate some guidance. Lets say that I'm trying to understand how to get a TV audience to ...
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1answer
35 views

Distribution Assumptions in Ridge & Lasso Regression Models?

What are the assumptions for the distribution of the features for regression models like Lasso regression or Ridge regression? Why is it better to have features with Gaussian distributions?
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2answers
172 views

How to interpret standardized regression coefficients and p-values in multiple regression?

I've been using R to analyze my data (as shown in example below) and lm.beta from the QuantPsyc package to get the standardized ...
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23 views

Forecasting sales for multiple departments using external factors

I have got the weekly sales information for various locations for about 3 years.It has got information for 157 weeks.Also,I have got the probable external factors affecting the sales.I want to ...
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13 views

How do I compute for the utilities in a choice based conjoint analysis?

I want to learn how to compute the utility value or estimate part-worths of the individual attributes in a conjoint analysis. Is there an equation to help me figure it out? All I see are software ...
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1answer
35 views

Which regression model to choose? [duplicate]

I have two models, one lm(y ~ x1 + x2 + 0) which gives me a close to 0.90 something $R^2$ and another model lm(y ~ x1 + x2) ...
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16 views

Multiple variable analysis for curvilinear seasonal data

This question is related to How to analyze curvilinear seasonal data I have data like following: ...
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17 views

How to choose right step size for alpha in the Elastic net using glment package?

I'm using glmnet to learn different Elastic net regression.as you know, Elastic net would perform at least as good as Lasso regression. but it's not the case for me and Lasso perform better than ...
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1answer
74 views
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57 views

About stepwise regression and correlation

I am trying to fit a model to some observed data with the least squares method. Now, I am at the stage where I have run a stepwise regression (traditional), with Entry level $=0.025$ and Stay level ...
3
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1answer
158 views

How to implement model in R?

i would like your help to implement this model in R or more explicity where yt = monthly mean values μi = mean value in month i, i = 1 . . . 12 . I1;t = Indicator series for month i of the ...
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33 views

How to estimate the correlated individual components from a sum, for a random process?

Assume that there are $N$ realisations of five individual, random variables$X_1$, $X_2$, $X_3$, $X_4$ and $X_5$, which in general could be correlated. We define another random variable ...
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49 views

How to interpret redundancy?

I have trouble making sense (i.e. real-world sense…) out of some of my results. I have Y and X1 and X2 for different geographic areas. Meaning they are the same variables, but their actual values are ...
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29 views

Multiple, multiple regressions?

I have done a study on whether personality and demographics predict interaction on Facebook brand pages. I have used a Big five personality scale and the demographics include, sex, age, marital ...
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3answers
60 views

Testing and reporting interactions in multiple regression

I have a model with two between-participants predictors -- one continuous (a), and one categorical with two levels (b) -- and ...
2
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1answer
80 views

How to estimate the individual components from a sum for a random process?

We have $N$ realisations of five individual, IID random variables $X_1$, $X_2$, $X_3$, $X_4$ and $X_5$. We define another random variable $S = X_1+X_2+X_3+X_4+X_5$. Now, for a given $S$ generated from ...
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1answer
66 views

Multiple Linear Regression Variable Selection

Using all possible subsets we consider the adjusted $R^2$, Akaike's Information Criterion (AIC), corrected AIC ($AIC_c$), and Bayesian Information Criterion. The model with the highest adjusted $R^2), ...
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2answers
91 views

Solving a regression equation

This is a simple question but I am new regression analysis. If my regression model is of the specification, $\ln(y) = \alpha + \beta_1 X_1^2 + \beta_2 X_2^2 + \epsilon $, and I have estimated ...
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20 views

VAR model for price forecasting in multiple time-series context. How to get “real figures” as forecasts?

Sorry for the rather long introduction, but since I was (legitimately) critizised for not explaining my cause and questions enough, I will do so now. I would like to conduct a (price)-forecast based ...
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1answer
40 views

What does the Argument “type” in VAR() - function do?

Right now I am working with vector autoregressive models in order to make 3 months forecasts for a commodity good (sawlogs) y. I have several time-series of "follow-up-products" of sawlogs that should ...
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1answer
49 views

Analysis where dependent variables are proportions

I have a set of demographic data (age, race, social class, etc.) for selected geographic areas. These independent variables are each proportional in each type, i.e. Area A: White 70%, Black 20%, Asian ...
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2answers
75 views

Why monthly stock returns instead of daily returns in multiple regressions?

This is probably a naïve question. Why do many multiple regression analyses of the Fama-French 3 or 4 factor model of fund returns use monthly return data instead of daily return data? I would have ...