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

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LOOCV vs. AIC for Weighted Multiple Regression Model Selection

I am currently trying to determine the most predictive weighted multiple linear regression model to use. I don't have much formal statistical training, so I would greatly appreciate any help with the ...
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16 views

What regression analysis to use? IVs with two levels and a DV with two conditions?

I'm trying to figure out what the best regression test to use for my data. I have three predictor IVs each with two levels. I also have a DV values belonging to two different conditions (A & B). ...
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29 views

If the null hypothesis is true, how will the test statistic be distributed?

I went with T~(50-6) The question goes.... "A regression is estimated with 50 observations, five explanatory variables and with a constant. Suppose You want to test the following hypothesis $H0: ...
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15 views

deletion diagnostics for time series

I'm following a tutorial on time series regression, which discusses diagnosis through selective deletion of data across the entire set of predictors, one observation at a time: ...
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35 views

If $ln(y) = 5 - 0.1X$ what is the elasticity of Y with respect to X, when X=10?

So i got the following model $\log(y) = 5 - 0.1* X$ ...The question is "The elasticity of $Y$ with respect to $X$, when X=10 is..... " i said -0.1 but apparently i'm wrong Isn't the coefficient ...
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10 views

Logistic Regression Question (Adjustments)

I had a question revolving around logistic regression. I'm looking at a data-set for my work that yields somebody as approved or denied (think credit rating applying for a mortgage, similar but not ...
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29 views

Linear regression - Simulation - “what if” scenario

I have an assignment at university and I have been given a simple situation which I would like to explain here. Situation: I would like to perform simulation on purchase price of a product and see ...
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44 views

How do you calculate the test statistic of a hypothesis test with more than 1 parameters?

So the test hypothesis test is $$H_0: B_2 + B_3 =1$$ $$H_1: B_2 + B_3 \ne 1$$ How do you find the test statistic for a hypothesis on the sum of two independent variables? I'm very confused. ok so ...
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30 views

replication of findings in regression models

Let's say we have a dataset for which we constructed a multiple linear regression model and obtained a particular set of $\beta$ coefficients and their significance values. Now, we want to replicate ...
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27 views

I'm in trouble while I'm estimating regression in R [on hold]

I try to estimate robust regression with R. But I am in trouble. I determine all variables. And I estimated regression with OLS (ordinary least square. I can do it. while I doing for robust, I ...
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1answer
19 views

How to deal with missing coefficients while bootstrapping regressions

I'm using R boot() function to perform regression bootstrapping. When boot() resamples my data, can happen that some coefficients are missing, especially in the case of factor variables with many ...
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1answer
56 views

How to calculate the weight of each variable in my multiple linear regression?

When one has built a regression, how to assess the relative contribution of each variable? Let's say I'm working on the energy consumption of a facility. For example: $Consumption = ...
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18 views

Normalize time series data - Wikipedia article counts

I have: 3 wikipedia article access counts (weekly) (A-B-C) Ground truth data (weekly) Total wikipedia english article traffic counts (weekly) My purpose is, build a multiple linear regression ...
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16 views

Multiple Logistic Regression confounding [on hold]

I have gone through an example of loan getting default based upon Regression on parameters such as student, credit card balance and income vs Regression on student only This is called ...
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16 views

Partial correlation - reliability of estimation

I want to test for vanishing higher-order partial correlations as part of a conditional independence test. For computational complexity reasons, I want to condition on progressively larger sets. In a ...
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1answer
32 views

What kind of independent variables can I use for multiple regression?

I'm very new to statistics. My assignment requires me to use one statistical method taught during lesson so I only have a choice between multiple regression, logistics regression and MANOVA. My ...
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10 views

how to write these two inequality? (Asymptotic properties of m estimator)

$T_n^*:=sup\{t|\sum ψ(x_i;t)\gt 0\}$ $T_n^{**}:=inf\{t|\sum ψ(x_i;t)\lt 0\}$ As it's seen in the above figure, $-\infty \lt T_n^{*} \le T_n^{**} \lt +\infty$ Then, how to show that the followings ...
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Using population as weights in regional-level data

I'm analyzing regional-level data (variously at the level of metro, micro, and county levels depending on their economic integration/population agglomeration). I'm using STATA 12 SE. It seems ...
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2answers
154 views

What is the interpretation of the covariance of regression coefficients?

The lm function in R can print out the estimated covariance of regression coefficients. What does this information give us? Can we now interpret the model better or diagnose issues that might be ...
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9 views

Multiple outcome shrinkage and selection

I have been reading Elements of Statistical learning and I could not understand what 3.7 is all about. It talks about RRR (Reduced rank regression), and I can only understand that the premise is about ...
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13 views

Key ways to compare two multivariable regression models?

The question goes "Compare Model 2 and Model 3 and choose a preferred model based on accordance of estimates with prior expectations and which one better addresses the characteristics of the data as ...
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21 views

In a multiple regression model what do the coefficients mean if you're asked to take the log of only dependent variable y

So Say like... $ln(y) = \beta_1+\beta_2x_1+\beta_3x_2+\beta_4x_3$ I only know of the interpretation when they're all (rhs and lhs) are converted in log it tells us elasticity. I dunno about this one. ...
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36 views

Analysis of Multiple Time Series Data with Exogenous Shocks

Real Life ProblemThis one is a tough one and some crowd sourcing seems like a good way to get some feedback. I am trying to determine the effect of Non-Farm Payroll surprises on a subsector of the ...
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23 views

Principal Component Analysis - Multiple Regression [closed]

I have carried out a principal component analysis to reduce the number of items for my likert-scale items. Now I need to do multiple regression analysis with these factors but I have no idea of how I ...
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1answer
46 views

Show $J(I-H) = 0$

This is in multiple linear regression. Given $m, n \in \mathbb{N}$ and matrices $X \in \mathbb{R}^{m \times (n+1)} (m > n + 1), H = X(X'X)^{-1}X' \in \mathbb{R}^{m\times m}$, the hat matrix, $, I = ...
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15 views

reduced rank regression

I am trying to learn Reduced Rank Regression (RRR) from Elements of Statistical Learning. I find the writing and them mathematics a little too prohibitive. Does any of you have a ...
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1answer
19 views

Sign of Estimate (Coefficient) of Interaction Terms

I create a linear regression model with interaction term in the model say: $$y=a_0+a_1x_1+a_2x_2+a_3x_1*x_2+e$$ where $x_1$ is continuous and $x_2$ is binary. Now, I have couple of questions: If ...
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1answer
31 views

Difference in multiple regression with x=factor/coefficients matrix in R

I have got 2 models. The first model uses a factor as the independent variable. The 2nd model uses a matrix with 0/1 coefficients as the independent variable. ...
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1answer
31 views

Multiple regression approach strategies for non-normal dependent variable

I'm hoping to analyze the influence of a set of variables on a continous dependent variable (between 0-1). The independent variables are a mix of both categorical, continuous and discrete features. ...
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17 views

R: Dynamic Regression with ARIMA model using xreg, make use of step function?

This might fit better here than on stackoverflow, I guess. I was trying to build a dynamic regression model with the dynlm package, but it did not work out. After reading this by Hyndman, I now ...
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1answer
18 views

Replace ordinal categories by their mean values for linear regression?

I have a variable that has 8 ordinal categories. These categories are made up by discretizing an interval variable; that is the categories (levels in R) are ...
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10 views

How to find the distribution of Betas of a Single/Multiple Linear Regression model?

How would I go about finding the distribution of betas for a multiple linear regression? That is, a matrix with the same dimensions as the data whose column means are the regression coefficients ...
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92 views

Linear regression with violated assumptions

I am trying to find out the determinants of cognitive function. The outcome variable is the mini–mental state examination which is a 30 point questionnaire response that has score values from 0 to ...
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2answers
87 views

Penalizing the Ordinary Least Squares estimation

In a regression analysis, we aim to find the best relationship between two variables (independent variable denoted $y$ and other dependent variable denoted by $x$, and which are related by: $y = ...
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70 views

Model Selection in Statistics

I have been told not to look at significance level, or not to use forward/backward selection using BIC/AIC for model selection. Let's say, I have 100 survey data with 11 variables and I want to see ...
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10 views

Efficiently processing a large MxNx2 logistic regression, only interactions matter

I'm working with a large 3-way contingency table (roughly $180 \times 40 \times 2$) — both independent variables are categorical and the response is binary. One independent variable (X) ...
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1answer
60 views

Linear regression analysis examples

I am looking for examples where linear regression analysis is used in answering real problems. That is, from formulating real questions as a statistical question, validating assumptions so on to ...
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3answers
62 views

Adding Interaction Terms to Multiple Linear Regression

I am currently running a multiple linear regression, and I am bit confused in regards to how to properly add interaction terms to the model by hand. All of the variables I am using are continuous and ...
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1answer
45 views

glm output in R: analysis without coefficiencts

Generally, coeficients and their p values are focussed upon while assessing the regression output. However, there are other things mentioned. How can we analyze the output of glm without the ...
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411 views

Difference between regression analysis and curve fitting

Can anybody please explain to me the real difference(s) between regression analysis and curve fitting (linear and nonlinear), with an example if possible? It seems that both try to find a ...
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2answers
35 views

Multiple regression/correlation analysis, large dataset:ways, tools [closed]

I've got a large "clean" dataset (800 MB), containing 210k rows and 320 columns. There is 2 discrete string-type columns, others are numeric. One of such numeric columns is selected as depended ...
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2answers
54 views

B is significant correlated with Y, but not a significant predictor of Y in a multiple regression. What can it mean?

I'm working on a paper and I have some problems explaining some of my findings. I have four independent variables, let's call them A,B,C,D. And i have one dependent variable, let's call it Y. In my ...
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1answer
51 views

Best way to determine contribution of a variable to regression model

What is the best way to determine the degree of contribution a variable is making by its addition to a regression model. Suppose I have following regression model for OutNumeric which is a continuous ...
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9answers
2k views

Are we exaggerating importance of model assumption and evaluation in an era when analyses are often carried out by laymen

Bottom line, the more I learn about statistics, the less I trust published papers in my field; I simply believe that researchers are not doing their statistics well enough. I'm a layman, so to ...
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23 views

Why opposite results of explanatory variable in multiple linear regression vs simple linear regression? [duplicate]

I've modelled the oxygen uptake from the sediment community (response variable) using multiple linear regression (based on AIC) with 8 possible explanatory variables. The results give me a model ...
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1answer
37 views

Transform response for hurdle model

I am using a hurdle model (dist=negbin, link = logit) for a dataset with multiple explanatory variables, excessive zeros and overdispersion by both, zeros and count data. The residual plots (pearson ...
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1answer
57 views

Can regression be used with 3 observations and more than 3 independent variables?

I want to regress v1 on o1:o7. I would like to do the same for each of v2:v5 with ...
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19 views

Calculate Confidence Interval of Multiple Regression from Standard Error

From a multiple linear regression model I know the parameter estimates as well as the corresponding standard errors. I also know that the model is based on 96 data points. I'd like to calculate the ...
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22 views

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

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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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 ...