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

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Variable selection with hand on example in R

I am looking for most suitable way to perform analysis (with statistical evaluation) where the aim is to find (select) a suit of continuous (collinear) variables that best describe other continuous ...
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11 views

eliminating outliers in MARS regression

I using the regression method called MARS, in R is it called earth and is located in the ...
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1answer
14 views

Best method for predicting a numeric response from multiple proportional predictors?

I have some data where I want to predict a continuous, approximately normally distributed response/dependent variable with three predictors which are all proportions (i.e. 0-1). The three proportions ...
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20 views

How to apply non-parametric methods to panel data? “The Elite Illusion: Achievment Effects at Boston and New York Exam Schools”

I'm studying this paper The Elite Illusion: Achievment Effects at Boston and New York Exam Schools. There the authors use a fuzzy regression discontinuity design experiment to assess the ATE of going ...
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22 views

Intuitive treatment of math for F-test in multiple regression

Can anyone point to an online explanation of why the F-test works for multiple regression? I found tons online, but I am looking for the sometimes contradictory requirement of the explanation being ...
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1answer
19 views

What is the regression test equivalent to a repeated measures (factorial) ANOVA?

As in the title, I'm trying to figure out what would be the regression test equivalent to a repeated measures one- and two-way ANOVAs? So, in the case of having different dichotomous IVs and two ...
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18 views

Insignificant slope coefficients

While calculating the value of the dependent variable why do we take into account even the variable whose slope coefficients were not significantly different than zero? Is my understanding correct ...
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11 views

Temporal Data set

I have a fishery data set of fourteen years in a tropical region. This kind of information is quite rare in ecological studies.The data were monthly collected and the set has 2 annual gaps and a gap ...
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2answers
58 views

Regression analysis low R2 value - Result interpretation

When I run linear regression on my test data I get the following report: You can find the test data in here. The graph of actual vs predicted looks like: I would like to know if this is fairly a ...
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32 views

Customer life time value prediciton [on hold]

I'm interested in predicting lifetime value for new and existing customers. Which data mining techniques are common for this? I've thought of using Linear regression or a multiple logistic ...
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1answer
58 views

Why is backward elimination justified when doing multiple regression?

Does it not result in over-fitting? Would my results be more reliable if I added a jack-knife or bootstrap procedure as a part of the analysis?
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16 views

Can we perform logistic regression on cross section data?

Can we perform logistic regression on cross section data? My friend says that logistic regression only works for panel data.
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17 views

Determining relative contribution of independent variables in predicting dependent variables in regresssion

I am running a multiple regression in which the dependent variable and both predictor variables are continuous, numeric and positive. lm(DV ~ PV1 + PV2, mydata) ...
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23 views

Modelling combined linear and quadratic age effects

I am running a GLM (Type III) with several predictors, including age and age squared as predictors. I am interested in knowing the combined effect size and p-value of age+age^2, since neither is ...
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41 views

Can I combine 10 variables into one variable before performing logistic regression on 18 total variables?

Univariate analysis of 18 variables possibly associated with spine infection--can all the historical variables be combined into one variable, then logistic regression be performed?
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22 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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33 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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17 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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1answer
40 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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12 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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41 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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1answer
71 views

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

I am interested in testing the following hypothesis: \begin{align} \newcommand{\var}{\rm Var} \newcommand{\cov}{\rm Cov} \newcommand{\se}{\rm se} H_0\!:\ B_2 + B_3 &= 1 \\ H_1\!:\ B_2 + B_3 ...
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32 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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28 views

I'm in trouble while I'm estimating regression in R [closed]

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
22 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
61 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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20 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

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
33 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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14 views

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
157 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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15 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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22 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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38 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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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
32 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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0answers
18 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
19 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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0answers
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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1answer
99 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
101 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 = ...
3
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2answers
72 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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67 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 ...