The parameters of a regression model.

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25 views

Interpretation of the coefficient of dummy regression?

I found this for a week, but I still cannot find anything about it. In a regression, Y = a + b * X + controls +e If we add dummy D=1 for group A and 0 for others, it becomes Y = a + b*X + c*D + ...
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28 views

Why is the ratio of $B$ and $e^{B}$ for some variables very large? [on hold]

I want to know how variables affect travel mode for different trip purposes (i.e. leisure trips, work trips and shopping trips) in a specified region. I have 450 respondents in three different ...
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1answer
22 views

Understanding Regression vs. Means/Median Results

I am having a little difficulty understanding my results - could someone help me understand how to interpret, and if my process is sensible? Here is an example of what I am doing I am trying to ...
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1answer
8 views

Interpretation of two indexes Interaction Term

Respected Fellows. I will thankful if someone help me to explain my model results.my model is as follows. Yit=αPFit+βPSit+δ (PF*PS) it+εit Where Y is GDP per capita PF=Political Freedom Index ranges ...
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1answer
58 views

How to capture & present lm model output from R

After running iterations of lm() in R, I am now stuck with which components of the model's output to present and how to present them. I know that the $R^{2}$ value, ...
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1answer
47 views

Compare coefficients from two separate panel regressions in Stata

I am trying to compare the coefficients of two panel data regressions with the same dependent variable. What I am aiming at is the following: ...
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0answers
8 views

What is a “concordance score” for regression coefficients?

I came across this "concordance score" in a set of slides called Penalized regression methods for ranking variables by effect size, with applications to genetic mapping studies, by Ji Zhu: $$ ...
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0answers
15 views

Calculate coefficients in a ordinal logistic regression with R

Following the question about manually fitting logistic regression, can someone provide the same 'manual' way to fit a ordinal logistic regression with ordered categorical response?
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0answers
8 views

Multidimensional Scaling - external scale regression using standardized or unstandardized weights

I am having trouble determining whether to use standardized or raw regression weights when using multiple regression to interpret Multidimensional Scaling plots. Different textbooks seem to advocate ...
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3answers
112 views

How to interpret coefficients of $x$ and $x^2$ in same regression

If I have the below functional form for an OLS regression, how do I interpret the $x$ and $x^2$? I cannot interpret them separately, correct? Do I interpret them as a summation of the two ...
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1answer
62 views

Orthogonalizing predictors for least squares estimation

I know that orthogonalization in LS is to avoid inverting X'X. The idea behind it is to find variables Z that are orthogonal to each other. Although the process to find those is clear to me, I don't ...
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0answers
35 views

Aggregating pooled regression outputs in different years

I performed multiple pooled cross-sectional regressions with the same time-intervals (5years) in different years. I'm wondering now on how to aggregate the different regression outputs. Does it make ...
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0answers
26 views

Compare regression coefficients within one sample

I run two univariate linear regressions within one sample (same subjects, two different conditions). Now I would like to know how to compare the regression coefficients in order to find out whether ...
5
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1answer
80 views

Is there a way to use the covariance matrix to find coefficients for multiple regression?

For simple linear regression, the regression coefficient is calculable directly from the variance-covariance matrix $C$, by $$ C_{d, e}\over C_{e,e} $$ where $d$ is the dependent variable's index, ...
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1answer
22 views

Standardizing single coefficient in multivariate analysis

I have panel data and for the I have a following equation $$ logY = \beta_1 + \beta_2 logX + \beta_3 m logW $$ Problem is with $\beta_3$ coefficient. Since m is outside the log and it is a very ...
0
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1answer
44 views

Linear regression without intercept - sampling variance of coefficient

I am comparing linear regression with and without intercept for the general sampling case. For this, I have $n$ samples of two correlated random variables $X \sim N\left(0,\sigma_X^2\right)$ and $Y ...
2
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2answers
127 views

Do coefficients of logistic regression have a meaning?

I have a binary classification problem from several features. Do the coefficients of a (regularized) logistic regression have an interpretable meaning? I thought they could indicate the size of ...
-1
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1answer
27 views

Why can certain variables in a multiple regression not be included in logarithmic form?

I have a multiple regression equation where log(salary) = b0 + b1(ceotenure). What is the purpose of putting the dependent variable in logarithmic form? How would you interpret the change in y for a ...
2
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1answer
33 views

Coefficient of Determination: For the perimeter and area of a square: Why different?

When calculating the coefficient of determination for a square, why is it that if you use the data set for the side length of as X= (1,2,3,4) and the perimeter as Y=(4,8,12,16) the Coefficient of ...
4
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3answers
156 views

Is it possible in R (or in general) to force regression coefficients to be a certain sign?

I'm working with some real world data and the regression models are yielding some counterintuitive results. Normally I trust the statistics but in reality some of these things can not be true. The ...
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1answer
50 views

Is the statistical significance of a regression meaningful if it has poor out of sample performance?

I want to determine the significance of a particular variable, among many confounders. If I fit a model on the training set and observe a small p value, should I discard the model because it ...
1
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1answer
111 views

Regression coefficients with longitudinal data yields different results in R and SAS

I have a question about SAS and R. For a research, I used a longitudinal data and I initially used SAS (GLIMMIX) and then I analyzed the data with R (...
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0answers
26 views

How to interpret log-log regression coefficients for other than 1 or 10 percent change?

I have read many threads here on how to interpret coefficients in a regression where the predictor and the dependent variable are log-transformed. Most give an answer for a one or ten percent change. ...
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34 views

Coefficients from a Dynamic Panel Data Model of Economic Growth

I am having difficulties with the interpretation of the regression results from estimating a growth regression in a dynamic panel data set-up, estimated using Stata. (I'm using difference GMM and ...
3
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1answer
84 views

Sampling distribution of regression coefficients for normally distributed random variables

Based on $N$ realizations of two random variables $X \sim N(0,\sigma_X^2)$ and $Y \sim N(0, \sigma_Y^2)$ with correlation $\rho$, I conduct a simple linear regression $Y = \beta_0 + X\beta_1 + ...
3
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1answer
58 views

Wald test and Likelihood ratio test, where do the confidence intervals on the regression coefficients come from?

So I'm trying to build my own Wald test and likelihood ratio test code within a machine learning pipeline. I can get the final fitted logistic regression coefficients from liblinear. I'm coding in ...
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0answers
31 views

How to interpret coefficients in the spatial lag and spatial durbin model?

How do I interpret the coefficient for the spatially lagged dependent variable in the spatial lag model or spatial autoregressive model (SAR) (y = αιn + ρWy + Xβ + ε) and how do I interpret the ...
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2answers
93 views

Large coefficients and std. errors

I run a fixed effect model with Stata and because my dependent variable is a large number (max of 12 million and min of - 4 million), I got large coefficients for ...
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2answers
100 views

Should the final R glm include only significant levels of factors

I am running a glm in R on data with quite many predictors (~50), both initially continuous and factors. The response is binary and the volume of the data is OK (~100K rows), in order to model ...
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1answer
36 views

Problem in computing the Variance of Regression Estimator

Referring to the link, my doubt is regarding the actual computation of variance of the forecast. The variance depicted here is $\sigma^2 [1+X^*(X'X)^{-1}(X^*)']$. As mentioned in the link added here, ...
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1answer
77 views

Why is my shared variance negative?

I have two questions regarding standard multiple regression: Why is my shared variance a negative number? Should I only include the positive semipartial correlations when calculating uniquely ...
0
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0answers
29 views

p - values in the summary of lm model in R [duplicate]

I am having a hard time understanding the notion of p-values (looking of layman interpretation in words) that comes up in the model summary of lm models in R. I understand that a layman ...
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0answers
62 views

Changing the variable you omit due to the dummy variable trap

I've got a quick question. The practice exam on which I have the question is linked below and its the first question As you can see, column (3) and (4) on the table are both the same except the dummy ...
2
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1answer
58 views

Positive correlations to dependent variable, but negative coefficients

First of all, sorry for the huge pictures, but I'm in desperate need of some input and help on the results following a study. I'm trying to interpret the results from my study, but I can't quite ...
2
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2answers
52 views

Interaction variable in multiple regressions

I am running regressions of the sort: $$ y_{i}= \alpha + \beta T_{i} + \gamma G_{i} + \delta( T_{i} * G_{i}) + \rho X_{i} + \epsilon_{i} $$ where $T_{i}$ is binary treatment variable, $G_{i}$ is ...
0
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1answer
39 views

Generate predictions from a logistic regression model reflecting the uncertainty of the model

I want to generate predictions from a fitted logistic regression model that reflect the uncertainty of the model (within a classic frequentist framework). To clarify, my objective is not to ...
0
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0answers
30 views

Linear model for this problem? Which regression coefficients should I use?

Suppose a researcher was investigating gender-based wage disparities across 10 different firms. The researcher obtained the following data from these 10 companies employees: 1) years of ...
3
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2answers
261 views

How to interpret p value of regression coefficient which is nearly 0?

When regression coefficient is nearly 0 (in fact in the real model it's exactly 0), what's the meaning of p value (<0.05) of the coefficient? For example, I did a multiple variable regression ...
7
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1answer
212 views

How to interpret coefficents from a polynomial model fit?

I'm trying to create a second order polynomial fit to some data I have. Let's say I plot this fit with ggplot(): ...
3
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1answer
61 views

Interpreting logistic regression coefficients with a regularization term

I understand the coefficients of a logistic equation can be interpreted as odd ratio. If a regularization term is added to control for over-fitting, how does this change the interpretation of the ...
2
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2answers
82 views

continuous vs categorical logistic regression for marks and admission

I have a list of marks scored by students in Science (X, between 0 to 100%) and whether they went to college to or not (Y). High marks in science showed a higher concentration of college admits and ...
0
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1answer
16 views

Interpreting percentage units regressions

I am using a panel of 2249 schools with data from 2002-2008. Some of the schools are single sex schools whilst others are mixed sex. Some background on my regression: Consider the determinants of ...
4
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2answers
100 views

Robust regression - a better understanding

I looked at robust regression for the first time today and I am a bit confused, comparing it to something like ordinary least squares and I am not sure if I am on the right track. I read a few ...
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0answers
57 views

Interpreting coefficients of Regression Model (Mincer Model)

Hi all, I am an undergraduate student who is currently doing an assignment. I am now facing a few problems which are:- 1) Age is usually a positive return to wage, but in my regression output, ...
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3answers
184 views

When to divide data into training & test set in logistic regression?

I am using Logistic Regression in a low event rate situation. Overall universe: 46,000 Events: 420 Conventional logistic regression models divide the data into ...
2
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0answers
63 views

Interpreting regression coefficients of log(y+1) transformed responses

I have measurements $y_1$,...,$y_i$,...,$y_n$ taken from a set of replicates in a factorial designed experiment. In order to use a linear regression I define my response $z_i = log(y_i + 1)$. The ...
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1answer
32 views

Signs on logistic regression betas flip relative to observed - expected counts from chi-squared test

I conduct a chi-squared analysis on some bins and conclude that an association between the bins and an event exists. I then calculate logistic regression coefficients to validate my hypothesis. Also, ...
0
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1answer
83 views

What do the coefficients of the crossproduct of regression mean?

How can I interpret the coefficients of the crossproduct of each of the following codes? What do they mean? How can I deduce that they correspond to our expectation? ...
3
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2answers
128 views

Efficiency of beta estimates with heteroscedasticity

I need something clarified and that is when you have non-constant variance, estimates won't be biased but will be a problem when it comes to the S.E. formulas and efficiency. Therefore OLS estimates ...
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0answers
42 views

How to interpret the coefficients and plot the relationship between IV_i and DV?

I'm using Tobit regression and I'm not sure how to interpret the coefficients. I made sample data with random function in Excel. ...