The parameters of a regression model.

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how to report estimate standard errors of levels from a one-way ANOVA

I'm trying to report means of levels given a model. ...
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1answer
62 views

Multicollinearity with highly safe t-statistics but VIF of 13

If all of my coefficients in my logsitic model have really perfect t-statistics that all show sufficiently high significance but have two coefficients that have high VIF like 13-14 with sample size of ...
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1answer
36 views

How to interpret a significant coefficient of 0?

I just ran a multiple regression with 8 predictor variables. Two of them have a significant coefficient, which is 0.000. How can I interpret this? I find it strange that an effect which basically is ...
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0answers
11 views

Autocorrelation of coefficients for strongly autocorrelated inputs?

In Chapter 5 of "The Elements of Statistical Learning" ("Basis Expansion and Regularization", pg 150"), it is written that Since the input signals have fairly strong positive autocorrelation, ...
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0answers
14 views

Interpreting fixed effects regression coefficients [duplicate]

This probably is a very "beginner kind of question", but I have trouble interpreting the coefficients in my fixed effects regression. The data is on book ratings. Ratings are measured on a scale ...
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1answer
41 views

Hypothesis testing with quotient of regression coefficients

Suppose we have the following multiple logistic regression model $\beta_0 + \beta_1 X_1 + \beta_2 X_2$, where $X_1$ and $X_2$ are binary variables, and $\theta = \beta_1 / \beta_2$. Then I have two ...
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1answer
95 views

Interpretation of coefficients in logistic regression output

I am doing logistic regression in R on a binary dependent variable with only one independent variable. I found the odd ratio as 0.99 for an outcomes. This can be shown in following. Odds ratio is ...
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1answer
7 views

Logit regression and Poisson relative risk estimators

I am running a logistic regression and have determined that Risk Ratios are better to explain my results than odds ratios. I have a dichotomous variable but I have both categorical and continuous ...
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2answers
22 views

Sample size of the levels of a categorical variables

Is there a generally acceptable sample size for the levels of a categorical variable included in a regression analysis? For example, if we have a variable color with 3 levels: 5 reds 140 blues 155 ...
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25 views

How do I generate appropriate group-level coefficients and standard errors for my regression?

I ran a mixed logistic model testing the influence of group (two-level) on a binary outcome, and I want to report the group estimates and their SEs in graph. However, I can think of two ways of doing ...
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14 views

Weights vs Correlation Linear Regression

I am working with Spark 1.5 and I want to predict something. Before in R, I would use the p-values from glm and the importance from randomForest to get an idea of feature selection. So, in Spark (...
3
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1answer
245 views

Regression when response variable is a function

I have a set of data $(X_i,Y_i)$, $i=1,\ldots,n$ where $X$ and $Y$ are supposed to satisfy the following equation $$ y = \beta_0(1+x^2)^{\beta_1},\quad x>0, \quad\quad (1) $$ I am interested in ...
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15 views

To fit a count proces

In R I have data where head(data) gives ...
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1answer
25 views

Measuring Variable Effect in Random Forest Regressor

Is there a way to measure the effect individual predictors have on an outcome for a Random Forest Regressor? If there's not something similar to a regression coefficient, is there a way to utilize ...
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23 views

Interpret coefficients from logit/probit models with inverse definition of dependent or independent variable

I have a couple of empirical studies examining the determinants of credit ratings. Here, the dependent variable is a binary variable indicating whether a firm has a credit rating or not ($rating$). ...
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2answers
36 views

Linear regression on large sparse feature set

I have a sparse feature matrix with 50K observations and 150K features. All features are binary. On this I have to run a linear regression. I want just a decent fit. Data: Let us consider training ...
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1answer
37 views

Manually compute the regression coefficients of a multiple regression model with numerical and categorical variables

I am going to explain my question using a reproducibile toy example. I would like to regress a numerical variable using a multiple regression model with either numerical and categorical variables. I ...
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1answer
33 views

How to predict from glm created with average values?

I want to predict count data (example: people visiting a beach) based on some predictors (example: temperature, cloudiness). I have created a generalized linear model (with Poisson distribution and ...
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2answers
67 views

Regression: What is the utility of R squared compared to RMSE?

Suppose I'm doing regression with training, validation, and test sets. I can find RMSE and R squared (R^2, the coefficient of determination) from the output of my software (such as R's lm() function). ...
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1answer
32 views

Heteroskedasticity Question

I have a model that's affected by Heteroskedasticity: bptest(m1) studentized Breusch-Pagan test data: m1 BP = 65.055, ...
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1answer
30 views

Using logistic regression to estimate whether probability of an outcome is greater than chance (and by how much)?

I have an outcome variable that is subjects' correct or incorrect responses to a single question asked at two time points (before and after the experiment). I want to know if subjects were better than ...
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1answer
26 views

Really weird results for a logistic model - is it due to high frequency of one value on response variable?

I am trying to test whether experimental group (a vs b) influences the probability of some binary outcome, but the model results are strange. The code I'm using: ...
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2answers
56 views

Regression Interpretation conundrum

I am running an OLS regression of the form $$\log\left(Y\right)=x_0 + \left(\frac{x_1}{Y}\right)\beta_1+\log (x_2)\beta_2 + \epsilon$$ I have one covariate as $\left(\frac{x_1}{Y}\right)$ which is a ...
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22 views

Coefficient of correlation from averaged and not averaged data

I want to understand why I get two different results for $r^2$ from the data I post. I use the linest function in Excel. One more noob question about weighted ...
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10 views

Compare the coefficients of two independent variables within a model, representing 2 diff independent variables are statistically different?

I'm trying to show that two coefficients within a model are statistically different from each other. These variables measure two similar, but different variables, price increase and price decrease. ...
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1answer
46 views

VAR model interpretation: Coef vs Impulse response functions

In courses such as time series analysis, we learned that the relationships derived from impulse response functions or Granger causalties are more interesting than the estimation output. I was ...
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1answer
63 views

Regression specification consequences

Suppose a true model is $Y_i = βX_i +u_i$ , where $β$ is parameter and $u$ is the random error, and $i$ denotes the number of observations. But instead of fitting this regression through the origin, ...
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11 views

Does the variance inflation factor make sense for regularized regression?

I have a logistic regression model fit using L1 regularization. There are two variables that entered the model that have a correlation of over 0.90. The VIF for these variables are each about 60 which ...
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1answer
16 views

Interpret/evaluate effect of including variables in regression analysis

I am running an asset pricing test (Fama MacBeth); regressing one month ahead excess stock returns on market beta and some firm-level variables (e.g. MAX and EISKEW shown below). My object is to ...
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1answer
23 views

Share of variance explained by individual predictor [duplicate]

I am interested in how to calculate portion of explained variance of each individual independend variable in regression equation. So regression model is $y=b_{0}+b_{1}x_{1}+...b_{n}x_{k}+\epsilon$ ...
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2answers
49 views

How to interpret Quadratic Terms

I'm answering a practice exam questions, and having trouble with one on quadratic terms. Could someone give me a quick summery of 1) why they are sometimes included? 2) How to interpret them? In ...
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17 views

interpretation of coefficients in regression with categorical, continuous predictors

I am having trouble with interpretation of regression coefficients when more than one categorical variable is included. Also, I am not clear on how including interaction terms changes the coefficient ...
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0answers
13 views

Do these two variables make sense?

I am running a fixed effects regression on wages and gambling to see what impact gambling has on earnings. The dataset I have been given has two interesting variables - poverty and unemployment rate. ...
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24 views

Categorical variable intercept in generalized linear model

I am running Generalized Linear Model and I have one continuous dependent variable, two categorical fixed factors and 22 continuous independent variables as covariates. When I run the model, I get ...
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12 views

SPSS: Interpretation of coefficients - OLS

I could need some help interpreting my findings. I've been conducting a linear OLS regression with the following output: I'm trying to discover what the influences are from an acquisition on the ...
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36 views

Covariance Between $\hat{\beta_0}$ and $\hat{\beta_1}$ [duplicate]

Our model is $Y=\beta_0+\beta_1X+U$. We know that $\hat{\beta_0} = \beta_0 + \sum\limits_{n=1}^N c_nu_n$ and $\hat{\beta_1} = \beta_1 + \sum\limits_{n=1}^N k_nu_n$, where $$k_n = \frac{(x_n-\bar{X})}{...
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0answers
26 views

Interpreting results from lasso regression?

I have a time series data set with about 2million observations and 31 variables, which I break to a few thousand using threshold value for my dependent variable. I am using lasso regression in R to ...
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41 views

Using repeated measures change/trend as a predictor variable

I have repeated measures of happiness for a sample of participants, and a single measure of satisfaction for each of the ...
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16 views

How do I calculate the Confidence intervall for the regression coefficient? [duplicate]

Hello! I need to calculate the 95 percent CI for the regression coefficients (coef). Is it possible to simply do this by taking the values plus or minus 1.96 times its standard error (se(coef))?
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22 views

Forward selection, using adjusted R square or t statistics?

When it comes to select variable in multiple regression model using forward selection, should we add variables in the models according to its adjusted R square or t statistics/Sig?
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1answer
27 views

Interpretation of Regression coefficient

I have a five-variable regression equation, and I added any constant (fixed value, say 100) to all the observations of variable $A$, another (or same) fixed value in variable $B$, while the other ...
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1answer
48 views

Why doesn't standardization work in the linear regression?

I have a matrix containing the attributes of the item and their corresponding rating. All of the attributes are in the range of (0,1) and the rating is in [1,5]. I transform the range of rating to (0,...
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3answers
58 views

How to interpret my coefficients?

I have the following model: $$ Gini_{it} = \alpha_i + \beta_1\ln(BNP_{it}) + \beta_2trade_{it} + \epsilon_{it}, $$ where $Gini_{it}$ is the Gini-index from 0 to 100, $\ln(BNP_{it})$ is $\ln$ of the ...
3
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0answers
54 views

How to treat categorical predictors in LASSO

I am running a LASSO that has some categorical variable predictors and some continuous ones. I have a question about the categorical variables. The first step I understand is to break each of them ...
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0answers
29 views

how interpret coefficient of a binary variable (coded as 1 and 2 in R) in a logistic regression model

I have a logistic regression model where Pstatus (a binary variable is coded as 1,2 (1 being apart, 2 being together in R see code below) has a coefficient of 0.8. I am wondering how I should ...
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0answers
21 views

non-trivial coefficients in an OLS regression

I have a problem explaining how and why the coefficient on my regressions is changing signs. I have a continuous outcome variable Y which is a linear combination of two continuous variables y1 and y2....
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1answer
37 views

What is the relationship between regression analysis, LASSO, and coordinate descent?

I'm a complete newbie and trying to understand what exactly LASSO is, how coordinate descent is used with LASSO, and how all of that factors into regression analysis. I'm totally confused about the ...
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0answers
15 views

Differing regression coefficients in the literature for Okuns Law

I'm currently writing up my applied econometrics project on Okun's Law, and it is important for me to give some historical context of Okun's original regression results. My problem however, is that ...
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30 views

Interpretation of coefficients

I know that probably a lot of people already asked about the interpretation of coefficients especially in log-linear models. Unfortunately, I was not able to find an answer to my specific question: I ...
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0answers
14 views

Cancelling roots in ARMA(1,1) with external regressors

I am trying to find out what cancelling roots would imply for the estimators of my external regressors in my ARMA(1,1) model. Unfortunately however I'm stuck in my final step since I'm insecure about ...