The parameters of a regression model.

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18 views

Why coefficient changes sign between linear and logistic regression?

My dependent variable $Y$ is continuous a linear model is estimated: \begin{equation} Y = \beta_{0} + \beta_{1} X + \epsilon . \end{equation} I transform the dependent variable into $Z = 1 \text{ if ...
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6 views

Different coefficient for same feature in different fits

I wonder how to generate such data, so that in single variable regression feature coefficient would be positive, and in multiple regression would be negative. So I read several related questions on ...
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11 views

Scale a coefficient in a regression

Can I multiple a coefficient by 100? For example, Y= b0 + b1Distance Distance is in metres If I increase distance by 1 metre, Y increases by b1. Multiple b1 by 100, my interpretation is: If I ...
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0answers
15 views

Constrained Least Squares in R [closed]

Alright so I am trying to setup a constrained least squares problem (which is quite simple) in R but I am having issues and thought people here might be able to help. Here is the problem: $min_P ...
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1answer
15 views

Regression with multiple dummy variables and dummy interactions

I have a model measuring Click through rates using 3 dummy variables. Placement location (PL1 vs. PL2) Ad type (Text vs. RM) Device type (Mob vs. Desk) Additionally I want to measure the ...
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3answers
169 views

Interpretation of the variance of a slope

If I have a simple regression model: $$Y = \beta_1 + \beta_2(\text{income}) + \varepsilon$$ I can calculate the $\text{Var}(\hat{\beta_2})$ quite easily with a formula. However, what is the ...
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12 views

interpreting the “effect size” of standardized regression coefficient

Is there a reference I could use to say how large the standardized regression coefficient is? For example, a 0.25 SD change would be "small" effects? Thanks!
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0answers
25 views

Regression method if dependent variable is the absolute value of a continous variable [duplicate]

Suppose we have a dependent variable $Y$ that has normal distribution with a mean of $0$. If I run a regression model using the absolute value of $Y$, $|Y|$, i.e. $|Y| = b_1 + b_2 X + u$, my dependent ...
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1answer
30 views

p-values of the coefficients or AIC for model selection in multiple regression

I´ve got two models from a multiple linear regression (A and B, see below) and don´t know which to select. I want to predict a value called AW as good as possible, so I´d like to have the highest r². ...
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15 views

Converting nomogram to logistic regression coefficients and intercept

My plan is to use a published nomogram to predict events in my data set. The question is, how do I derive logistic coefficients and intercept from the nomogram?
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0answers
23 views

Dropping the non-significant parameters in multiple regression

Given the standard multiple linear regression model $$Y=X\beta+\epsilon\sim N(X\beta,\; \sigma^2I)$$ One derives the distribution for the estimated parameters $$\hat{\beta}\sim N(\beta,\; ...
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9 views

Calculating elasticities from spatialprobit Bayesian coefficients

I have run a model in R using the spatialprobit package and would like to calculate elasticities with respect to some of my coefficients of interest. I am a bit ...
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11 views

Interpretation of orthonormal contrasts in ANOVA/regression

Is there an intuitive substantive or geometric interpretation of regression coefficients associated with categorical predictor variables coded with orthonormal codes? For a simple example, say we are ...
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0answers
26 views

How to determine if a (binary) variable has a statistically significant effect on a response variable?

To be more specific, assume the following scenario: A customer advertising for a job on your site wants to know whether buying an extra ad-product or not will increase the number of applicants. You ...
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1answer
53 views

Interpreting the change in two logs in a regression

If I have a log-log regression, like: $\ln(\text {Price}) = b_0 + b_1 \times (\Delta \ln (\text{emp}))$ Where $\Delta(\ln (\text{emp})) = \ln(\text{employment growth_year2}) - \ln(\text{employment ...
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1answer
33 views

logistic regression - Compare coefficients between categorical and numeric variables

I have category (season, Time of day...) and numeric variables (temperature, humidity). I want to compare the coefficient to find out what variable has more impact on the dependent variable. But the ...
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1answer
35 views

Adding new variables makes regression coefficients individually insignificant [duplicate]

I have a multiple regression where all my coefficients are significant. When I add new variables my initial variables become insignificant. Furthermore, my new variables (that in a simple regression ...
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1answer
18 views

lower order term has positive prediction in simple regression but negative prediction in quadratic regression

I am using SPSS to conduct a quadratic regression. The IV is positively and significantly related to the DV in a simple linear model. However, after the squared IV is put in the model, the lower order ...
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2answers
312 views

Regression to the mean in “Thinking, Fast and Slow”

In Thinking, Fast and Slow, Daniel Kahneman poses the following hypothetical question: (P. 186) Julie is currently a senior in a state university. She read fluently when she was four years old. ...
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37 views

Linear regression using variable as both regressor and weight

I've come across a linear regression model aiming to estimate the relationship between $X$ (population) and $Y$ (expenditure). The approach taken isn't what I'd assume, which would be to simply ...
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13 views

Negative binomial regression - compare size of effect

I am analyzing the influence of grades and work experience (measured in month) on the number of invitations to an job interview. sice number of invitations is a count variable i am running a negative ...
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1answer
25 views

Standard error for the sum of regression coefficients when the covariance is negative

I have a question about appropriately calculation the standard error for the sum of two coefficients in a linear regression model. My question is similar to this and this, but I can't seem to solve ...
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0answers
11 views

Coefficient - different specifications - significant vs not significant - interpretation [duplicate]

for my bachelor thesis I am analyzing the influence of grades (G) and work experience (WE) on the probability to get a job (J). I have three specifications (simplyfied they look like this): J = ...
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1answer
26 views

Significant correlation but in regression analysis Beta is insignificant. How come? [duplicate]

I have 3 IV's and they are significantly correlated with DV, but when I run regression one of the IV's Beta value turns out to be insignificant. What might be the reason of this?
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28 views

log transformation with zero value

I am studying the impact of dependence on natural resources on the economic growth of provinces. The resource variable is measured as % share of mining in GDP or per capita value of mining. In either ...
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0answers
29 views

Comparing multiple regression coefficients of two populations

I have two populations with three variables v1, v2 & v3 each. The variables are the same in both the populations and I have developed multiple linear regression models for the two populations with ...
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16 views

Main effects of multi-level variables in a regression versus ANOVA

I have a design where I want to look at the interactions between a 2-level categorical and a 3-level categorical variable, as well as the main effects of each. In an ANOVA scheme, I would be able to ...
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30 views

A question on Multinomial Regression

Assume an experiment with 6 outcomes, dubbed A, B, C, D and E. For outcome A, there are Na subject, for B there are Nb subject and so on. Now assume we fit a multinomial regression using a Bayesian ...
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2answers
77 views

How to interpret logistic regression coefficient

How do I interpret a regression coefficient in a logistic regression with two predictors? $\hat{L} = -14.27+3.32(3)+0.88(7)$ My understanding is to take the anti-log of the coefficient, like ...
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16 views

Logistics regression categorical predictor significance and penalization

I have the following scenario: Have multiple logistic regression models predicting the same outcome Each of these models were built off their own sample in the entire data set (i.e. different ...
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3answers
97 views

How to read the Interaction effect in multiple linear regression with continuous regressors?

If the interaction happens between a continuous and a discrete variable it is (if I'm not mistaken) relatively straightforward. ...
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1answer
66 views

How can I test the significance of a non-linear function of regression coefficients in R?

Let's say I have an equation $Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + ... + \beta_k X_k $, where $\beta_i$ represents an estimated coefficient and $X_i$ represent independent variables. How can I ...
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0answers
24 views

Visreg-package in R / interpretation of the output of glm

I thought I've understood the output of the logistic regression in R (also I learned a lot through stackexchange), but somehow my vizualization tells me something different. The output of the glm in R ...
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13 views

When does fitting via intermediate submodels matter?

Suppose you have two features A and B and plenty of data. What happens when, instead of fitting a model to A and B simultaneously, you first fit a model to A and then fit a second model to the output ...
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28 views

Violation of 1) normality of error terms, 2) heteroscedasticity and 3) spatially correlated error terms.Alternatives?

I am using linear (Ordinary Least Squares) regression to estimate the coefficients and model fitness for vegetation in an ecological study. However, after model fit, tests showed that the linear ...
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0answers
14 views

True signs of coefficient of variables in multiple regression [duplicate]

I do multiple regression (y ~ x1 + x2 + x3) where independent variables come up with positive and negative coefficients. However when i do the simple regression for each independent variable ...
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0answers
12 views

Predicting variable value by simple correlation and standardized regression coefficient

I am trying to predict the value of transformational leadership by known personality trait values from this article: http://www.timothy-judge.com/Judge%20%26%20Bono%20JAP%202000.pdf It looks like ...
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1answer
49 views

How are the coefficients computed in multivariable logistic regression in R statistics?

I'm going crazy, because I can't find a simple description how the coefficients are calculated in R statistics in the multivariable logistic regression (and I'm not a mathematician). Are they ...
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24 views

Interpreting multiple linear regression with continious moderating variables

First some background information: I am doing a study that examines whether number of patents and trademarks (2 independent variables) influence gross margin (dependent variable). Now I speculate that ...
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19 views

Difference-in-differences analysis with non-significant coefficients but significant F-test

I have performed a difference-in-differences analysis but I'm not sure how to interpret the results. I have a regression on the form: ...
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1answer
46 views

Understanding the formula of dfbetas

I'm referring to the formula used in the answer here. The numerator in the formula for dfbetas is straight forward: the difference between the value of the coefficient for a regression model that ...
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1answer
152 views

Conjoint Analysis - Incorporating individual-specific intercept

We are new here, and have recently gotten a question that we have very much been struggling to answer. It is concerning a question regarding a conjoint analysis in which we have to incorporate an ...
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38 views

Binary Logistic regression results

Is it correct to find that an explanatory variable was found to be statistically significant with the chi-square test but insignificant with the logistic regression analysis model?
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2answers
103 views

Closed form solution for slope coefficients in bivariate regression

In a univariate regression, $Y=a+bX+e$, the solution for slope b is given by $COV(X,Y)/VAR(X)$. Is there a similar expression for a bivariate regression $Y=a+bX+cZ+e$. What is the closed form ...
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30 views

Curve fitting - accounting for variability caused by different initial conditions (Matlab)

I'd like to fit a Gaussian model (composed of 1 to 5 Gaussians) to 55 data points, and then repeat this process for >1000 more data sets, each having 55 data points. I'm interested in the fitted ...
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1answer
24 views

In count data models with dummies, what exactly means “on average”?

There are some questions + answers out here that explain how to interpret coefficients from count data regressions (e.g. negative binomial), both as incidence rate ratios or marginal effects. Bottom ...
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1answer
27 views

Regression Through Origin (RTO) with 2 variables?

I am seeking a parametric expression of a RTO (regression through the origin) for a 2-variable system, that is, $Y = b_1 X_1 + b_2 X_2$. The OLS (ordinary least square) expression is commonly known, ...
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7 views

Efficient ways to partition rows of augmented design matrix $[X|y]$ into subsets with similar regression results?

Imagine I have $n$ observations on a regression model; are there any reasonably efficient methods for partitioning that into two (or more) roughly equally sized groups which almost reproduce the ...
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25 views

The variance of a biased estimator

This builds on an an earlier question from Math SE. I am just starting to learn about the simple regression model. In particular, I am trying to understand what happens to $\hat{\beta_1}$ when the ...
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30 views

Examining PLS Results in R

I would like to know how I can go about examining the results of a partial least squares regression. Specifically, I am interested to know what the coefficient is for each component, and what the ...