Questions tagged [regression-coefficients]
The parameters of a regression model. Most commonly, the values by which the independent variables will be multiplied to get the predicted value of the dependent variable.
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Relationship between different types of correlation coefficients
Let,
$r_{1(2.34...p)}$ = Correlation between $x_1$ and $x_{2.34...p}$. The latter being the residuals after regressing $x_2$ on $x_3 , x_4 ....x_p$.
$r_{1.234..p}$ = Multiple correlation coefficient ...
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1answer
21 views
Comparing slopes between different regression lines in the same sample
I have two models:
mod1 <- glm(y ~ A + CONTROL1 + CONTROL2, data = dat,family=binomial(link="logit"))
...
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1answer
54 views
How are p-values computed from t-values when doing regressions?
I'm performing a regression analysis using the statsmodels module in Python. The regression gives both t-values and p-values for each coefficient, but I'd like to understand exactly which test is ...
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1answer
25 views
Multiple Regression to suggest the number of stores needed per town/location
Is it possible to apply a multivariate regression to identify the number of company stores or branches required in a town or location?
the dependent variable is the number of stores
the independent ...
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0answers
41 views
Generating Target Data According to Regression Coefficients [closed]
I am in the process of creating data for a linear regression problem set for a class that I am teaching. I am interested in manually setting the coefficients for my linear model in such a way as to ...
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30 views
How should I interpret a quadratic term in a logistic regression?
My understanding of a quadratic term in a regular regression is that it can be thought of as the rate of change, where the slope in the original feature x is adjusted by the amount in the quadratic ...
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26 views
Plot confidence interval of average polynomial fit from coefficients
I am studying the propagation of a wave and to do that I want to follow the position of my maxima over time. In order to do that I thought to fit a polynomial on the data of each replicate, then save ...
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26 views
dummy variables and interaction terms: when the number of observations matters
Some authors conducted a univariate cross-section regression using 26 observations:
$$Y_i = a + b \cdot X_i + e_i$$
Some others did the same regression and added another one where $X$ is split ...
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15 views
Summing linear and quadratic effects of a variable in polynomial models?
I have a regression model that includes two predictor variables, but each is represented by a linear and quadratic term.
$$y \sim a + b_1x + b_2x^2 + b_3y + b_4y^2$$
All the terms are significant, ...
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1answer
20 views
Difference between two dependent variable with two covariates
I have two groups (A & B).
First step
In each group, I am trying to find the relationships between dependent variable (flow) and 2 covariates (total rain and preflow).
Should I:
Do a multiple ...
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1answer
25 views
Meaning of $r^2n$ for a large dataset
I have a large astronomical dataset, showing the OLS regression value $r$ between two continuous variables, and the number of observations $n$. My research supervisor has told me to include the value ...
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1answer
34 views
Standard Error of simple linear regression coefficients
dear members,
I have been troubling myself with this question for the past few days but have not found any answers on the Internet:
For a simple linear regression, you get the estimates ...
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19 views
Logistic regression coefficients
I am doing logistic regression with 3 attributes. According to my data set I am expecting all coefficients to be positive. But it gives me both positive and negative coefficients. Is it possible to ...
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1answer
15 views
Standard error of coefficient estimates for model II regression
I'm working with time series data that has error in both the dependent and independent variables, so I'm analyzing each half hour of data with model II linear regression, specifically geometric mean ...
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0answers
16 views
Can I split the intercept in a glm into the contributions by two dummy variables?
I have a multivariate glm, with several response variables (in this case, as species matrix). As an example, the coefficients for one response variable (one species) are:
...
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0answers
24 views
Ratio of Unbiased Estimators
If there is a linear regression model as follows:
$$y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3 + u$$
and we want to estimate the ratio of the slope coefficients:
$$\theta = \frac{\beta_1}{\...
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0answers
33 views
Is it valid to solve an equation for multiple coefficients, then average them to obtain overall effect?
I have a regression model, the setup for which is as follows: I am using manyglm, a multivariate general linear model approach to determine the difference in several invertebrate species between two ...
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Interpreting coefficient estimate of square rooted explanatory variable in multiple regression
I have a made-up linear model, and am interpreting the coefficient estimates. One of my prediction variables is square rooted, and I am struggling to work out an accessible interpretation.
My ...
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1answer
42 views
Interpreting intercept in multivariate linear regression when excluding some factors
This question may have already been asked, but I cannot find anything quite like what I am asking.
Background and model
I am using manyglm with a negative binomial distribution (from the package ...
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24 views
OLS regression coefficient - increase vs. decrease
I am running an OLS regression with a few independent variables. For a particular variable of interest, I would like to find out the coefficients separately for an increase in the independent variable ...
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1answer
36 views
Is there a relationship between number of covariates and sample size in logistic regression? [duplicate]
Is there some definite relationship between number of covariates and the sample size in logistic regression? (e.g. larger the number of covariates, larger the sample size needed, etc.)
Thank you,
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1answer
17 views
interpret the intercept and coefficients of normalized input variables in regression model
My target variable of regression model is a rate between 0 - 1. When using the original input variables, it is easy to interpret the intercept, say 0.8, and coefficients of each input variable, say 0....
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1answer
73 views
statsmodels logistic regression with binned variables has large coefficients and standard error for some variables
I'm fitting a logistic regression (binary) using Python's statsmodels, and here's a snippet of summary from the model:
I have noticed that the large coefficients ...
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1answer
41 views
Modelling a percentge as a dependent variable
I have a dataset containing 4 variables:
Y - the dependent variable. This is a percentage of students in a school that choose to take an external exam. The values vary from 20% to 70%.
X - the ...
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50 views
How can I interpret relative and absolute income of both partners in one regression?
Suppose you want to examine the effect of income on the amount of housework for women. Does it make sense to include both relative income (compared to partners income) and absolute income of BOTH ...
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18 views
Random coefficients logit estimation with Hierarchical Bayes in R
I am trying to estimate a Random Coefficients Logit model using the RSGHB R package. Thought, I came across with 2 main issues:
Why the ...
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0answers
33 views
How do you interpret “explained” coefficients in Blinder-Oaxaca decomposition with considerable negative values?
For illustrative purposes, consider the example given on p. 473 of Jann (2008). However, instead of the difference and coefficients noted, let's assume the difference and coefficients were the ...
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1answer
80 views
regression coefficient in the poisson model [closed]
When we are dealing with count variables we are told not to log transform our data but to instead use a poisson regression.
I was wondering.. when it comes Poisson regression, the common formulae is :...
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4answers
324 views
Is the average of betas from Y ~ X and X ~ Y valid?
I am interested in the relationship between two time series variables: $Y$ and $X$. The two variables are related to each other, and it's not clear from theory which one causes the other.
Given ...
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0answers
14 views
Out-of-sample predictive checks for Bayesian TVP models
Comparatively new to Bayesian econometrics so apologies if this is a silly question.
I am running a time-varying parameter regression where the parameters are estimated as in Primiceri (2005). My ...
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0answers
7 views
Main effect changes after adding interaction term [duplicate]
I have two models:
Model 1:
Y = b0 + b1X1 + b2X2 + b3X3
Model 2:
Y = b0 + b1X1 + b2X2 + b3X3 + b4X2X3
all coefficients are significant in both models but b2 changes from positive in "model 1" ...
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1answer
100 views
glm returns NA as coefficient for logistic regression
I am fitting a logistic regression for the response variable- 0 or 1. There are 15 explanatory variables- 10 are continuous and 5 are categorical with 3 levels each. I checked collinearity among the ...
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2answers
46 views
Regarding glm.nb() and my parameter
I have been doing a negative binomial regression model using the following code
My my estimate here comes out as 3.48. (the exponential of the intercept).
The data was taken randomly (with set seed) ...
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26 views
Biased coefficient estimates when using logistic regression with unbalanced classes?
I'm aware of the fact that probability estimates can be biased in logistic regression when dealing with unbalanced classes. When looking at the log-likelihood function ...
$$
ℓ(β)= ∑ 𝑦_𝑖 *\log 𝑝(𝑥...
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1answer
21 views
Calculating regression coefficients from the covariance matrix involving categorical variables
Prelude
Let us start by generating some data:
...
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0answers
33 views
Functional Forms of Independent Variables
If our objective is to ascertain the relationship (specifically, sign and significance of Beta coefficient) between independent variables and dependent variable in an OLS regression (cross sectional ...
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1answer
70 views
Short Run vs Long Run Effect in Dynamic Panel Regressions
This video differentiates between short run and long run effects of an independent variable in dynamic panel regression (from 19:25 to 20:50). Firstly, I would like to know when and why do we ...
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1answer
35 views
Calculating 95% confidence intervals for GLMM additive coefficient - count data estimates
I am running a GLMM on some data where the response is count data, using the glmmADMD package in R. I would like to plot the results giving estimates for the response variable with certain explanatory ...
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68 views
Simultaneous estimation of a group of linear model (regression) parameters
Suppose $y=ax+z$ where $x, y, z$ are random variables with range in $\mathbf R$, $\mathbf E[x]=\mathbf E[z|x]=0$ and $a$ is a constant. Note the distribution of $z$ conditioned on $x$ depends on $x$. ...
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How to estimate error of regression parameters from data with errors
I'm a physics student and in school we often measure some data (like voltage and current) and then use regression to determine an unknown quantity (ie. resistance in this case). My problem is that I ...
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2answers
105 views
Interpretation of β in case of log-lin model for relationship between X and Y
In many papers, the dependent variable is transformed by taking natural log. For instance, consider the following model:
$$\newcommand{\Cov}{{\rm Cov}}
\ln(\text{Y}) = \alpha + \beta\, X_1 + \epsilon
...
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1answer
20 views
How can we check whether coefficeints of a multivariable regression models are zero(null hypothesis) without creating full and restricted model?
I want to test whether a variable Y has an influence over other variable Y. For this I have established a null hypothesis that the coefficients of Y in the regression model are zero. Can I test this ...
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2answers
48 views
Interpret reuslts of PLS regression coefficients
I have performed PLS regression using sklearn library (python 2.7) over three types of soil (PLS model per soil type) and I plotted the regression coefficients, but ...
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0answers
28 views
Interpreting the coefficient of the interaction between 2 (binary) endogenous variables
I have the following outcome (second-stage) equation:
$$y = \beta_0 + \beta_1w + \beta_2x + \beta_3w x + \cdots$$
$y$, $w$ and $x$ are all binary. Both $w$ and $x$ are endogenous, but I have an ...
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1answer
32 views
Odds Ratio but for linear regression!
I have a linear regression model that predicts lifetime customer value. It has coefficients that tell me things like, if the customer is a VIP then they have +$100 value.
However if i know that these ...
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0answers
19 views
Mean Square of Regression Error for categorical variables while computing F statistic
Give the annova table in the image below:
I need to calculate the F statistic for the null hypothesis: b2 = b3 = 0 .
b2 is cofficient of cylinder and b3 is the coefficient of doors. The formula used ...
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1answer
48 views
How do I interpret a negative binomial regression with categorical predictor?
I am trying to interpret R output for a negative binomial regression.
Below is my output. I'm trying to infer how much my predictor (socfrend_bin) affects my ...
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58 views
How to plot predicted values for fixed and/or interaction effects? (different results of predict() function and effect() (from effects package))
I've applied a linear mixed model to my data:
...
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0answers
31 views
Multiple Regression Effect Size, Significance, and Cohens f^2
I have a multiple regression with a continuous dependent variable, 1 continuous independent variable, and a handful of binary independent variables. The R summary is pasted below:
...
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1answer
96 views
Controlling for a variable in OLS - Stratification and Reaggregation. Simple Example
In his engrossing book "Naked Statistics" Charles Wheelan begins to explain how controlling for variables works by stratifying the sample. However, he stops short of explaining the reaggregation, ...
