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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Does High Information Value (IV) for a variable implies high coefficient in logistic regression?
I'm performing a Logistic regression for a binary classification task.
As a preprocessing technique I use a transformation with WOE and Information value(IV), but I found something counterintuitive ...
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17 views
Linear Regression with Changes
Consider two variables with levels over two time periods $\{y^i_t,x^i_t\},\{y^i_{t+1},x^i_{t+1}\}$.
For example, it could be profit and cost data of various firms over two quarters.
Suppose I take ...
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41 views
Test significance of weighted average of multiple regression coefficients from different models
I have 3000 independent time series samples (customers) where I fit a dynamic regression model with ARIMA errors to each sample and estimate regression coefficient of interest (intervention), $B_1{_i}$...
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9 views
Spatial Lag or spatial Error Model? Deciding by using the Lagrange multiplier diagnostics
Honestly, my knowledge of geostatistics is limited. My assumptions are as follows: If I want to choose between a Spatial Lag Model (SLM) and a Spatial Error Model (SEM), I can use the Lagrange ...
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1answer
10 views
Capturing effects / Controlling for variables [duplicate]
I understand the idea behind regressions and know how to interpret them, however, when I hear the term "capturing the effect of.." or "controlling for.." so far I've just accepted it without ...
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14 views
Selected variables varies depending on whether or not standardization is in lasso regression (glmnet)
The paper often suggests both standardized and unstandardized coefficients in the lasso model (glmnet in R).
However, when I run glmnet, the selected variable is different depending on standardized =...
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13 views
SVM as linear equations
I'm using SVM for a regression problem (sklearn.svm.SVR). After I train my model I use these 2 attributes svr.coef_ and ...
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27 views
How to compare LME regression coefficients across models with same variables but different sample sizes/trial numbers?
I have a quite specific situation that does not seem to be covered by other, similar posts: I ran a study where a task (Task A) was periodically interrupted by a probe that asked participants what ...
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Using a subset of parameters in joint confidence region of a linear model
For a standard linear model of the form $y = X\beta + \epsilon$, where $\beta$ is a vector of parameters. we can calculate an individual confidence interval for each parameter (of 1-$\alpha$ quartile)....
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How to interpret the resulting negative regression coefficient? [duplicate]
How to interpret the resulting negative Poisson's regression coefficient? I am investigating the effects of environmental factors on mortality. A negative regression coefficient means feedback (proves ...
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How can I compute the standard error and confidence intervals for the base level on a variable?
I'm running a GLM with a tweedie, log-link function. That said, I have a categorical variable that transformed to dummy variables leaving off one of those variables when I modeled.
Now that I'm ...
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How to measure the “Impact/influence” of a feature y on Logistic regression model based on the coefficients?
I have a dataset X which contains probabilities returned for classification 4 different classification models, say M1, M2, M3, M4 those probabilities are use to feed a fourth model M4 and that model ...
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Refining a difference-in-difference analysis
I'm doing a difference-in-differences analysis with one pre-treatment time (0), and two post-treatment time points (1,2).
My basic regression model is:
= $β_0+β_1T_1 +β_2T_2 +β_3S+ β_4(S∗T_1)+β_5(S∗...
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Ordinal Logistic Regression in R - Understanding coefficients
I am creating an OLR model using R with the polr function in the MASS package. All of my predictors are also ordinal data, all of the data is the integers from 1 to 5 coming from a customer survey.
I ...
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1answer
20 views
Incorporate continuous group level variable in a hierarchical model?
I aim to assess the effects of difficulty (continuous variable) and trial type (0/1) on whether a subject has been correct in a logistic regression model. However, I have also measured subjects ...
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42 views
R-squared and sample size
I was wondering if R-squared is affected by the sample size? Is adjusted R-squared also affected?
The reason behind this though is, that i have run a multiple linear regression on two samples. The R^...
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30 views
Dynamic regression, models with coefficients = 0 chosen as top models
I am running auto.arima on part of a time series (training data) using all possible combinations for several external regressors. I then choose the top 5 models according to fit to testing data using ...
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Interpretation of functional regression models for scalar response
I have an application scenario in which I want to determine a single outcome from the course of a series of measurements.
I decided to give functional regression a try, so I read and ran the example ...
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Incorporating rank-ordered logit results from different samples
I would like to create rank-ordered logit models to predict the outcome (winner in this case) of variants of a multi-player game. For the most part, the predictors for each variant differ. However, in ...
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Shapley value vs ridge regression
My goal is to get the feature importance for multiple regression. I have a data set with some multicollinearity. I found two methods to solve this problem.
The first one is the Shapley value. ...
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1answer
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Testing the difference between two independent regression coefficients
I would like to test the difference between two independent regression coefficients. David C. Howell's book 'Statistical Methods for Psychology' (Chapter 9.11) suggests that there is a t-test for ...
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Results of a survival analysis change when converting the data to counting process format
Consider the following simple example:
...
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How to calculate coverage rates for 95% confidence intervals for estimands (like regression coefficients)?
I'm working on a Synthetic Data Generation model, and I'm confused about a metric mentioned in a seminal paper (details of paper added below)
Context: Synthetic Data Generation involves sampling from ...
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OLS reinterpretation (?)
I have read on a book written by a professor something similar to the following and want to check this statement on the forum, since it is the first time I have heard it. I have read that the OLS ...
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1answer
45 views
Determining Intercept for Regularized Logistic Regression
Going off of the standard set up, we have $N$ observations and $P$ predictors stored in the data matrix $\mathbf{X} = \{ x_{i,j} \}$ for $i = 1, \ldots, N$ and $j = 1, \ldots, P$. The response is ...
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How do I compute a Cohen's d from b weight and standard error?
From Table 3 and the paragraph below, you have a good deal of the information I have available. N's for taser and non-taser conditions are 339 each. My initial inclination is to take the raw B weight ...
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How to get this coefficient in multiple linear regression?
I'm reading a paper in epidemiology.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2744485/
While I'm reading this article, there is a formula about multiple linear regression.(in this paper, (2) is ...
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addressing the effect of the independent variable on the dependent variable for 2 different types of individuals
I am estimating the effect of a continous treatment X (that goes from 0 to 1) on a dependent variable y (data is taken through an experiment).
I have around 250 Individuals in my dataset that can be ...
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16 views
Understanding subgroups and covariates in linear regression
I'm trying to better understand how adding covariates, especially possible confounders, to a linear regression affect the regression results. I also want to better understand the relationship between ...
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4answers
141 views
Big Sample size, Small coefficients, significant results. What should I do?
I did some quantitative research and I used Rank-Order logistic regression in Stata. The the independent variables have almost 0 p-value which shows they have significant effect on dependent variable. ...
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33 views
Logistic regression vs segmentized logistic regression
This might be a very rookie question. I need help interpreting the results of my logistic regression.
Assume I have the following model: y ~ categorical + numerical...
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R - Interpretation of coefficients and written form of fitted model in lm() linear regression when using poly()
I've tried reading several resources on poly(), I'm not able to see an answer to my question. My question pertains how I might present my fitted linear model in a way that the coefficients are ...
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Linear model on decompose time series in R and interpretation [closed]
I am a newbie in time series.
I need a help with an interpretation of simple example of time series.
I would like to analyze whether trends over time of time series significantly increases/decreases ...
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Interpreting Multiple Regression [duplicate]
I am working on my thesis and I had to do a multiple regression. I have only 45 samples and I checked that there were not problems of multicollinearity (VIF < 3) and the residuals are normally ...
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1answer
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Substantive Interpretation of Negative Binomial
I am trying to interpret the output from a negative binomial regression.
Online, I read that we can exponentiate the coefficients to get substantively significant values.
However, I know that this ...
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Are correlated errorbars useful for regression fitting?
Let's say I have a dataset that roughly fits a 2nd order polynomial but I trying to fit it using a linear regression (see image). The error in my y measurement depends on y, but the coefficient of ...
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How Do I Summarize To a Single Estimate After Bootstrap Resampling For Various Statistics?
It is relatively straightforward when I want to know about the coefficients, fitted values, residuals and residual standard error of my (ordinary least squares) regression models, especially if you ...
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Combining regression estimates by summing
I want to know if one can combine regression estimates from panel regressions when the new dependent variable is a sum of the dependent variables from previously estimated regressions.
To be ...
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How to average 1000+ regression coefficients?
I am doing OLS regression on 1000's of stocks forward returns against a factor score. All the factor scores are the same model results for each stock at some point in time and vary between 1-5.
My ...
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Help with meta-regression
I want to implement a meta-regression and require some assistance. Suppose that two univariate features ($X$ and $Y$) were measured from two samples $A$ and $B$ of size $N_A$ and $N_B$, respectively. ...
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Creating a risk score from Cox Regression
I have two datasets with palliative cancer patients including 106 and 60 patients, respectively. I have biomarkers of inflammation and coagulation, as well as clinical characteristics for all patients....
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5answers
281 views
How to interpret regression function with categorical variable?
I am trying to figure out how to interpret a regression function with no intercept and one categorical variable performed on a survey data. Each participant marks which actions, from a list of 25, ...
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Does the “divide by 4 rule” give the upper bound marginal effect?
In the logisitic regression chapter of "Data Analysis Using Regression and
Multilevel/Hierarchical Models" by Gelman and Hill, The "Divide by 4" rule is presented to approximate average marginal ...
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Non-linear regression where dependent variables are dependent on different independent variables in R
I would like to know how to proceed with the following non linear regression analysis, which is a simplified version of my real problem.
5 Participants where asked to observe the speed of three ...
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1answer
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Help needed to Interpret ln(y) = a +b (Standardized X)
I am analysing server data and I have a scenario where I need to get the % by which Y is changed because of a unit change in X:
EDIT: I am doing a Linear Regression in Python
(and its other forms ...
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1answer
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Why does the inner product or norm represents the variability of a random variable?
I am studyng about the $R^2$ coeficient in a OLS regression. I would like to understand the following statement: One measure of the variability of the dependent variable $y$ is the sum of squares:
$...
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Closed-form solutions for constrained multiple linear regression
Normally a multiple linear regression is unconstrained
$$y=X\beta+\epsilon$$
so that closed-form solutions in the case of data orthogonality ($X^\top X=I$) are
$$\beta=(X^\top X)^{-1} X^\top y$$
...
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How to convert orthogonal polynomials from MULTIVARIATE regression to basic polynomial equation [duplicate]
I believe the link below converts the coefficients of one x from orthogonal to monomial form, but does someone know an edit to that code that can convert the coefficients of many x's in one regression ...
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Chow test results interpretation
I am analysing time series data right now using gretl, and want to test for a structural break, but I am not quite sure how I have to interpret the results.
Let's say I have a wheat price and flour ...
