Questions tagged [regression]
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
30,768 questions
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Advice on regression approach
How should I handle a mass-point in the dependent variable when running OLS regression in R?
I’m working with a a household expenditure dataset (Living Costs 2019) where the dependent variable is the ...
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Endogeneity and Low DF in Annual FDI-GVC Model for Egypt: ARDL vs. VAR Alternatives
i am an undergraduate student working on an empirical project about the effect of FDI inflows on GVC integration in Egypt, using annual data from 1995–2023 (29 observations). My dependent variable is ...
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Is Bayesian ordinal logistic regression (OLR) a better choice than conventional OLR when certain cells have a small number of observations (<10)?
The outcome variable of my study is the level of knowledge of tobacco cessation services, with three categories: no, low, and moderate/high. The sample size is 660, but some predictors have cell ...
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Regression model for a survey [closed]
In our questionnaire the answers are in the categorical format therefore we used dummy trapping for the regression part, however we have a doubt to use which of the following 2 ways:
(i) For models ...
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Narrow vs Broad-based U-shape comparisons
I’m modeling mortality using a multivariate logistic regression model with a nonlinear effect of X1 and I’m examining whether this relationship changes across ...
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How do I estimate the linear effect for a factor so that my estimate doesn't depend on the sample size?
I’m trying to use the R poly() function with degree 1 to force glm to interpret a factor linearly. I’m puzzled by the fact that the size of the sample seems to increase the coefficient of the ...
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Borderline interaction p value
I’m working on a logistic regression model where I want to examine whether the effect of one continuous predictor (X1) on a binary outcome depends on another ...
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How can I compare models in weighted multinomial logistic regression?
I want to do a regression analysis after a GMM. I have a dependent variable with three categories (classes), which differ in their posterior probabilities. That's why I included the posterior ...
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Using ordinal logistic regression to extract insights with imbalanced data
I am attempting to understand how each independent variable effects the probability of each dependent variable, which are ordinal (0, 1 and 2). Therefore, I am attempting to use ordinal logistic ...
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Partialing out a time-trend I'm unable to evaluate
I am investigating the influence of policy X on grade outcomes.
Earlier research utilised a partial implementation of policy X to establish a natural experiment to compare "with X" and "...
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Prediction intervals for random-design simple linear regression
I am going through the creation of a prediction interval for a value drawn from the conditional distribution of $Y$ given $X=x$ under simple linear regression as shown in the image above. The ...
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Error in the slope of a linear regression
I am trying to find the uncertainty/error in the slope of a linear regression of a data set where the data contain standard errors. However, searching for this online is very confusing as there are ...
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Number of knots in splines (internal vs total)
I’m trying to understand how natural cubic splines (splines::ns) and restricted cubic splines (rms::rcs) handle knots — ...
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Why is my simulation not showing bias?
I am trying to observe the Nickell bias (https://www.jstor.org/stable/1911408) in simulation. For example, its said that using a lagged response as a predictor in a regression model can create a bias.
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Use of differential equations in statistical modelling
Consider a situation where there are multiple subjects and each subject has multiple measurements (response, covariates) over time. The goal is to identify a statistical regression model which allows ...
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