Questions tagged [confounding]
In statistical models, confounding is said to occur when the apparent dependence of the response on a predictor is partially or wholly due to the dependence of both on a third variable not included in the model, or dependence on a linear combination of other variables included in the model. Confounding with a variable included in a model is often called multicollinearity. A synonym is *aliasing*, used in design of experiments.
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Understanding Ignorability and Confounding Variables
I am reading Data Analysis Using Regression and Hierarchical Models and am confused by the concept of ignorability. The description in the book seems to say different things.
Said another way,
we ...
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Confounding Variable in Regression Model: Simpson's Paradox
I am working on a mixed effects regression model where Yi = exam score of student i.
The explanatory variables are the following:
Level 3: school type (public vs. private) and school's socioeconomic ...
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Can I interpret the size of my regression coefficient when I only control for confounders and not non-confounding covariates?
I am very confused at the moment, for my bachelor's thesis I am performing a Panel Individual Fixed Effects analysis and have only controlled for confounders.
I was under the assumption that when I ...
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How to deal with possibly important predictors omitted during the building of an OLS multivariate linear regression model?
I am building a descriptive model using OLS multivariate linear regression. I have a couple dozen candidate predictors, but only around 200 cases.
Since I wanted at least 10 cases / variable for the ...
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Shrinkage of covariates in the Cox model
In a regression model (e.g Cox model) when there are too few events to support modeling all desired covariates / confounders, a possible solution is to apply shrinkage / penalise all but the exposure(...
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Three continous variables + 2 factors vs. five continous variables to control for confounders?
I am trying to make sense of the design for my Master's thesis.
I am looking at how three different types of play relate to anxiety in children. So I have three continuous independent variables ...
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Understanding "Multiplication/ Group Operation" in Fractional Experiments
There's a group operation, at least of sorts, in Fractional Factorial design that I'm trying to understand. For definiteness, let's say we have 3 factors; A,B,C , at two levels each . Please critique ...
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Chi-Squared for demonstrating confounding in Logistic regression (or not...)
I am using logistic regression for inference and classification, using data from 190 X-rays/subjects. We want to see if certain X-ray measurements could predict development of a disease (Case vs ...
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When does Dose Response Function estimation work better than simple regression?
I have been recently asked what is the difference between a Dose Response Function (DRF) estimation (as the one proposed in this link and this paper) and a statistical regression method. I therefore ...
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IPW recalculating with deterministic treatment
Let's assume I want to calculate the ATE for a certain deterministic treatment, such as surgery (i.e., one either had it or not), and I'm interested in a per-protocol analysis.
Note that those who had ...
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How can I test whether a moderation effect is only present due to confounding variables?
I plan to investigate the effect of a personality trait on reaction measures (emotional reactions and intention for political participation) in a vignette study with two conditions. I assume that the ...
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How to account for confounders in a simple correlation analysis?
Beginner question sorry - I'm a coder and need stats advice.
I have a dataset broken down by local area, with columns for the proportion of owners who are French, the proportion of owners who grow ...
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A covariate as an inherent part of predictor
I want to compare brain volumes of two disease categories: young vs. old onset. I know that age, in general, is a covariate for brain volume. That is, the older the age, the smaller the brain. However,...
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Adding and interpreting covariates in logistic regression
I have a dataset and I want to do a logistic regression between the continuous variable "A" and the categorical variable "B". However, I also wanted to include "age" and &...
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Confounding variables in a t-test [duplicate]
Suppose you want to compare a certain score (dependent variables) in two groups A and B (independent variable), to see if one group has significantly better scores. You can run a t-test. Now what if ...
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