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.

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Find the effect of a attribute value on an outcome by eliminating confounding values

I have a series of lets say five attributes. The first attribute is called diagnosis code 1, the second diagnosis code 2 etc. The values are codes which represent diseases. In other words, each ...
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5 views

Mixture model for dependent observations with additive group-level confounders

I'm looking for a special type of mixture model (described below) and I'm hoping to get some hints with regards to relevant literature to look at or names to be searching for. On the general level, ...
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Dropped cases from matched studies

We have cohort data and a rare exposure which we are matching to controls in a large epidemiologic dataset. The matching variable is a deidentified neighborhood indicator (cluster) which guarantees ...
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22 views

Issue with controlling confound in multinomial regression analysis; different results when removing kids on meds

I examined the influence of ADHD on abnormal bodyweight in a very large, national sample of children. In my multinomial regressions, I controlled for several specific confounds, which have been shown ...
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17 views

Alias Structure of one-fourth replicate of a $4^2$-Factorial Design with interaction $\text{A}{B}^3$ confounded

For finding the Alias of main effect A , i started as the following : $\text{A}$$\times$ $\text{A}{B}^3$$=\text{A}^2\text{B}^3={(\text{A}^2\text{B}^3})^2=\text{A}^4\text{B}^6=\text{B}^2$(mod ...
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23 views

Meta-analysis with known confounder

I’m performing a meta-analysis in which the main outcome of interest is a correlation coefficient between two variables, $X$ (a psychological measure) and $Y$ (a biomarker). $Y$ is known to be ...
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63 views

Infer causality with high collinearity

I recently started to ask myself how to measure the impact of education on indexes like GDP: what is the outcome of mathematics or computer science on GDP, at the country level for instance. In this ...
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52 views

Random forest: confounding factors

I have N variables in K samples. There is a classification variable, T (treatment), and a confounding variable -- sex. Unfortunately, in the "no treatment" (CTRL) group there are significantly more ...
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69 views

What is the purpose of precision variables?

Why do we need to include precision variables in a regression model (i.e., a variable that is associated with the outcome but not the predictor of interest)?
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70 views

Including confounders in a model

Suppose that you are performing a linear regression examining the main effect $x_1$ and want to adjust for possible confounders $x_2, x_3, x_4$. Is it better to have an unadjusted model and a model ...
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133 views

Multicollinearity when adding a confounding variable

When you run a regression on ice cream sales with predictor shark attacks, you find a significant coefficient. But that is because there is a confounding variable temperature. But how do you correct ...
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162 views

Whitening data before regression, should I whiten the response variable too?

I have some data X where the samples are not independent (they're correlated with each other), and I'm trying to do a regression of some continuous variable y on X. This sample correlation could ...
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72 views

Purposeful selection and confounding

I conducted purposeful selection as outlined in Jewell's Statistics for Epidemiology. The log likelihood tests showed covariates, which I considered to be confounding though not significant in the ...
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295 views

How to calculate permutations of categorical variables with R

I want to simulate or calculate probabilities of combinations of group membership for different sample sizes (e.g., n= 3, 4, 5, 10, or 100) for two groups (of the same sample size). Each outcome could ...
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27 views

Discounting effect of one variable on another variable

Hope I manage to explain this simply enough so I don't end up confusing myself and you along with me! I've measured a variable (rate of soil respiration) throughout the day. However my variable is ...
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283 views

What examples of lurking variables in controlled experiments are there in publications?

In this paper: Lurking Variables: Some Examples Brian L. Joiner The American Statistician Vol. 35, No. 4, Nov., 1981 227-233 Brian Joiner claims that "randomization is not a panacea". This is ...
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27 views

Group comparison: match on variable

I am comparing two groups (A and B). Group B is matched to group A on variable X, by sampling two subjects from a population for each subject in group A. Group A has ~200 subjects, group B has ~400 ...
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36 views

Dealing with perfectly confounded microarray experiment

I need to compare microarray data, where all of the "cases" were hybridized in one batch and all of the "controls" in another, so I have no way of removing this batch effect. What would be the best ...
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40 views

Case-control study with data collected in batches

I have (matched) case-control data. The data is collected in batches in such a way that the batch determines some quality of the data (there is a 'batch' effect). Also, the cases and controls were ...
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Factor Elimination in Microarray data analysis

Many researchers must have issues with unwanted variance between experiments, be it technical or otherwise. What solutions are the most appropriate and commonly used to deal with (eliminate) such ...
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49 views

Confounder - definition

According to M. Katz in his book Multivariable analysis (Section 1.2, page 6), "A confounder is associated with the risk factor and causally related to the outcome." Why must the confounder be ...
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2answers
116 views

How can I convert my dataset into a new dataset which is adjusted for confounding covariates?

I have used software before to do linear regression and factor in/out the confounding variables, but what I would like to do is generate a new data set which is adjusted for the confounding variables. ...
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204 views

Hypothesis test on data with confounding spatial clustering

This is a bit of an elaboration on a question I posted earlier, since I feel like my approach to the problem as a whole is probably quite flawed. Suppose I have a set of treatment and control cells, ...
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174 views

Can ANCOVA disagree with multiple regression?

I have 3 categorical variables (CVa, CVb, CVc) all 0 or 1. Two continuous variables (IV1, IV2) are confounding my observational study. The multiple regression ...
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389 views

Does adjustement completely remove the effect of the confounding variables?

This might seem a silly question but I am really confused about it. In theory adjusting for a confounder variable should remove its effect. Is this always true? and does this mean that the effect of ...
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107 views

Visualizing association results after adjusting for confounders

I'm trying to find a way to visualize the results of an association analysis where I corrected for confounding variables. I have a set of cytokine data (amount of protein in the blood) from a set of ...
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226 views

Adjusting for confounding variables in binary response variables

I have a dataset of patient information and I'm looking to find a way to compare two groups of patients and take into account confounding variables. My dataset has an N of ~1500 and I'm looking for a ...
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144 views

Techniques for analyzing ratios

I am looking for advice and comments that deal with the analysis of ratios and rates. In the field in which I work analysis of ratios in particular is widespread but I have read a few papers that ...
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121 views

Can lack of main effect and lack of interaction be caused by the same confound?

Can the lack of main effect have the same underlying cause as the lack of interaction in 2-way ANOVA? My results failed to reach significance for variables of gender and language. Is it possible that ...
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97 views

Can a confounding variable be correlated with the DV and not the IV?

Can a confounding variable be correlated with the DV and not the IV? I have heard of the DV being corr. but I can't find IV in any textbooks. I found this def. in Wiki: ...
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Examples of a confounding variable [duplicate]

Possible Duplicate: Correlation does not mean causation What is your favorite example of a confounding variable / confounding effect?
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524 views

Is it possible to have a variable that acts as both an effect modifier and a confounder?

Is it possible to have a variable that acts as both an effect (measurement) modifier and a confounder for a given pair of risk-outcome associations? I'm still a little unsure of the distinction. I've ...
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94 views

Using z-standardization to account for covariate

I would like to know whether z-standardization is an appropriate way to account for a covariate. Please consider the following dummy example (I am not interested in the interpretation of the result ...
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167 views

Understanding regression results when data are subsetted

I have some data that span several years: 2006-2010. I have run logistic regression to model the data. For the whole dataset, I get a 95% confidence interval for the odds ratio of a parameter of ...
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304 views

Which test to use to check if a possible confounder impacts a 0 / 1 result?

I've been given a task with the following question: Investigate whether or not the type or treatment (0 or 1) has an impact on the result (0 or 1) The same as 1), but keeping in mind another ...
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Checking whether or not a variable has impact

For a statistics assignment, I've been given a data set (regarding drug prevention) and a few questions. One of the questions is to check whether or not the choice of treatment, treatment A or ...
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77 views

Account for group age differences

I have a dataset of two patient and one healthy control group which I would like to compare (using R) with respect to a continuous outcome variable (each subjects is measured once). However the groups ...
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190 views

What to conclude when you fail to find an association in an epidemiological study?

Normally when somebody finds an association in an epidemiological study people are quick to point out that it doesn't prove causality, that there are problems of missing co-founders, that it is at ...
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171 views

References about univariable vs multivariable variable selection

Suppose I have variables $X_j$, $j=1,\ldots,p$, some of which are correlated, and some continuous output $y$. I want to rank the variables by importance. One way is to do an association test of each ...
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181 views

Please help to understand Agresti's book

I need some help to understand some topics in Agresti's Categorical Data Analysis. In section 6.3.1 (p 231), he provided a model like: $$ \text{logit}(\pi_{ik})=\alpha+\beta x_i+\beta_k^Z $$ where ...
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174 views

Does control get us closer to or farther from causation?

In logistic regression with an N of 40,000, purchase decision is unrelated to price. However, with certain demographic variables controlled, price can show a positive coefficient of meaningful ...
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Basic Simpson's paradox

I have a question about something that my statistics teacher said about the following problem: There are two hospitals named Mercy and Hope in your town. You must choose one of these in which to ...
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489 views

Identification of confounder in a logistic regression model example in “Applied Logistic Regression”

I am reading Hosmer's Applied Logistic Regression, and I am a bit stuck in chapter 3, when taking about interaction and confounders. In page 77, it states the following: Using the estimated ...
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Overmatching bias and confounding variables

As I understand it, matching is one way to identify causality in observational studies. By matching observations that are "similar" and comparing ones that did or did not receive treatment, you can ...
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354 views

Simpson's paradox or confounding?

Consider a scenario where a two-way contingency table is analyzed by a chi-squared test of independence and a significant result is found. Now, it turns out that this table is an aggregation of data ...
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Testing for confounding

Suppose we want to test whether $Z$ is a confounding variable for the effect of $X$ on $Y$. Is it enough to just check unadjusted and adjusted estimates of the coefficient of $X$ and see if they ...
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355 views

Non-parametric test with several confounding factors

I am pretty new to statistical testing with confounding variables, so please excuse if there will be some gross misunderstandings or basic questions. I want to test for systematic differences in ...
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How exactly does one “control for other variables”?

Here is the article that motivated this question: Does impatience make us fat? I liked this article, and it nicely demonstrates the concept of “controlling for other variables” (IQ, career, income, ...
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123 views

Differences in coefficients

Suppose I want to see whether $z$ is a confounder for a model with $y$ the outcome variable and $x$ the predictor. If I adjust for $z$, and the adjusted coefficient of $x$ changes versus the ...
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667 views

How to identify suitable variables to assess confounding, mediation and effect modification?

Imagine that you are planning a study about risk behaviours among HIV positive injecting drug users. All the individuals included in the sample are injecting drugs and all are HIV positive. The main ...