# Tag Info

Accepted

### Can a confounding factor hide a possible causal relationship? (as opposed to find a spurious one)

Yes Rephrasing the opposite of a confounder: It is definitely possible that an unobserved variable yields the impression that there is no relationship, when there is one. Confounding usually refers ...
• 10.7k

### Can a confounding factor hide a possible causal relationship? (as opposed to find a spurious one)

Following on existing answers, I wanted to give a concrete example. Imagine trying to figure out if the gas pedal affects the speed of a car. You observe how far the gas pedal is pressed and how fast ...
• 403
Accepted

• 30.9k
1 vote
Accepted

### Omitted variables problem

Section 4.1 of the Wooldridge text describes what's being considered: The correlation of explanatory variables with unobservables is often due to self-selection: if agents choose the value of [...
• 84.4k
1 vote

### Adjusting for confounding in linear regression model

It depends on the substantive nature of the relationship between the confounder and the other variables. Here's one example Let's say that you are running a model trying to predict income as a ...
• 3,246
1 vote
Accepted

### Endogeneity coming from omitted variable vs measurement error

I don't know if I'm the best to explain this but I'll give it a go. A measurement error is, for instance, when the person was supposed to code you as LFG in a dataset, but coded you as GFL. So then ...
1 vote

### Should I adjust for a confounder when it is colinear with a predictor?

that's not a bug that's a feature, you just showed that when you control for x2, x1 has no effect on y, which is exactly what you wanted to know. Good job. You also learned that x1 is highly ...
• 7,341
1 vote
Accepted

### Trade-off between omitting variables or dropping observations in multivariate logistic regression

This is an unnecessary trade-off, as data don't have to be "missing completely at random" (MCAR) to include cases with missing values in the analysis. In practice, you often have data "...
• 84.4k
1 vote
Accepted

### Is omitted variable bias possible with a perfectly correlated dependent and independent variable?

Yes, because omitted variable bias depends on the underlying causal question you want to ask. Suppose you are interested in explaining the causal effect of schooling on earnings (just to give an ...
• 30.9k

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