Questions tagged [selection-bias]
Bias introduced by non-random selection of observations, such that the sample is not representative of the underlying population.
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questions
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1answer
14 views
How to estimate the impact of policy on labor supply if the policy causes death, too?
Suppose people can make only one of three choices A, B, C.
A = Death
B = Survive, Work
C = Survive, Not work
I want to study the impact of an exogenous policy on ...
1
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0answers
46 views
Is this referring to the true underlying distribution, or the distribution of our sample?
I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In the introduction, the author says the following:
One of the most common ...
0
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1answer
23 views
Endogenous Sample Selection and Heckit Correction in relation to Research Question
I am researching the funding amounts of start-ups. I am calculating two models:
...
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0answers
10 views
Truncation based on two variables
I have some data, which has been constructed from multiple API pulls. Observations have an expiry date, $x_i$, which means that observations which expire before the API pull is done do not appear in ...
10
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3answers
186 views
Abraham Wald survivorship bias intuition
During World War II, the statistician Abraham Wald took survivorship bias into his calculations when considering how to minimize bomber losses to enemy fire. Wald noted that the study only considered ...
0
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1answer
56 views
Heckman Selection (Selection vs. Outcome equation)
A common example of the Heckman selection model involves wages, which are only observed if an individual chooses to participate in the labor force. The first stage probit model dependent variable is a ...
1
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2answers
38 views
How to solve selection bias in a survey?
Selection bias often happens in survey studies. For example, sending out a survey to 10,000 customers to ask whether they like one specific product or not. Only 10% of people respond and 80% of them ...
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0answers
116 views
Heckman with second step probit in R
The functions selection and heckit (package sampleSelection) support a binary dependent ...
1
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0answers
24 views
Selection bias in categorical independent variable in regression analysis
I have an issue with selection bias in my independent variable and I am uncertain of the best approach to correct for it.
I'm looking at soccer data and trying to make some forecasts on players from ...
0
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1answer
20 views
Alternatives to balance tables to examine selection bias
I was wondering if someone has ideas to statistically examine selection into programme participation? For example, would it make sense to present the results of a propensity score analysis?
Thank you
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0answers
16 views
Correcting for known imputation bias
I have a survey sample which includes income values by type of income for a significant number of high-income households. Some of the income data is measured, i.e. present in the responses of the ...
0
votes
1answer
123 views
Sample Selection Bias in Logistic Regression [duplicate]
I'm working on a classification problem where I expect
$True\ Positive\ Rate =0.999$
$True\ Negative\ Rate = 0.001$
To model this data, I have created a training set with an equal proportion of ...
5
votes
2answers
63 views
Favored methods for overcoming selection bias (special attention to healthcare fields)?
I am frequently measuring the effect of behavioral health treatment interventions on outcomes of interest. However, comparing the relative efficacy of different types of treatment is tricky - more ...
0
votes
1answer
43 views
What is the correct notation for expressing a mixture of distributions?
In a normal classification context, the training instances are drawn from a distribution $D$ which is defined over $X \times Y$, where $X$ is the feature space and $Y$ is the label space. When ...
0
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1answer
53 views
Sample selection bias
In Learning and Evaluating Classifiers under Sample Selection Bias, we suppose that
examples $(x, y, s)$ are drawn
independently from a distribution $D$ with domain
$X × Y × S$ where $X$ is the ...
0
votes
0answers
147 views
How to perform inference on inverse Mills ratio in Heckit estimation?
I want to estimate log(wages). Most wage estimations suffer from sample selection bias.
So I used the two step heckit procedure to correct for it.
The problem is that I get an insignificant inverse ...
1
vote
0answers
69 views
Can selection bias be solved by including control variables?
Omitted variable bias can be solved by including covariates that are omitted. However, can selection bias also be solved by including covariates?
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0answers
21 views
Logistic regression when only TRUE values are observed, but a control sample exists
I'm involved with a creel survey. We have reason to believe that anglers are keeping the larger fish they catch, or at least that a relationship exists between the size of caught fish and the ...
0
votes
2answers
151 views
Correcting sample selection bias of binary classifiers
In fraud investigation the number of detected fraud cases can be very small when compared to the total number of cases. This would also apply to rare desease detected in a very small number of people ...
0
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1answer
386 views
IV-estimation vs. Heckman's selection model
I am trying to grasp the difference between IV-estimation and Heckman's selection model.
I do that by considering the following set-up. My outcome if interest is y ...
2
votes
1answer
810 views
Why does weighted bootstrap have awful coverage even in toy example?
I'm interested in using the weighted bootstrap to correct for selection bias with a known form. I simulated a very simple example where the underlying data, $X$, are $N(0,1)$ and we are calculating a ...
6
votes
2answers
218 views
Is this actually an example of selection bias?
In Lesson 3, Chapter 3 of Miguel Hernán's edX course on causal diagrams, he presents this DAG:
It represents a study on the effect of hormone therapy on lung cancer (whether hormone therapy causes ...
3
votes
2answers
250 views
Usage of Heckman estimation for a random sample
My colleague argues to use a Heckman Model in the following case (Agricultural economics):
I have a random sample of farmers (n) of the general population N. In n some observations apply a given ...
2
votes
1answer
161 views
In what instances do we need to worry about Heckman correction for selection bias?
I understand that Heckman selection models attempt to address selection bias by running two-part models. In the oft cited example of determinants of wage offers: 1) we have a group of people who work ...
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0answers
69 views
How to handle bias due to self-selection in one group
I want to compare two or three social groups across a set of dependent variables, using data from a longitudinal survey.
The problem is that membership in one of the groups leads to a self-selection ...
4
votes
0answers
230 views
Correcting Sample Selection Bias given actual Distribution
I have two datasets, both from the same population:
The samples from the first survey are quite representative of the underlying truth. However, the second survey comes with a change in distribution ...
5
votes
4answers
259 views
Bias induced from model selection
I am trying to understand the following sentence
Cross-validation and information criteria make a correction for using the data twice (in constructing the posterior and in model assessment) and ...
2
votes
0answers
68 views
Adjusting for selection bias in a structural topic model
I want to build a structural topic model that adjusts for selection bias into the sample of entities about whom documents are written. I wanted to use the stm R ...
1
vote
2answers
2k views
Different forms of Inverse Mills Ratio & their interpretation
I have noticed different authors using different forms of IMR, i.e., $\frac{f(x)}{F(-x)}$ or $\frac{f}{(1-F(x))}$ depending on whether they are modeling selection or non-selection in the first-stage ...
10
votes
1answer
18k views
Interpretation of coefficient of inverse Mills ratio
How do you interpret the coefficient of inverse Mills ratio (lambda) in two step Heckman model?
