All Questions
37
questions
2
votes
0
answers
34
views
Best way to address selection bias when outcome cannot be randomized
I have an (low incidence) binary outcome compared between 2 groups. The intervention for group 1 is coming from a specific type of center (academic) while group 2 from a different center. It is not ...
- 41
1
vote
0
answers
304
views
Logistic regression panel data fixed effects
I heard a remarkable claim at work last week
Fixed effects in logistic regression of panel data introduces bias, so we would want to do a linear probability model.
I find this remarkable for two ...
- 65k
0
votes
0
answers
49
views
Bayesian Logistic Regression: Correcting for Pre-Experiment Bias
In this post, I will outline a proposed procedure and ask for critical review of the approach's validity. The context is that in a business experiment, it is known that the response variable in the ...
- 3,382
1
vote
1
answer
107
views
Logistic regression of 'true model' has bias
I'm trying to train a logistic regression on simulated data. I have n=1000 simulations for the following variables:
binary proxy variable proxy = rbinom(n, 1, 0.5)
...
- 11
0
votes
0
answers
21
views
Is it possible to conduct a coefficient test within a multiple regression?
In an analysis of employment, a difference in means test shows that gender is important.
Multiple logistic regression using several specifications robustly identifies a positive coefficient on gender, ...
- 143
2
votes
1
answer
613
views
Classical logistic regression VS Firth logistic regression: comparison in power
I understand that in case of separated data, logistic regression via ordinary MLE has an upward bias in the p values, which implies that any penalized MLE designed to reduce this bias will have more ...
- 704
7
votes
1
answer
1k
views
Biased estimates in logistic regression due to class imbalance
I was asked by a reviewer to evaluate the robustness of the results of logistic regression, given that estimates can be biased by class imbalance in the outcome.
To contextualize, I have run three ...
- 71
1
vote
0
answers
136
views
Correct method to prevent survivorship bias?
I am trying to predict the most successful contact method (like social media, telephone, email) that will make people buy a product given some X input variables such as age, race, and gender. Our ...
- 11
1
vote
1
answer
124
views
Can ordered logistic regression suffer from omitted variable bias?
If I ran an ordered logistic regression, with say a couple of explanatory variables, is it possible that omitted variables can bias the categorical outcome of the dependent variable similar to how ...
user207543
1
vote
0
answers
408
views
Logistic Regression: how to reduce bias in data
I have a logistic regression model and my main goal is to predict probability of surviving using explanatory variables like age, gender etc. Each row in my data represents an individual and columns ...
- 7,544
0
votes
1
answer
888
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 ...
- 11
2
votes
2
answers
232
views
Is covariate significant in logistic regression
Im going to investigate if a disease have a negative impact on the development of children. The disease is the independent variable with additionally confounders.
Tests from the study have shown ...
- 51
0
votes
1
answer
47
views
Splitting large number of variables into three separate logistic models for variable selection
Is it appropriate to split up to 100+ variables into three groups then running each group into separate decision trees then run the new created features into their own separate logistic models to help ...
- 1
6
votes
1
answer
1k
views
Logistic Regression and Omitted Variable Bias
I just want to confirm that I am understanding this correctly. So if logistic regression models have omitted variable bias, does that mean that I should discard any logistic regression models that ...
- 209
4
votes
1
answer
2k
views
Bias corrected calibration curve (regression modelling strategies)
I have a question regarding calibration plot for a binary logistic regression model (calibrate)
in the rms(regression modelling strategies) package. The Bias-corrected curve (see below) shows if the ...
- 359