All Questions
14 questions
0
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1
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99
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How can I calculate residuals of a dependent binary variable, using a glm (logistic) model that was fit on a different sample?
I have a data frame D1 in R with a dependent binary variable Response (0/1) and a set of covariates like age and gender. I want to know how "typical" ...
0
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0
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31
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compare the outcome of logistic regression (predictive probabilities) before and after an event
To train a glm model, I'm using using clinical data (~10 features) of a large cohort of patients and healthy subjects. I'm using a smaller test group (around 20 people) and predict their outcome (...
4
votes
2
answers
382
views
Prediction using a logistic regression model
Given a logistic regression model:
$y \in \{0, 1\}$
$ P(y=1|x;\theta) = h_{\theta}(x) = \frac{1}{1+\exp(-\theta^T x)}$
And given the value $\theta^*$ which maximises the conditional likelihood $P(y|X; ...
1
vote
0
answers
414
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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 ...
1
vote
1
answer
681
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Help testing the predictive quality of a binomial GLM (currently attempting using the "caret" package)
Hello world (sorry for the novel; if you read this, I appreciate it!),
I'm running into a question that is probably a mixture of how to approach a problem of modeling and the technical difficulties ...
1
vote
2
answers
735
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Logistic regression and prediction
I'm following this tutorial to fit a logistic regression model on to my data which has a binary response. I've understood the reasoning behind each step, apart from why the author checks the first 5 ...
4
votes
2
answers
636
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logistic regression for competitive games
I am interested in using logistic regression to model a competitive game.
The data looks something like this:
...
6
votes
1
answer
2k
views
Why is ROC curve used in assessing how 'good' a logistic regression model is?
Suppose you fitted a logistic regression model and find out that it is well calibrated,that is, good agreement between observed outcomes and predictions. Also, suppose that it agrees with some ...
1
vote
1
answer
165
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Logistic regression doesn't fit this Infection risk analysis. Wrong model?
I am looking at a logistic regression model for predicting hospital acquired infection likelihood (HAI) from predictors of whether germs are found on the x number of patients (Patient), x number of ...
2
votes
1
answer
2k
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Can I set up multiple probability models that sum to 1?
I am interested in consumer research. For simplicity's sake, assume I want to know if people prefer Burger King or McDonald's. My questionnaire will contain a question like "If you had to choose one ...
2
votes
0
answers
167
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What should I do when logistic regression model doesn't perform well on test sample?
For logistic model, I divided dataset into two parts training sample (70% of 360 data point (observation)) and test sample (rest 30% of 360) randomly. After that I built logistic model on training ...
5
votes
1
answer
3k
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Difference Between Discrete Time Proportional Hazards and Logistic Regression
My data consists of one row per person, per month that person was "exposed" to an event. So the month is the discrete time and the row corresponds to one "person-month".
There are a few independent ...
4
votes
1
answer
2k
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Is it possible to get a covariance matrix of fitted values for a GLM model in R?
I would like to get a covariance matrix of fitted probabilities for a logistic regression model in R. I would like to do this because I want to find the variance of the difference between the two ...
1
vote
3
answers
2k
views
How to choose data for training a predictive model for attrition prediction
Trying to build a predictive model for attrition prediction at service desk/call center.
Have daily data on the following parameters:
1.Call quality - QTM (0-100%),
2.No. of calls - Calls(Number)
3....