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Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

4 votes
2 answers
423 views

continuous vs categorical logistic regression for marks and admission

I have a list of marks scored by students in Science (X, between 0 to 100%) and whether they went to college to or not (Y). High marks in science showed a higher concentration of college admits and lo …
Maddy's user avatar
  • 768
2 votes
1 answer
287 views

Signs on logistic regression betas flip relative to observed - expected counts from chi-squa...

I then calculate logistic regression coefficients to validate my hypothesis. … However, this Bin 1 has a negative coefficient from logistic regression. Is my understanding wrong - when observed >> expected, logistic regression coefficient should be positive? …
Maddy's user avatar
  • 768
2 votes
1 answer
2k views

Logistic Regression using dummy variables in MATLAB

How can I code a logistic regression model in MATLAB that proves that some of these variables explain the bankruptcies better. There are 4 variables: which implies 3 dummy variables. … .]; % 1 means bankruptcy I think I should use glmfit (from http://matlabdatamining.blogspot.com/2009/03/logistic-regression.html) but I wasn't sure if using dummy indicators would require any additional …
Maddy's user avatar
  • 768
12 votes
1 answer
20k views

How to choose the cutoff probability for a rare event Logistic Regression

Logistic Regression should work fine in this case but the cutoff probability puzzles me. In common literature, we choose 50% cutoff to predict 1s and 0s. …
Maddy's user avatar
  • 768
2 votes
0 answers
1k views

Chi-square on a categorical variables (derived from continuous distribution)

It has been pointed out to me at continuous vs categorical logistic regression for marks and admission that using such an approach with logistic regression may be flawed. …
Maddy's user avatar
  • 768
6 votes
2 answers
6k views

Logistic regression using penalized likelihood (lasso?) in Matlab/R

I am trying to use logistic regression in a scenario where there are very few positives. I'm aware that maximum likelihood suffers from small sample bias. So MATLAB's glmfit doesn't work for me. … MATLAB also has the function lassoglm but I'm not sure if it can be used for logistic regression with few positives. Can you please confirm/suggest alternative? …
Maddy's user avatar
  • 768
1 vote
0 answers
91 views

Compare Frequencies

Do I perform univariate logistic regression 6 times and compare model results? (all prob are=0 for the asset growth=100% bin using LR/glmfit). I use MATLAB. …
Maddy's user avatar
  • 768
3 votes
1 answer
2k views

Choosing between chi-squared / logistic regression vs difference of mean tests for studying ...

I then check the results using logistic regression which actually gives me negative coefficients for low cash balances! (Using LR is fine as I have ~2000 positives for ~150k observations). …
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  • 768
9 votes
3 answers
25k views

Interpreting coefficients in a logistic regression model with a categorical variable having ...

There is quite some content online interpreting odds in a logistic model with a dichotomous predictor. …
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  • 768
7 votes
3 answers
16k views

When to divide data into training & test set in logistic regression?

I am using Logistic Regression in a low event rate situation. … Overall universe: 46,000 Events: 420 Conventional logistic regression models divide the data into training and test sets and compute the error rates. …
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  • 768