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Results tagged with logistic
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user 24515
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
2
votes
Using a set of binary logistic regressions with multiple choice categorical response variable
The choice between one multinomial and a series of logistic regressions is in most cases relatively artificial. … The biggest disadavantage is that you cannot test simultanous parameter restrictions across the logistic models, which is rather straight forward in the multinomial case. …
- 6,704
1
vote
How to test for mediation when working with binary data?
You can easily model this in structural modeling software such as Mplus. You need a model of
X --> Z --> Y
where Z is the mediator and inspect fit and/or residual correlations. If the model fit is p …
- 6,704
1
vote
0
answers
130
views
How should I handle measurement error in logistic/probit regression and what are its effects?
I am concerned with the problem where dependent discrete variable $R$ is to be modelled by continuous predictor $X^*$, which is subject to measurement error $u$ of the form $$X^*=X+u$$ ($X$ being the …
- 6,704
23
votes
3
answers
14k
views
What is the relationship between the Beta distribution and the logistic regression model?
My question is: What is the mathematical relationship between the Beta distribution and the coefficients of the logistic regression model? … To illustrate: the logistic (sigmoid) function is given by
$$f(x) = \frac{1}{1+\exp(-x)}$$
and it is used to model probabilities in the logistic regression model. …
- 6,704
8
votes
Stochastic gradient descent: why randomise training set
Generally, in case your data is ordered (see e.g. Mnist data set) SGD will have problems. Also, in case you run through it multiple times (so called epoches) having the same order on each run through …
- 6,704
4
votes
Accepted
How should I interpret this residual plot?
The plot is very dense so it is not easy to see all trends there may be. You could run alternative tests for hetoroscedasticity and autocorrelation to get additional diagnostics.
What is visible is t …
- 6,704
5
votes
Comparing nested binary logistic regression models when $n$ is large
One option is to use pseudo R-square measures for both models. A strong difference in pseudo R-square would suggest that the model fit strongly decreases by omitting V17.
There are different kinds of …
- 6,704
5
votes
1
answer
2k
views
How to make correct predictions of probabilities and their uncertainty in Bayesian logistic ...
In the context of Bayesian logistic regression, outcomes $y$ are binary (discrete) and covariates $X$ are given. …
- 6,704
3
votes
1
answer
2k
views
Can naive Bayes model this type of (approx. circular) decision boundary?
Logistic regression (with linear features)
Neural Networks
Naive Bayes
Support vector machine (with linear Kernel)
I was convinced the answer is Neural Networks and Naive Bayes. …
- 6,704
9
votes
1
answer
932
views
Why is the Bayesian credible interval in this polynomial regression biased whereas the confi...
The functional relationship between a covariate $x$ and $p(y_{obs}=1 | x)$ is 3rd order polynomial with logistic link (so it is non-linear in a double-way). … The green line is the GLM logistic regression fit where $x$ is introduced as 3rd order polynomial. …
- 6,704