# Questions tagged [logistic]

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

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### Marginal effect clogit not significant

I developed a conditional logit model in Stata. The model is good and the variables are highly significant. Then I do mfx predicted (PU0) to determine the marginal effects of variables $\frac{dy}{dx}$....
1k views

### Variable selection / Dataset reduction for large datasets (in R)

I'm working on a behavioral scorecard modelling exercise, and many of the decisions taken to date have been based on the experience of a consulting credit analyst (whose experience software-wise is ...
65 views

### Modeling pass rates for departments and courses within a school

Suppose I have a regression model, for example a logistic regression model, which provides a score between 0 and 1 reflecting whether or not that a student will pass a course given certain variables: ...
193 views

### Using priors to detect an effect? logistic Bayesian regression

I have designed an idea and am looking for similar approaches in other literature/areas or if I have applied the Bayesian concepts wrongly. Here is a statement of my problem: I am modeling the ...
103 views

### Nested outcome categories in a multinomial logistic

I’m modeling a target-shooting video game. A player can shoot and hit the target, shoot and miss, or switch weapons. For simplicity, the outcomes are HIT, ...
278 views

### Variable selection with restricted cubic splines

Is there any function in R for doing variable selection (backward elimination) in a multiple logistic regression using restricted cubic splines like mvrs procedure for STATA?
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### How to test proportions of a Categorical response variable for a Repeated measures design with Unequal Sample Size?

I have a question about the analysis of a unequal sample size repeated measures data with categorical response variable. This experiment looks at 5 young and aged persons and for each of the ...
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### Do we need to apply the same transformation of predictors on a test dataset?

I first divide the dataset into training (75%) and test (25%). Then fit a logistic regression model on training data set. When fitting the model, I did some modification on independent variable, such ...
300 views

I am wondering whether there is ever justification in adjusting your logistic regression coefficients. For example, I have a logistic regression model that predicts that 4% of farmers will go out of ...
418 views

### Is there a better alternative to a logit / probit regression when all dependent variables are dichotomous?

I'm working on a clinical trial dataset with binary response. All independent variables are also binary. My first impulse was to simply run a standard logit / probit regression and be done with it. ...
226 views

### Combination of multinomial logit model and logit model

I want to analyze the determinants of credit constraints of a firm. I have information for both formal and informal credit. I have 6 categories of credit-constraint statuses of a firm for formal ...
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### SAS PROC LOGISTIC: Hosmer and Lemeshow test is good but Gini is bad?

I am using PROC LOGISTIC along with Class statements to do binary logit model(default=1,non-default=0) on a bank loan dataset ...
1k views

### Bayesian model averaging in R

I have a logistic model that I've built with the nls function in R. I want to use Bayesian model averaging for variable selection, but I can't find a package for ...
663 views

### What is the effect of merging categories on logistic regression estimates?

I have a logistic regression with a number of predictors variables including a factor with, say, 5 categories. The estimates for that factor compare categories 2-5 in turn to the reference category ...
3k views

### AIC and deviance don't agree

I'm trying to test the fit of two logistic regression models. I understand that deviance and AIC are good methods for this, but what if one model has better AIC but worse deviance? This is what I ...
2k views

### Convergence failure with step-by-step parameter estimates in SAS proc logistic using the OFFSET option

I'm trying to fit a logistic model of the following form: $$y \sim \frac{1}{1 + \exp(-\beta_X)}$$ where $$\beta_X = a_0 + a_1x_1 + a_2x_2 + a_3x_3 + a_4x_4 + a_5x_5$$ In my case, there is ...
348 views

### How do I compare 2 models?

I would like to show that a new biomarker (let's say percent tumor volume reduction at 3 weeks of treatment estimated with automatic methods) performs better than an old one (same measure, but based ...
64 views

### Which statistical test to compare same model with different parameters?

I have two datasets on people buying apples based on weight and price. One dataset in 2019 the other in 2020. I estimate a logit model with Utility = betaWeight * weight + betaPrice * price. Training ...
20 views

### Is it correct to combine any feature selection (backward/forward/stepwise) with regularization in logistic regression?

I use stepwise regression for exclude "worst" features (based on p-value) and after try to build model with L2 regularization on selected features. Emperically, this model is better that ...
44 views

### Determining the Weight of Categorical Variable's Coefficient

Lately, I have been studying about Logistic Regression, and I came across a question on how to handle categorical variable (as opposed to numerical ones). Let's suppose I have a data table with two ...
35 views

### Adjusted one sample test with logistic regression

Suppose I have a performance benchmark to beat from an established study. In this study sample, 60% of the patients belonged to stratum A, and 40% belonged to stratum B, and the performance in A was ...
28 views

### Appropriate statistic for describing differences between nested regression models?

I have run a series of nested binary logistic and negative binomial regression models in SPSS examining the impact of an intervention on re-offending outcomes. For example: Model A = Individual ...
32 views

### Ordinal variables in logistic regression

I am working with a data set with 3000+ rows. The response variable p is binary (1 representing purchase of a specific item, 0 representing no purchase) and I have ...
42 views

### Inconsistency of logistic regression in a parametric dose finding model

The following problem is a simplified model of dose finding in combination clinical trials. Assume we have a matrix $p = (p_{ij}) \in [0,1]^{K_1 \times K_2}$ representing the probability of non-...
37 views

### Problems with KHB method for assessing mediation in nested logit models

I have a binary outcome Y, a key independent variable X and a possible mediator Z, plus a control variable C. In my original analysis I ran a "restricted" logit model of Y controlling for X ...
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### How to analyse binary responses for various factors, including interactions: chi square, mixed models, logistic regression, or ANOVA on percentages?

I run an experiment where subject had to recognize an emotion from various musical stimuli (which were composed with a certain emotional intent). There were 4 levels of emotional_intent, subjects ...
58 views

### Sampling/Asymptotic Distribution of Estimated Coefficients of Logistic Regression

If I understand correctly, in a logistic regression, we have that $Y_i \mid X \sim Bern(S(X\beta))$ where $S(x)$ is the sigmoid function. Suppose we estimate $\beta$ using MLE and get $\hat \beta$. ...
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### Power analysis for multinomial logistic regression

I am planning a regression analysis where a continuous independent variable predicts 3 categorical outcomes of a dependent variable. I believe this is done using multinomial logistic regression. ...
22 views

### Why does the Youden rule does not recommend a threshold of 0.5 on balanced data?

Suppose I have a logistic regression model estimated using a balanced target (equal group sizes). My questions concern the optimal threshold for prediction and it's relationship with the Youden's rule ...
69 views

### FInding stationary points of Logistic regression with cross-entropy loss

Let's say that I want to find the stationary points of the Cross-Entropy Loss function when using a logistic regression The 1 D logistc function is given by : \label{eq2} \begin{split} ...
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### Can we estimate $R^2$ for logistic regression using only summary statistic of each predicting variable?

A toy example: We aim to predict the onset of stroke by body weight and age. We know that: 1-SD increment of weight increases the risk of stroke by 20% i.e. standardized coefficient of regression ...
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### Is there anything wrong with having a Bayesian logistic regression model with beta priors?

The Bayesian logistic regression model with beta priors seem to work using JAGS. I just can't find any examples of it in any literature or any tutorials. They all seem to use normal priors. Just want ...
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### No Goodness-of-Fit for Binary Responses (GLM)

In this book, p.334 (348 for pdf) it says you can model a binomial regression in a few ways: response as an observed proportion, with weights. e.g. ...
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### Reversing order of outcome variable - multinomial logistic regression

Here is a working example of my issue: I am trying to predict an outcome variable with three levels (e.g. underweight, normal weight, overweight) from a series of categorical variables (e.g. eats fast ...
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### Model Cause-Effect in Timeseries with Events

I am wondering what good ways to model cause/effect relationships in timeseries events are. My data consists of events with a timestamp. Some of those events are already known to be effects and some ...
18 views

### Softmax classifier with class priors

Softmax classifier is a discriminative model that directly models $p(Y|X, w)$ where $Y$ is the label for input $X$. We can write it as follows: p(y_i=k|x_i,w_k)=\frac{\exp \lbrace w_k^T x_i \rbrace}{...
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### Logistic generalized Additive Model (GAM)

How are the smoothers fitted in case of Logistic GAMS? For Gaussian response variable, many smoothers are defined such as splines and local regression etc. But how are they used in case of Logistic ...
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### Extremely basic question: how are data assumed to be generated in machine learning?

Given a dataset $\mathcal{D} = \{x_i\}, i = 1, \ldots, N, x_i \in \mathbb{R}$ In machine learning, what assumption is made as to how data are generated? I've seen two basic ideas circulating around, ...
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### Assumption logistic regression: linearity of independent variables and log odds?

I checked whether in my logistic regression models the assumption of linearity between the independent variables and the log odds is met. I used R and followed the instructions on this website to do ...
48 views

### (Repeated) Event Model - How to model entry?

I am modeling the entry of 30 firms into 25 industries over time. The unit of analysis are industries. I have cross-sectional panel data on the industries and know when a firm enters. I have 5 ...
40 views

### plot probabilities from mixed effect logistic regression with random intercept and fixed continuous and categorical covariate

I have created a mixed-effect logistic regression model with a random intercept, a ...
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### Logistic regression vs. negative binomial regression for the same type of data?

I'm asking this mainly out of curiosity, but few times I've come across data that could be modeled with either logistic or negative binomial regression. For example, there may be an experiment with a ...
229 views

### Whats the different between Logistic regression and perceptron?

In a binary classification problem, if both logistic regression and a single preceptron uses Sigmoid function, what's the difference in classification results, since they will have the same decision ...
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### Develop granularity-invariant criteria for comparison of logistic (binomial) models

I have a model with logistic (binomial) likelihood, with number of successes and failures as a response variable. I am comparing various models, which can be of different granularity. Different ...
74 views

### Matching biometrics with NHANES

Good morning everyone, I'm trying to figure out how to do some matching with NHANES datasets. Basically, I have a separate population of participants in a weight loss program, for which we do not ...
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### Interpreting Odds Ratio (in an Interaction)

I need advice on the correct interpretation of an odds ratio of an interaction term. Both the mixed-effect logistic regression output is below as well as the predicted odds values, which I calculate ...