# Questions tagged [logistic]

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

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### "LinAlgError: Singular matrix" when using statsmodels Logistic Regression [closed]

I am trying to use a Logistic Regression model to predict the Disease from the Symptoms using this dataset: https://www.kaggle.com/datasets/rabisingh/symptom-checker?select=Training.csv I am focusing ...
52 views

### Is it possible to adjust a logistic regression model when the false positive rate is too high for observations belonging to a specific category?

This is a hypothetical scenario for self-learning purposes (not homework), so not a lot of additional details to give than what I mention below. Let's say I have a binary logistic regression model, ...
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### Strange interaction term estimate in a logistic regression with a large class imbalance between exposure groups. How to interpret?

EDIT 2 In reply to one of the commenters, here is the 2x2x2 table. Y = 1 : Y = 0. X = 1 X = 0 M = 1 9 : 73 3 : 29 M = 0 34 : 245 1,214 : 21,204 EDIT 1 In my attempts to make things simpler when ...
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### Obtaining Marginal Forecasts

I am trying to make predictions on a dummy variable. What I am predicting is whether or not a separate variable ever changes from a zero to a 1 in a year from the observation date. The dummy variable ...
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### What maximum value of AUC optimism could still be allowed to confirm that logistic regression model does not overfit?

I am not sure how to define that a statistical model does not overfit based on a difference between bootstrapped AUC and AUC calculated on all training data. In the literature I saw 2 approches. The ...
15 views

### Is it right to call the values produced by emmeans coefficicents?

I have a logistic regression model with a categorical predictor with five levels. I compute emmeans for the model, splitting by my categorical predictor. ...
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### Is my regularized logistic regression model overfit?

I have a dataset with the following characteristics: moderate sample size (~300 samples) moderate class imbalance (~20% positives) high-dimensional (the number of independent variables, again ~300, ...
244 views

### Is G*Power reliable for logistic regression? It does not seem to account for Hauck-Donner

I've just been introduced to G*Power. The only option I could find for analysing logistic regression is described as: Options: Large sample z-Test, Demidenko (2007) with var corr That seems to ...
1 vote
49 views

### Alternative test instead of logistic regression for binary dependent outcome variables?

I have a dataset of patients who underwent an operation, and I collected information on post-surgery complications such as necrosis (binary outcome variable). Now, I would like to investigate whether ...
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### Evaluating changes in between-individual variation in time series data

I'm working on evaluating an intervention using an interrupted time series approach, and one of our hypotheses involves evaluating its effect on between-individual variation. I'm using ...
26 views

### How to linearize logistics function?

The function is $y=L/(1+e^{(-kx)} )$. After research I found this equation to linearize it, replace y values by this: $\ln(1/(y/(L-1)))$ , then keep x values the same and plot it. But with further ...
1 vote
27 views

### Relative Risk or Odds ratio using machine learning

I am thinking of using machine learning type classification models to compare them with the traditional approach of logistic regression (dichotomous outcome) in a sample of patients with diabetic foot ...
24 views

### "This parameter is redundant" - SPSS Binary Logistic mixed model

I know there is a question that asked about a similar warning, but that user's "error" had to do with dummy coding while I think my problem has to be with statistical power and understanding ...
16 views

### Second order cross-partial derivative for a binomial logistic regression in R [closed]

I have this following code in Stata: ...
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### Psuedo-"Odds ratio" for multiple columns

I have a dataset with a categorical target ($y$) and multiple categorical features ($x_1$, $x_2$, ..., $x_i$). I have been able to successfully use a logistic regression model to calculate an odds ...
25 views

### Sklearn feature selection performs strangely with 2 groups (and with SVC)

Previously I've successfully performed support vector classification with recursive feature elimination in R using the e1071 package, but I'm now hoping to move over to SciKit Learn given that Python ...
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### Interpretation of an interaction effect (ratio of odds ratios) when using effect coding

I ran a multilevel logistic regression model using function glmer from R package lme4. All of my predictors are binary and I have used effect coding, i.e., coding -...
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### Why shouldn't I run a logistic regression with dependent vars between 0 and 1?

I'm trying to predict the probability of an individual progressing all the way through a series of tasks. I have participants, they participate in Task 1, if they succeed, they move to Task 2, if they ...
19 views

### VPC for a three-level logistic regression

I am building a mixed effects logistic regression model to explore whether or not someone is diagnosed late with a specific infectious disease. My outcome is late diagnosis (yes/no). My data includes ...
192 views

### Binary logistic regression results interpretation when one IV is ordinal [closed]

I don't know how to interpret the ordinal variable 'Stress' in my binary logistic regression analysis.'Stress' was measured on a 10 point scale where 1 is 'Least stressed' and 10 is 'Most stressed'. ...
33 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 ...
17 views

### Logit model for panel data with fixed effect [r]

I'd like to estimate the factors that determine the development of heating networks in French municipalities. To do this, I use various variables (population density, age of dwelling, ideology of the ...
1 vote
65 views

### Strange interpretation of odds ratio from logistic regression

I am involved in writing a manuscript applying logistic regression to estimate rates of seafood mislabelling. The model (fitted using glm() with the default logit ...
32 views

### Logistic regression odds vs Survival analysis odds

Why do I get significantly different answers from the logistic regression and survival analyses? How can I fix this code? Logistic regression: ...
1 vote
19 views

### Automated Code for Logistic Regression [closed]

My Y variable (output) is binary (0 or 1). I have 10 input variables in total, 3 of them are scaled variable, 2 of them are ordinal number therefore being written with C( ). Rather than running the ...
1 vote
75 views

### Interpreting Logistic Regression with categorical variable

Please help! I am using binary logistic regression to model the probability of nesting in 5 different habitat types, with 1 = nest presence and 0 = random point. I have 5 different habitat types and ...
1 vote
48 views

### Is this the right equation format for a logistic regression?

I was reading a paper and the authors wrote the equation for a logistic regression like this: Pr(yf = 1|X,C) = P(β1Xf + β2Cf + σs + ρr +  f sr > 0) Is this a typical way of writing a logit ...
37 views

### Implications of very low but statistically significant average marginal effects

I built a multivariate logistic regression model, which is largely a replication of a published paper (I just some different data). My regression table (with the coefficient reported as log odds) ...
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### Imbalanced classes and possible ways to increase precision, recall and f1-score of the prediction model

I've just started my data science internship, and this is my first time in the field. I'm sure I'll face challenges in the future where I might need your help. It's also my first time asking a ...
77 views

### Difference between Probability and Effects in Logit Models

when I run a logistic model I get log odds that I can easily convert to probabilities. What I don't understand is how can I use percentages instead? Here's the code: ...
1 vote
32 views

### Importance of goodness of fit in Hypothesis testing

I am struggling with one question. Is goodness of fit of a model necessary when your purpose is to test hypothesis regarding a coefficient? To be specific, I am regressing formal credit access on ...
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### Help with question comparing logistic regression analyses

I have accounted a problem when trying to finish my analyses. So, I want to compare the beta weights between two logistic regression analyses from independent samples (same IV and DV in both ...
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### Do predictors in logistic regression need to be stationary?

For linear regression with time series predictors, it is widely accepted that both dependent and independent variables must be stationary. The reason is that we need to assume that the errors are ...
1 vote
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### Does marginal effects change depending on the size and heterogeneity of the population?

I am trying to predict the probability of receiving treatment using a logit regression. I have two regressions with the same explanatory variables: Regression 1: I predict the probability of ...
1 vote
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### The "detectseparation" package. How to interpret its results?

I am running a logistic regression on financial data of several companies. The dependent variable is the company to be a smoother (binary variable: 0, 1), and there are several independent variables: ...
1 vote
130 views

### Would ordinal logistic regression be appropriate in this case?

I have 2 independent variables with 2 categories each: 'gender' (male, female) and 'relationship status' (married, single), and one DV: 'emotional impact' measured on a 10 point scale ranging from 1 (...
51 views

### Analysis of a case-control study using ordinal logistic regression

Suppose we have data from a case-control study where for each case having had some disease or event $Y_{binary}$ a control was included that was free of $Y_{binary}$. Due to this study design we ...