Questions tagged [logistic]

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

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Any introductory paper, dealing with 'logistic regression on time series data'

Question Can you introduce me any academic paper dealing with "logistic regression on time series data"? The difficulty of the academic papers that I want is the introductory level for ...
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Is cross-validation (test) error below chance an indicator of overfitting?

I am training a binary classifier on some multidimensional problem. I have tried leave-one-out and k-fold cross-validation. I have tried L1 and L2 regularization, and I have produced plots sweeping ...
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Unexpectedly poor fit for logistic regression predicting connectivity between vertices in a graph

I have built a graph where each vertex has an associated time point and the edges between vertices are weighted by a pairwise distance measurement ("distance" is a small percentage, ...
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Running Logit Model on data and changing weights

I have created a logit model off of my data. There are two independent variables and dependent is 0/1. If I want to run my model off of a dataset I can create probabilities from the coefficients and ...
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RESET test for model misspecification for logistic regression

I am trying to replicate the analysis in Papke and Wooldridge (1996) in R as a way of learning about fractional response models. I've made it to page 628 where they run the RESET test for model ...
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One Hot Encode and Logistic Regression

When using Logistic Regression, and the categorical variables are one hot encoded, do we always have to drop a variable to avoid the dummy variable trap? If I recall it correctly, I have seen ...
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Logistic regression coefficient interpretation

There is one binary dependent variable (Winner/Loser) and there are three independent variables which are also categorical in nature: Age (Below 31, 31-40, 41-50, 51-60, 61 and above while retaining ...
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Ordered logit with independent variable only taking negative values

I have a continuous independent (explanatory) variable that takes on negative values only. How do I interpret a negative coefficient on this variable? The dependent variable is ordered as 1,2,3. Is it ...
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Generate binary classification data in python?

Is there a simple way to generate binary classification data in python? I'd like to specify $X$ input parameter, $[x_1,...,x_n]$, and generate a dataset such that the (overall) McFadden's pseudo $R^2$ ...
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Interpreting logistic mixed model estimates of a model with continuous and categorical predictors

Newbie here. Sorry in advance if I express poorly as I don't completely master yet the vocabulary of statistics! I am performing a logisctic mixed model - with glmer - which presents as follows: CE ~ ...
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Is my plot wrong? This is a plot of auc against lambda

I am trying to fit a logistic regression model using glmnet package. My data consists of 5 columns and 748 observations. I want to predict if blood donor will ...
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Interpreting glm() function with interaction effect

I have a dataset with 10 variables. Some are continuous, some binary. I'm trying to work out the interaction effect of 2 variables A (binary) and B (binary) on C (binary). I'm confused as to how I ...
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Model that shrinks a set of coefficients towards their common mean

I am interested in estimating the odds of a certain disease based on a medium sized group of correlated biological markers (roughly 20 markers). The model will also include several confounding ...
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What are some common prior/likelihood choices for Bayesian logistic regression?

I'm not really clear on the Bayesian approach to logistic regression. From everything I've read, the prior and likelihood can be can be whatever you want them to be. Well, I've a couple things; namely,...
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How would you interpret this Binomial Logit GLM? [duplicate]

I ran the binomial logit GLM which predicts whether a claim occurs in a policy or not. My estimated coefficients are as follows: Intercept: -2.68 Car Type (Saloon is base level) SUV: -0.07 Bus: 0.15 ...
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Pooling estimates from logistic regression; (how) can I do this?

I wanted to determine trends of plant species in a certain area over a certain period of time. I divided the area in square kilometers and ran a Bayesian Logistic Regression in R for each species. So, ...
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Can logistic regression be used to analyze sensitivity of a test over time?

I am working with a data sets to compare two clinical tests that yield either a positive result (1) or negative result (0). The clinical tests use EEG responses, so as the testing time increases, the ...
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Testing interactions in simulated data

I have some simulated data and wish to test for interactions. There are 500 predictors (0, 1 or 2) and a binary outcome variable. Predictor 101 and 424 are simulated to interact multiplicative. The ...
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Why is the sign of coefficient of the fitted logistic regression and fitted linear regression different?

I was using logistic regression to fit the diff-in-diff data (the original y is a dummy variable). However, the sign of the fitted function is contrary to what I expected. Based on the mean of y ...
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Packages in python for logistic regression on an unbalanced panel data [closed]

I am new to building models in Python, any help will be appreciated. I want to build a logistic regression model (with fixed/random/mixed effects) for an unbalanced panel data I have. The data I have ...
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Is this the correct hypothesis function for logistic regression?

I was reading a popular article on adversarial training. https://adversarial-ml-tutorial.org/linear_models/ It says, In this case, rather than use multi-class cross entropy loss, we’ll be adopting ...
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Very high standardized coefficient beta (binary logistic regression)

I am comparing the influence of eleven independend variables on one binary dependent variable. I decided to use the standardized coefficient beta for the comparsion because some of the variables use ...
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Appropriate application of Cook's Distance? [closed]

I'd like to know if applying Cook's Distance back to raw values used in the linear model makes sense in anyway. How exactly are these values related if at all? Here's what I'm working with: You can ...
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Do fixed effects models work on non-panel data?

I'm working with a logit model that contains the following variables: Dependent Variables: Self-identification in the left-right political spectrum (dummy, 1 = left / 0 = other) Independent ...
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Stratum specific estimates in a model with an interaction term

Lets say I have a logistic regression model predicting the log odds of mild cognitive impairment (MCI) and my exposures of interest are age, education and carbohydrate intake. I expect that the ...
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Simulate data for multilevel & multivariate logistic regression

I want to simulate data for a multilevel logistic regression with several independent variables. I tried doing this with the steps of >>Arnold, B. F., Hogan, D. R., Colford, J. M., & Hubbard,...
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How should two cross-validated logistic regression models be compared?

I'm using 100 times 10-fold repeated cross-validation to assess the ROC-AUC performance improvement of adding a biomarker to an existing model: Model_A : pred1 + pred2 Model_B :pred1 + pred2 + pred3 I'...
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Finding the interaction terms in Logistic Regression with 4 ind. variables (11! different ways of choosing int. terms)

When doing logistic regression with 4 independent variables, it is believed there will be significant interaction effects, and the strongest interaction will probably be when 3 or 4 of the variables ...
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Are the outcome and predictor variables in a logistic/linear regression interchangeable?

Consider the following example. I am studying the mutation burden across three subtypes of cancer. In my dataset, I have individuals without cancer (controls) and individuals with cancer (cases); the ...
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log-odds and it's standard error as priors in logistic regression

I'm attempting to complete a Bayesian logistic regression with the outcome of whether or not a crash occurred. I have various covariates in my model that are widely used to predict crash occurrence. ...
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Multivariate GLM in R

I have two dependent variables (Y1 and Y2); they are both binary. And I have an independent variable. Y1 and Y2 are correlated (Y1 refers to whether an infant is premature or not, and Y2 refers to ...
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How to perform post-hoc with logistic regression in SPSS? (Two dichotomous IVs)

I performed a logistic regression in SPSS using two IVs (both dichotomous) and found a significant interaction effect. Now I want to understand where the differences come from. ⠀⠀⠀⠀⠀⠀ V1_a⠀⠀⠀⠀V1_b ...
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Hyper-plane in logistic regression vs linear regression for same number of features

Geometric interpretation of Logistic Regression and Linear regression is considered here. I was going through Logistic regression and Linear regression. In the optimization equation of both following ...
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Can GLMM be used with Case-Control data?

My initial hunch is no, since in case control data (assuming $y_i$ is a binary response, i.e. = 1 for case, 0 for control), we match a control (or several) per case. Meaning the data is very much ...
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Can I use logistic regressions and least squares coefficients in a meta-analysis?

I am trying to write a Economics meta-analysis. The papers that I have collected so far contain a 50/50 split between OLS models and Logistic regressions (coefficients reported as odds ratios). If we ...
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How to apply the uniform shrinkage factor to the logistic regression to get the updated coefficients and intecept in R?

Hope to ask a bit about uniform shrinkage factor in updating the coefficients and intercept of prediction model: I have built up a prediction model with "rms" and got the uniform (global) ...
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Selecting Correct Statistical Methodology

I am designing a predictive model, and I am unsure of how to group the data from individuals companies, or whether I even need to group that data, and it's valid to treat each row as an independent ...
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Logistic Regression on Non-linear Boundary [duplicate]

How should we expect logistic regression to perform on a dataset of 2 classes separated by a non-linear decision boundary like the unit circle? My understanding is that accuracy will most likely be ...
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Two stage model - first stage logit and second stage OLS

I would like to run a two stage model where I estimate a logit regression to estimate the likelihood of an event happening followed by a conditional OLS - where the condition is - provided the event ...
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R - Logistic regression: how to prepare data [closed]

I've been doing a lot of googling on logistic regression but I've been getting confused more and more so please help me out. The data set I have The outcomes of interest (dependent variables) are Are ...
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Logistic Regression, continuous feature is categorical

I'm using logistic regression for a simple binary classification. I have a feature, x, and looks something like this ...
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Danger of choosing multinomial logit instead of ordinal logit

(I feel like if you're active here, you've come across my problem before because I've been asking a lot...) I want to run a regression, in the area of credit risk in loans, to predict the outcome of a ...
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Correct regression model for independent variable limited 0-100

So I'm having some questions about a regression model I'm trying to fit The dependent variable is a continuous interval scaled index reaching from 0 to 100. It's severely left-skewed and most ...
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Interpreting logistic regression coefficients for a categorical variable

I got these results from a logistic regression in R. The data are the proportion of women elected in Uk elections, according to their party. As you can see, I used ...
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glmertree to fit logistic regression with two-column y

With both glm and glmer, if I wanted to fit a proportion, I could do it as either: ...
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What kind of analysis can I make in order to understand which variable impact the most my result?

Here's the thing, I have data from my products in a dataset just like this: ...
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Using Offset in Binomial/Logit GLM for Exposure Years? [duplicate]

I am building a GLM Model that predicts whether there will be a claim in a certain policy or not. So target variable is either 0 or 1, so my choice of GLM was Binomial, and link function was Logit. In ...
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Overdispersion in logistic model

I'm relatively a newbie in R, and I've been trying to make a silly example of logistic regression to predict, according to Age and Sex whether someone dies of corona or not. I'm from Colombia, so my ...
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Wrong sign in regression coefficient?

I have been getting these extremely puzzling results in my logistic regression model. "New.Regs" is a dummy variable indicating whether or not an observation came after a certain law was ...

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