Questions tagged [logistic]

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

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Odds ratio interpretation in logistic ordinal regression

In my model I have my response/dependent variable (which is ordinal) and I wanted to explore whether a continuous predictor variable was associated with it, so I used ordinal logistic regression. ...
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Optimal cutpoints using {cutpointr} gives different number of observations [closed]

I have a binary outcome, Survival_status_bin2Y and would like to obtain the optimal cutpoint for a continuous variable, NLR. I ...
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Difference-in-Difference with Logistic Regression, how to add mutliple fixed effects?

I'm using R and running a Difference-in-difference (DID) regression with unbalanced panel data. Since my dependent variable is a dummy variable (Government ...
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Logistic regression for observations on a monthly grid - impact of overlapping information of a given customer

My question is based on the usual setting in credit scoring. Assume we have historical monthly observations of customers, their risk factors $R_{i,t}$ and the flag whether they are currently in ...
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R: Logistic Regression Error - Algorithm did not converge + High P Values, how to fix? [duplicate]

I am building a logistic regression with Churn as the dependent variable. I cleaned my data and transformed the categorical data to factors. This is the description of the data after updating the ...
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Nomogram function from the RMSpackage in R [closed]

I am currently using the nomogram function from the RMS package in R. However, I don't succeed in doing these two things: 1.) How can I rename breaks. For example, I have the variable sex as factor (0,...
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Election Predict Using Machine Learning

I want to predict the election results in a country. Firstly I want to check and specify probabilty. For doing this, I intend to use the election results of the past years and the estimation results ...
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How to assess phylogenetic signal in generalised linear model (alpha in phyloglm)

I'm running a binomial logistic regression using phyloglm in R. I want to know how much phylogenetic signal there is in the traits I'm testing. I think the value 'alpha' in the output is giving me ...
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Model validity for Ordinal logistic model

I am doing a study using OLR. The model tries to assess the satisfaction of ground level stakeholders (scale of 1(extremely dissatisfied) to 5(highly satisfied) in an urban area. The independent ...
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Cluster standard errors on experiment group?

I am running a very simple experiment. There are two different experiment groups, participants are randomly assigned. They have to make a simple binary decision in the experiment. I have three control ...
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Could we explain the disadvantage of imbalanced data mathematically?

Simple setup: observed response is binary (yes/no, 0/1, positive/negative). use logistic regression to model the probability of the response being, say, 1: $P(Y=1|X)$. the MLE of the model ...
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Binomial glmm with a categorical variable including zero cell [duplicate]

I am analyzing the data using generalized linear mixed-effect models (GLMM) using the lme4 software package (Version 1.1-30 in R; Bates, Maechler, Bolker, & Walker, 2022). The model includes 2 ...
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Logit space bias adjustment equivalent for multinomial logistic regression

Imagine we have a 2 class logistic regression: $ P(Y=1) = \sigma(\beta x) $. Let us also say that we think that our logistic regression has some bias in the logit space, i.e. we think that rather than ...
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Is it acceptable to create a dummy variable out of a quantitative variable?

I have a variable that takes the value of 5% or 10% throughout the data set. Is it okay to transform this variable into a dummy variable such that 10% (high) = 1 and 5% (low) = 0. I am running a ...
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Poisson regression with time dependent covariates

I am an epidemiologist and recently our team receive a data from nursing homes in our city. We have weekly data for each elderly person for about 3 years during their stay in nursing homes. The ...
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How to determine if the log likelihood of logistic regression is too large or not?

I am running a logistic regression on STATA with binary response variable, and 2 predictor variable that are discrete, as such one is in % (but takes only 2 values strictly i.e., 5% or 10%) and ...
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Simulated data for logistic regression

I used the code below to create the random variable x1 and binary variable y, and fit the regression with y and x1. My questions are: Why regression coefficient estimates are not close to 2 and 10 (...
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I want to feed the results of a clustering into a logistic regression

Basically, my problem is, I have a dataset where I know about 12% of the rows should be classified as something, and I have some reasonable predictors. The problem is, my predictors aren't too good, ...
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What happens if we change the threshold probability value for classifying into different class? [duplicate]

Suppose, I classify something as 1 when predicted probability of that event is greater than 0.5 (referred as threshold, henceforth) and 0 when predicted probability of that event is less than 0.5. ...
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Interpretation of significant predictors in logistic regression

I am approaching an exercise about data analysis, but I have some doubts about interpreting my results. I have $p$ predictors, some categorical, others continuous (let's call them $X_1$, $X_2$, $\dots$...
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Very different sizes of parameter estimates in lmer vs glmer (binomial) versions of “same” model (R)

In a 2-level glmer analysis the assumptions did not hold, so I created a binary outcome variable instead and run the same model setup on that (most Y values were 0’s and 1’s originally). With regards ...
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Statistical test recommendation for efficacy of three different drugs with categorical responses

I have a really small study sample of 70, in which they are being medicated with 3 different drugs (A,B,C). The study aimed to determine the efficacy of each drug in treating the disease and the ...
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What type of regression to use to compare continuous and categorical independent variable with categorical dependent variable? [closed]

I am working on a bank marketing data set. I have 17 independent variables which are both continuous and discreet. But my dependent variable is Categorical? What is the best method that I can use to ...
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Logistic regression(with Markov chain) on time series data?

I'm working with a biotech device's time series data to predict the replacement amount. The background is the battery of the device will die after the implant for a few years, and the battery will be ...
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Logistic regression: What are use cases for logistic regressions where $n \neq 1$, i.e., $n >1$? [duplicate]

NOTE: This question relates to Binomial logistic regression. Thus, the $n$ in the title, refers to the parameter of the Binomial distribution. Most real-world use cases of logistic regression ...
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Why does the logistic model for binary logistic regression return the probability that the outcome was in class/category 1?

In the context of simple binary logistic regression (https://en.wikipedia.org/wiki/Logistic_regression) we have $p(x)=\frac{1}{ 1 + e^{\beta x}}$, where $p(x)$ is interpreted as the probability that ...
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Weighting Ratio Data?

I am conducting an Interrupted Time Series Analysis on ratio data (number of applications refused/total number of applications). Data is modelled using a binomial logit regression (see below): ...
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GridSearchCV returns unrealistic AUC score with Logistic Regression

Long time lurker but I've just created an account because its the first time one of my questions has not actually been answered. I'm currently struggling with optimizing the hyperparameters of a ...
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Johnson-Neyman plots for glmer models (logistic, mixed effects) in R against non-zero values

Note: this is a different question from the one I asked here, but I'm using the same example model. I have an R glmer (logisitc mixed-effects) model that looks ...
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Which is the likelihood function of the logit model? [duplicate]

I'm wondering which is the likelihood function for a logit model and how I can derive it. Thanks!
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Coefficients of dummy variables in a logistic regression [duplicate]

I wanted to know what is the difference between running a multinomial logit regression and a logit regression on a model in which the dependent variable is a dummy with just two levels. My database ...
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Interpretation of logistic regression results

I have a database that looks like this ...
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How to jointly model a binary outcome with an associated confidence rating using R?

I have data of the form: judgment confidence variable A 0.4 2 A 0.7 1 A 0.8 5 B 0.2 4 B 0.6 6 B 0.1 8 Outcomes: A dichotomous variable (binary judgment) A confidence score associated with the ...
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Two-Stage Residual Inclusion with Binary Treatment, Instrument, and Outcome

I'm attempting to conduct an instrumental variable analysis using the two-stage residual inclusion method. The outcome, instrument, and main treatment of interest are all binary. There are also a ...
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Marginal effects of exposure variable in logistic regression with matched dataset

I have a question related to the estimation of effects of a certain binary exposure variable on a binary outcome via logistic regression after an exact matching procedure. Originally, I followed ...
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Logistic GLM vs GLMM diagnostic issues

Problem I am running through the diagnostics of two logistic regressions and two equivalent GLMMs with their only differences being crossed random effects (intercepts only). The output for the ...
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Derivation of factors associated with increase in HIV DNA

I would just like to verify a statement made in the following paper: Peripheral blood HIV-1 DNA dynamics in antiretroviral-treated HIV/HCV co-infected patients receiving directly-acting antivirals The ...
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Johnson-Neyman plots for glmer models (logistic, mixed effects) in R

I have an R glmer (logisitc mixed-effects) model that looks something like: ...
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Can I combine dichotomous and continuous outcomes into a single regression model?

I am doing analysis on an educational product that aims to predict what impacts whether or not a student gets a question correct or incorrect. The DV includes item scores from four different question ...
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Coding the likelihood function for logistic regression

I would appreciate help in understanding if I made a correct interpretation and coding of the likelihood function for logistic regression. Background: For a task I am going to write a function in <...
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Logit transformation of target values in regression

What sense would it make to logit transform a target variable that is a rate of something in a time series - Log(rate/1-rate). Does such a transformation have a theorethical purpose?
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Would there be any alternatives to a Logistic Regression or way to modify the Regression for what I'm looking for?

To provide more information I am looking for an alternative to logistic Regression or a way to modify it. This is because of two reasons: My data is widely dispersed across the X axis for both my 1s ...
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Dependent Variable takes on the values 0, 1, 2, 3 - What is the right (logistic) regression model to use?

I am looking for help to analyze the data from my online experiment. For my master thesis I conducted an online experiment where participants had to conduct a shopping task where they were provided ...
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The results from 2 programs are conflicting on convergence issues in my multivariate logistic regression, how do I deal with this?

Currently I am analyzing a dataset using logistic regression, I ran it in R using the glm function to run a multivariate logistic regression with 12 predictors. Some of these are quite collinear as ...
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Calibrarion curve of a logistic Regression model

I have a high imbalanced dataset and I fitted a logistic regression model on it. The calibration curve is: As you can see there is poor calibration after 50. Is the model bad or the problem is the ...
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Resampling to handle class imbalance in logistic regression [duplicate]

I was wondering if anyone could help me understand resampling for class imbalance. From what I have learned, class imbalance is usually a small data problem where the less prevalent class usually ...
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1 answer
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Why doesn't adding additional explanatory variables in a logistic regression model decrease our primary explanatory variables variance?

Imagine a clinical trial setting where we have binary outcome Y and we are interested in the effects of treatment X. Lets say we also have additional explanatory covariates Z and W. Thus our ...
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Effect estimation after exact matching in MatchIt

I am performing exact matching on a set of continuous and categorical covariates. Once the matched (via MatchIt) is performed, I use logistic regression to estimate the effect of my treatment variable ...
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Is the Hosmer-Lemeshow test appropriate for logistic GLMMs?

I have read a bit on the Hosmer-Lemeshow test as a goodness of fit measure in logistic regression, though I have read that it is quite flawed in terms of power, effects in choice of g, and issues with ...
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Obtain Characteristics of Feature Importance?

I'm working on a classification problem, predicting bank loan defaults. I have fit a logistic regression model to the data and obtained the coefficients like so: ...
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