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Questions tagged [logistic]

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

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Is a logistic regression appropriate for my question and correctly interpreted?

I need help knowing if my statistical approach is correct for what I want to achieve. I want to know whether a trial that follows an error (i.e., has a post.error value of 1) makes it more likely that ...
jbrimm2004's user avatar
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Should I Use Regularization in Univariate Logistic Regression for Diagnostic Methods Comparison?

I am comparing two diagnostic methods, Method 1 and Method 2, where Method 2 is considered the gold standard. I am using Method 1 to predict the Method 2 using logistic regression. My dataset contains ...
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Rescale measures of association for meta-analysis (e.g., log-transformed independent variables)

I am carrying out a meta-analysis of studies evaluating the association between blood levels of specific environmental pollutants and health outcomes (binary). Some studies reported OR/RR/HR for ...
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Need help understanding odds ratio over time example

I'm trying to recreate a paper that compares the frequency and characteristics of emergency department visits that are repeats (ie; same patient had another emergency department visit for the same ...
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Bayesian Mediation Analysis

I have: 1 binary outcome (0, 1) 1 continuous quantitative mediator 1 continuous quantitative predictor I would like to compute Bayesian mediation analysis with Liu et al. (2023) method. The formula ...
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How to choose default uninformative prior in the R Package BAS

I'm conducting a Bayesian multilevel logistic regression based on the Rpackage BAS. I'm a beginner in Bayesian statistics. But in bas.glm, I don't understand and I don't know how to specify my prior. ...
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Compare effect of two coefficients in logit model

I have a logit model with multiple independents qualitatives variables (A, B, C), and I would like to compare the probability of success between individuals who have a certain profile. For instance, ...
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Bayesian Logistic Regression: default uninformative priors choice on JASP [closed]

I'm currently trying to perform Bayesian logistic regression using JASP. For this, I need to choose a prior distribution. JASP offers the following options: AIC, BIC, EB-local, g-prior, CCH, Beta-...
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Compare the proportion of multiple diseases between 2 groups

I'm conducting an analysis on data derived from two groups subjected to different environmental conditions. Here's a brief overview: Group A: 750 individuals exposed to smoke. Group B: 1500 ...
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How to perform model comparison based on multinom( ) function of nnet package in R? [duplicate]

My independent variables are gender and sequence, and the dependent variable is intervention (including 3 intervention methods). I established a multinomial logistic regression model to examine the ...
zhang xia's user avatar
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How to perform model comparison based on multinom( ) function of nnet package in R?

My independent variables are gender and sequence, and the dependent variable is intervention (including 3 intervention methods). I established a multinomial logistic regression model to examine the ...
zhang xia's user avatar
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Why residual term $\epsilon$ is not included in logistic regression specification? [duplicate]

I have a simple question, which bothers me. In the logistic regression context, the odds are defined as: $$\frac{p(X)}{1-p(X)} = e^{\beta_{0}+\beta_{1}X}.$$ I was wondering, why in the literature the ...
Sane's user avatar
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Regression with dependent observations of only one individual

Last week, I received a task to plan an analysis that my team wishes to perform. My objective is to measure if one physician agrees with the outputs that a certain tool generates for a set of N ...
kKodorna's user avatar
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Conditional Logistic (Discrete Cox PH) Regression Model

I am very new on the topic of disc påret time survival modeling. I found the following function in R from package powerSurvEpi. It seems that powerConLogistic.bin function can be used for #Sample Size ...
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Can I use Multinomial Logistic Regression's probabilities as proxies for proportions?

Summary of the Problem: I am exploring methods to simultaneously predict the proportions of different tree species within 250 square meter forest plots using ALS (Airborne Laser Scanning) and spectral ...
candelas762's user avatar
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What are the `estimates` returned by `avg_slopes()` in modelsummary?

I have an interpretation question of R's marginaleffects avg_slopes function for logistic regression models. Consider the ...
spindoctor's user avatar
1 vote
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Association between more than 2 categorical variables

Is there a method that can detect an association between several categorical variables? I know that chi2 test Can help me with paired variables, but imagine the usecase with 5 variables and there IS ...
curious's user avatar
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Regression strategies for predicting a binomially distributed, count outcome: Poisson, Negative Binomial, and Logistic Models with Offsets

Data Description: I am working with a dataset of 100 hens, represented across four columns: ID: Numbers 1 through 100. Age: Each hen's age. EggCount: Number of eggs laid per hen, with a range from 0 ...
insan's user avatar
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Feature selection for logistic regression and random forest (using Orange - no coding)

I’m using Orange to create a prediction model for the Indian liver patient dataset (binary target variable – either has or does not have liver disease – with 580 instances and 10 features). I’m using ...
Jess's user avatar
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1 answer
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How to determine probabilities that maximize likelihood in logistic regression in case of categorical variable [closed]

Edit: Let's say that we want to predict if mouse is Obese (Y=1) vs NotObese (Y=0) given that the predictor is the fact that a mouse has a normal Gene (X=0) vs Mutated Gene (X=1). I can deal with this ...
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1 answer
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Lack of within-cluster variability

I am working on patients' data. I want to do multilevel logistic regression. The cluster is hospital, exposure variable is treatment (A, B, C), and independent variables include sex, age and others. I ...
W Ramadi's user avatar
3 votes
1 answer
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Extrapolating standard error of logistic regression in R

I'm trying to extrapolate the mean and standard error range of a logistic regression using the predict function in R, splitting the x axis range up into small pieces and predicting the value at each ...
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1 answer
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Do the threshold values in the results of Ordinal Logistic Regression need to be strictly increasing?

I understand that the estimates of the thresholds should be strictly increasing from here and this youtube lecture. This is because they represent the thresholds that determine which output class the ...
jojorabbit's user avatar
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Negative average marginal effect for positive estimate in ordinal logistic regression

I'm running an ordinal logistic regression with eight indepdent variables and the dependent variable has five categories (1 = Not at all and 5 = To a great extent). To interpret the coefficient ...
silje's user avatar
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1 answer
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What changes in swapping predictor and outcome variables in logistic regression

I have a dataset containing a variable representing the source of isolation of a bacterium, with 2 factors, along with multiple other binary variables indicating whether the bacterium is resistant to ...
user416509's user avatar
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Wanting to create a cut-off point for measurement (Length by width) at which an adverse outcome occurs

I am working on a project investigating dimensions of tears in shoulders and how it affects retear rate after an operation. From the literature, age, and tear size (Dimensions AP [width], ML [length], ...
Atham's user avatar
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3 votes
0 answers
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How to identify the most important features that impact an ordinal score?

I have 40 rows of 5 continuous features and 1 ordinal score. What statistical technique is recommended for me to identify which features have the highest impact on the ordinal score? I have looked ...
joran.g's user avatar
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2 votes
1 answer
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Sample Size for Logistic Regression

I'm carrying out multiple logistic regression with three independent categorical variables each with more than two categories per independent variable. I want to use the EPV (events per variable) ...
Laura's user avatar
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1 vote
1 answer
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discrete time model and Logistic regression

To analyse discrete time cox PH (including time varying covariates), the following R function can be used: glm (family = binomial, link = "cloglog") Since there is no open formula for ...
Stat2024's user avatar
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1 answer
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Sample size for multivariate logistic regression (not using rule of thumb)

1. I tried numerous software packages, including PASS, but it appears that they can only be used when the model contains a single variable. So I was wondering if there was a function (mostly in R) or ...
Stat2024's user avatar
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Discrete-time hazard model vs. conditional logistic regression vs. logistic regression

I was wondering what is the difference between these three models (discrete time cox proportional hazard, conditional logistic regression and logistic regression). I would appreciate it, if you could ...
user413503's user avatar
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Need of complex sample analysis for a stratified random sample with clusters

I presented the baseline findings of our cluster-randomised RCT in a cross-sectional paper. The cross-sectional study used stratified random sampling design with clusters as sampling unit. There were ...
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derivative of Logistic Regression with sigmoid func [duplicate]

I am having difficulty figuring out, why I get different answer from the professor. we are tasked with finding the deriative of the logistic regression cost function with the sigmoid function: $$L(w│D)...
Ofek nourian's user avatar
2 votes
0 answers
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derivative of Logistic Regression (sigmoid) [closed]

I am having difficulty figuring out, why I get different answer from the professor. we are tasked with finding the deriative of the logistic regression cost function with the sigmoid function: $$ L(w│...
Ofek nourian's user avatar
1 vote
1 answer
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Comparing odds ratios on same people but from different models

I have run two logistic regression models (two different versions of handling missing data( using the same sample and using the same predictors. I want to compare whether or not the odds ratios for ...
Jordank's user avatar
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6 votes
2 answers
263 views

Count predictor and binary outcome

Is a binary logistic regression the best approach when I have a count predictor and a binary outcome? Can I apply a multiple binary logistic regression model if I have more than 1 predictor that is a ...
stephan_phd's user avatar
1 vote
1 answer
35 views

Interpretation of average marginal effect logistic regression model [duplicate]

I am currently writing a master thesis on the relationship between the unemployment rate (measured in percentage points) and first birth hazards (i.e. the probability of having a first child) using ...
Flap's user avatar
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1 vote
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logit model - labor probability(odds ratio) [duplicate]

The logit model is given: $$ \text{Labor probability} = \alpha + \beta_1 \cdot \text{income} + \beta_2 \cdot \text{age} + \beta_3 \cdot \text{education} + \beta_4 \cdot \text{young kids} + \beta_5 \...
silvia's user avatar
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1 vote
0 answers
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Violated assumption of independence in logistic regression

In order to predict forest fires occurrence, some studies (study 1,study 2)used meteorological data plus vegetation and topographical data. I'm trying to do the same for a different location but I'm ...
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Panel Data logistic regression

I am working with a panel dataset that describes company code as an id variable and fiscal year as a time variable (1500 firms from 2013-2022). The dependent variable is binary. First I checked for ...
Lou's user avatar
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Are diagnostic tests and clinical (risk) prediction models in medicine essentially the same thing?

In medicine, are diagnostic tests (e.g. covid test, HIV test, ...) and risk prediction models essentially the same thing? If not, in which aspects do they differ (from statistical point of view)? ...
sitems's user avatar
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4 votes
1 answer
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Comparing Firth's logistic and traditional logistic by AIC

My data has rare events so I decided to develop a Firth's penalized logistic regression using logistf package. I also want to apply a traditional ML logistic ...
AmirMohammad's user avatar
3 votes
1 answer
38 views

Taking into account a non-symmetric loss function in a classification problem

Consider a binary classification method that estimates the class probability and where the observation weights can be specified (e.g. Logistic Regression). To accommodate the difference losses from TP ...
James's user avatar
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2 votes
1 answer
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Difference between regression methods

When to use logistic regression and when to use beta regression in statistical modeling for given data? How do know the difference between them? And when can I fit just a linear regression and not ...
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0 answers
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How to fit a binomial model with repeated observations per subject

I have a small dataset for 100 participants. The dataset includes repeated 'tests' over a course of a week. A test can have the binary outcome of pass or fail, and the same number of tests are not ...
snalmznh's user avatar
2 votes
1 answer
66 views

VIF/GVIF for binary logistic regression

How do I decide if there is multicollinearity or not in my logistic regression? Specifically, the GVIF OR GVIF^(1/2*Df). How ...
Diyan Milla Hanifah's user avatar
2 votes
1 answer
49 views

What is the difference between using logistf and brglm2 when dealing with complete separation in a logistic regression?

I am trying to looking at how the three factors A (5 levels, a-e), B (2 levels, a and b) and C (2 levels, a and b) affect the likelihood of event Y (1 = occured, 0 = did not occur). I initially ran a ...
Insect_biologist's user avatar
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0 answers
16 views

Logit model not predicting any values < 0 despite class imbalance

I am building a logistic regression model to identify potential channelling factors that predict whether a patient will initiate of one of two antidiabetic drug classes at a specific stage in their ...
jos0909's user avatar
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0 answers
39 views

R throws deficiency warning when running a logistic regression (LMM)

I have never run a logistic regression analysis (linear mixed-effects model) in R, but it seems to be a reasonable approach to answer the question as to what extent condition BB affects the ...
user avatar
3 votes
1 answer
65 views

Multiple logistic regression with ordinal predictors

I'm looking for resources on general guidance for how to perform and interpret multiple logistic regression using SPSS, with ordinal predictors. I have 2 ordinal predictor variable. Each ordinal ...
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