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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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7 votes
1 answer
2k views

Geometric Interpretation of Softmax Regression

I'm writing a series of blog posts on the basics of machine learning, just for fun, mostly to validate my understanding of Andrew Ng's class. As I'm currently studying generalized linear models (GLMs),...
0 votes
1 answer
26 views

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 ...
5 votes
3 answers
19k views

Logistic Regression on Time Series Data

I would like to forecast the probability of a binary outcome using logistic regression at t+1, using all previous data points. I am new to forecasting so any help would be appreciated. The raw data ...
2 votes
3 answers
344 views

Standardized coefficients logistic Regression R

Is there an R analogue to the standardized logistic regression coefficients I can get in Stata? I know in regression it is simply lm.beta(model). Is there something like this for logistic regression ...
2 votes
2 answers
257 views

Deriving predicted probabilities from gologit2 (proportional odds models) output

I am trying to understand the output from Richard Williams's amazing gologit2 STATA package. The software is used for ordinal logistic regression and circumvents violations of the proportional odds ...
0 votes
1 answer
23 views

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 ...
1 vote
1 answer
573 views

Data setup: Attrition/Churn Modeling with Time Dependencies

Beginner Data Scientist here... I'm setting out to build a predictive model for our client in the hotel/hospitality industry to explain the factors contributing to the attrition of their Loyalty ...
4 votes
1 answer
919 views

Likelihood of Linear Discriminant Analysis compared to logistic regression

I've come across an interesting exercise. We are given four classification models for binary response and a $d$-dimensional independent variable: A Linear Discriminant Analysis model where the ...
1 vote
0 answers
18 views

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 ...
1 vote
2 answers
44 views

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 ...
1 vote
1 answer
229 views

Comparing the fit of logistic regression model to a poisson regression model

How do we compare the fit of the two models given that the explanatory variables are the same, except the response variable is different? (the response predicts an equivalent thing). We were told that ...
0 votes
0 answers
11 views

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 ...
0 votes
0 answers
13 views

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. ...
0 votes
0 answers
16 views

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, ...
1 vote
1 answer
273 views

How to test proportion of each factor level against mean proportion across all levels (binary outcome)

I have a dataset with the factor region (4 levels) and a binary variable outcome (0/1). Here in wide format. ...
0 votes
0 answers
26 views

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-...
2 votes
1 answer
529 views

Interpreting odds ratio units

I'm running logistic regressions in Python using statsmodels logit and, downstream, am calculating odds ratios for each independent variable. I know that, conventionally, an odds ratio is interpreted ...
0 votes
1 answer
280 views

Odd ratio for binomial variable values

I am calculating the odd ratio of logistic regression (using statsmodel of Python). I have one independent variable (i.e. process type: faulty (1) or non-faulty (2) and one dependent variable (i.e. ...
0 votes
3 answers
35 views

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 ...
2 votes
1 answer
32 views

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 ...
2 votes
1 answer
2k views

How to choose alternative specific constant (ASC) in multinomial logistic regression in R? (unlabeled choice experiments)

I am trying to replicate my colleague's NLOGIT analysis using R. This analysis was for a discrete choice experiment in which fisherman chose whether to opt into a hypothetical environmental protection ...
0 votes
0 answers
11 views

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 ...
6 votes
4 answers
1k views

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 ...
0 votes
0 answers
16 views

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 ...
2 votes
1 answer
47 views

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 ...
0 votes
0 answers
19 views

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 ...
0 votes
4 answers
114 views

Small-sample binary logit and linear models - response to referees [closed]

Background: This cross-sectional study collected 30 thrombosis samples. We evaluated the presence or absence of MP components (dependent variable), where 24 cases had MP (coded as 1) and 6 cases did ...
2 votes
1 answer
416 views

Should we always use clustered standard errors in panel data with only two time points, in a multilevel logistic regression?

This is the situation: I have a binary outcome at two timepoints (T1 and T2); I'm using a random-effect logistic regression (I mean: just the random intercept, no random slopes) to estimate subject-...
1 vote
0 answers
30 views

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 ...
0 votes
0 answers
49 views

Given that quasibinomial/quasipoisson reg models overdispersion, why ever use normal bin/poiss regression if quasi is more flexible?

In reading about quasibinomial regression: The quasi-binomial distribution, while similar to the binomial distribution, has an extra parameter 𝜙 (limited to |𝜙|≤min{𝑝/𝑛,(1−𝑝)/𝑛} ) that attempts ...
1 vote
2 answers
28 views

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 ...
2 votes
1 answer
76 views

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 ...
1 vote
2 answers
303 views

Comparison vs Reference Group, which tests to use in this scenario?

we are researching whether the date of a certain medical procedure impacts the complication rate of said procedure. To this end we have identified multiple risk factors we would like to study more ...
8 votes
2 answers
2k views

Oversampling correction for multinomial logistic regression

When modeling rare events with logistic regression, oversampling is a common method to reduce computation complexity (i.e., keep all the rare positive cases but just a subsample of negative cases). ...
1 vote
1 answer
670 views

How to Conduct Binary Logistic Regression with Repeated Measures

I have a data set in which the response variable ("Binary_Response") is binary. The explanatory variables I am hoping to include with my model are categorical and also binary ("...
7 votes
1 answer
86 views

Is there any physical process producing a logistic distribution?

In his Logit Models, J.S. Cramer writes the following (p. 23) Are there no physical processes producing a logistic distribution?
0 votes
1 answer
44 views

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 ...
2 votes
1 answer
63 views

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 ...
0 votes
0 answers
15 views

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 ...
3 votes
1 answer
58 views

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 ...
1 vote
1 answer
222 views

Point estimate and confidence interval for the difference in $x_1$ between two groups for which a particular $y$ is achieved

I have two variables (continuous $x_1$, control/treatment $x_2$) that I want to use to predict a probability. Domain knowledge suggests that the relationship is roughly linear in the log-odds, so I am ...
6 votes
2 answers
329 views

R squared in logistic regression adjusted for number of predictors

For OLS we have an adjusted R squared which adjusts for the number of predictors included in the model. For logistic regression there are some R squared analogues (Tjur’s R squared, McFadden’s R ...
0 votes
0 answers
18 views

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 ...
3 votes
1 answer
48 views

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 ...
0 votes
1 answer
225 views

Binary logistic regression- enter vs. all at once

I have a question regarding binary logistic regression. My DV is dichotomous (0=no, 1=yes), and I have 9 predictor variables (dummy-coded & scale). If I do for each predictor one regression ...
2 votes
1 answer
27 views

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 ...
14 votes
2 answers
26k views

Logistic regression and ordinal independent variables

I have found this post: Yes. The coefficient reflects the change in log odds for each increment of change in the ordinal predictor. This (very common) model specification assumes the the predictor ...
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 ...
0 votes
0 answers
20 views

Logistic Regression - categorical predictors [duplicate]

I'm looking for resources on general guidance for how to perform and interpret multiple logistic regression using SPSS, using categorial predictors. I have 2 categorical predictor variable. Each ...
6 votes
3 answers
1k views

May I replace Fisher's exact test or Chi-squared test with logistic regression and vice versa?

Let's assume we have two groups of patients, a control group and a treatment group. They were asked a question and the answer can be yes or no. Since I come from biological science where I used mainly ...

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