Questions tagged [logistic]
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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SPSS and PSPP yield very different logistic reggression results with same dataset
I'm trying to run a multiple logistic regression model where the dependent variable is dichotomous and independent variables are either bynary or continuous. At first I only had access to PSPP, but ...
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Is the use of logistic regression with 'ordered entry of variables' in this paper statistically meaningful?
I'm reading a paper which says:
In performing the logistic regression analyses, the order of entry of predictor variables was guided by our theoretical rationale and our major hypotheses. In each ...
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Variable selection in logistic regression [duplicate]
So I'm trying to make a multivariate logistic regression model in R studio. I'm not sure how to go about this. What seemed to make sense to me was to model every predictor against the response ...
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How to estimate this specific logistic regression model which is not linear in its parameters?
A. Suppose I want to fit the regression
$Y = f(\lambda X_1 + (1-\lambda) X_2)$
where $f(x) = ax^2 + bx + c$, and $\lambda$, a, b, c are to be estimated using the data.
This is nonlinear, but it's ...
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Logistic regression after a 3 year follow up where successful people can leave the sample
I have data tracking the outcomes of young people participating in an intervention project (between the ages of 12-16). In 2016, data was taken of all young people who had joined the project that year....
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How do I include these variables within my logistic regression analysis?
So my logistic regression model aims to predict the likelihood of a severe accident (yes/no) based on characteristics of drivers, car types and other factors. I have data which has all this ...
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Signs for marginal effects and regression coefficients are inconsistent for beta regression
I have conducted a zero-one inflated beta (ZOIB) regression using a logit link function for explaining tenure incidence in colleges and universities. Tenure incidence is a proportion in the interval [...
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link log and identity in GLMER
Say that we have a GLM model with the following formula:
outcome = b1x1 + b2x2 + b0
and outcome is cost, x1, x2 are independent variables
Fitted using log link with gaussian distribution, so log ...
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Logistics regression gives opposite result than 2 by 2 table
I am running logistic regression on sas. My outcome var is if student retained or not. One of my independent variable, if they attended first year oritentation is showing opposite result than what is ...
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mediator or moderator in R?
Hello I am learning how to decide whether a variable is a moderator or a mediator in R. For my knowledge, if the interaction term is not statistically significant, we need to consider the mediating ...
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Can I perform logistic regression or any other type of regression on this dataset?
My data set contains information regarding the number of road accidents separated by gender, age, area, and other factors. Can I perform logistic regression analysis using this dataset to predict how ...
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Is logistic regression suitable for high frequency values?
I have the dataset with the following situation. My dependent variable (Y) is decimal and has non-parametric distribution (shapiro test p-value<0.05) and the current variable has a determinated ...
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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 ...
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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 ...
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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, ...
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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 ...
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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 ...
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How to linearize logistics function? [closed]
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 ...
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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 ...
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"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 ...
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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 ...
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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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With logistic regression, how does one choose a number of predictors when preregistering a study?
Harrell's Regression Modelling Strategies suggests that the number of predictors should not exceed $m/10$, $m/15$ or $m/20$.* For logistic regression $m$ is $\textrm{min}(n_1, n_2)$, where $n_1$ and $...
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Making and reporting a logistic regression, stratified by sex and age
This question was already asked at Stackoverflow - R Language Collective, but they said this might be a better place to post this question, so here I am.
I'm doing the statistics in R. I have this ...
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Could multicollinearity be messing up my logistic regression? Can I overcome it?
My data has 5 binary dependent variables, 9 categorical independent variables, and 3 continuous independent variables, with a sample size of 1232. The 5 dependent variables are just different ways of ...
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Orthogonal polynomial contrasts in SPSS (for a binary logistic regression)
I have 4 IVs: gender (male, female), marital status (married, single), threat (continuous variable) and stress with four levels (ranging from 7 to 10 with ten being 'most stressed'). My DV is ...
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How to Handle Non-Multinormality in the Context of Exploratory Factor Analysis for Logistic Regression
I'm trying to follow the book A Step-by-Step Guide to Exploratory Factor Analysis with R and Rstudio, by Marley W. Watkins, and apply the principles in the book to a real-world data set. Ultimately, ...
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How to forecast changepoints from Gas Concentration Data?
So I'm trying to predict when gas concentrations change from sensor conductivity readings over a day. The gases randomly change concentrations around every 80-120 seconds and are kept constant between ...
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Probability threshold in ROC curve analyses
When conducting a logistic regression analysis in SPSS, a default threshold of 0.5 is used for the classification table. Consequently, individuals with a predicted probability < 0.5 are assigned to ...
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Logistic Classification using R::caret
My question stems from this one I recently posted (I've fixed the issue raised in the comments, though that wasn't the topic of the question):
Strange interpretation of odds ratio from logistic ...
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Use of simple statistics for matched study designs
This might be a silly question, but I have always found this confusing. In a case-control study one selects participants to the study based on having or not having the outcome, in addition to some set ...
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exact match on covariates or include in a model?
The scenario is I have a binary outcome, a treatment group variable (3 groups) and 3 covariates. It is possible to exact match all 3 covariates on 1:N from group 1:2 and group 1:3. Would you perform ...
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heterogenous treatment effects - a question
So I conducted a framing experiment - 4000 people received either framing A or B, and donated $ to a charity if they wanted to.
Now I want to check if framing A or B had specific efffects on ...
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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 ...
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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 ...
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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'. ...
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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 ...
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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 ...
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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 ...
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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:
...
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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 ...
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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 ...
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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 ...
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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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