Questions tagged [logistic]

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

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8 views

Incorporate continuous group level variable in a hierarchical model?

I aim to assess the effects of difficulty (continuous variable) and trial type (0/1) on whether a subject has been correct in a logistic regression model. However, I have also measured subjects ...
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1answer
15 views

Logistic Regression in MATLAB glmnet always returns 0 vector as coefficients

I am using glmnet in MATLAB 2019a on my Macbook to do logistic regression. Algorithm: $log(\frac{\pi_i}{1-\pi_i})=\beta_0+X_i^T\beta$ $\pi_i=P(Y=2|X_i)=1-P(Y=1|X_i)$ Code: ...
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Interpreting odds ratios for log transformed and non-transformed variables in an ordered logistic regression with many levels

I am using an ordered logistic regression to evaluate the impact of various predictors relating to product and review characteristics on the performance of products in a sales ranking. My dependent ...
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Group level effects (odds ratio) - dummy coding vs. effect

I ran a logistic model in R's brms, with a categorical variable (condition) with two levels as predictor. When interpreting the ...
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30 views

Shrinkage Parameter for LASSO (glmnet package in R)

I am using glmnet package in R-software to build a Binary Logistic Regression with the LASSO. I have used the following link as ...
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18 views

Why SVM performs better than logistic regression for well separated case?

In ISLR page 357, the author mentioned that " When the classes are well separated, SVMs tend to behave better than logistic regression; in more overlapping regimes, logistic regression is often ...
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How much missing data can you replace with data imputation? [duplicate]

I have a data set with 40 participants that underwent 20 different tests. For most of these tests all the data is there. For 2 of the 20 tests, 2 out of the 40 values are missing. However, for 5 of ...
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6 views

Regression with an array instead of column as features in R [on hold]

I would like to know if it is possible to do a regression with features that will be in a single column and how to do it. Example. Let's say my dataset is like this: ...
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How to do model fit if the Hosmer Lemeshow GOF is less than 0.05

I have a data set that the response variable is count data, with other predictive variables all categorical. I used the stepwise logistic regression to try to find the best model fit. I used the code ...
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13 views

What is the difference between lasso and WOE encoding in logistic regression?

I know lasso is one of the best method to select important variables and make variables sparse. But WOE encoding does the same thing, making variable smooth. I would like to know what is the ...
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29 views

How to weight different variables to produce optimal AUC in logistic regression

Lets say I have 7 independent variables (x1 to x7) that I determined to be important variables in predicting y using forward selection (stepAIC function): ...
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2answers
26 views

In a logit model, what does a Estimate value = 0 (zero) mean? Is it a useless variable?

As an output of a logistic regression analysis I got an Estimate value of 0 (zero). Does this mean that the variable is useless in the model? Or what? logit(P) = log(P / (1 - P)) = 13.458 - 0 ...
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45 views

How can I try to do logistic regression of time series? [closed]

I'm trying to get some information using my data. My data set is below. ...
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1answer
28 views

Feasibility of running mixed-effects poisson/logistic regression with correlation structure such as AR(1), Toeplitz

I'm not aware of any R package that lets me use specify the covariance pattern model such as in the package nlme and run the mixed effects poisson/logistic ...
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2answers
58 views

GEE logit / Poisson versus mixed effects Poisson / logit

There's a way to do Poisson or logit mixed effects and Poisson or logit GEE in R. What's the difference between GEE and the mixed effects models for Poisson / logistic regression? I heard its the ...
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Collapsing a categorical variable in multivariable logistic regression analysis in R. What would be the reference class? [closed]

I am fitting a multivariable logistic regression model to find out the predictors of burnout in medical students and residents using the following variables: yearN, depressionN, anxietyN, satiscareerN,...
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1answer
26 views

How to convert beta from logistic regression into cohen's d?

Is there a way to transform a coefficient from a logistic regression into a cohen's d value? I am trying to calculate the cohen's d for a study with a binary DV while controlling for another ...
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8 views

Incorporating rank-ordered logit results from different samples

I would like to create rank-ordered logit models to predict the outcome (winner in this case) of variants of a multi-player game. For the most part, the predictors for each variant differ. However, in ...
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4answers
290 views

Are there any differences in causality between linear and logistic regression?

I'm guessing this is a pretty basic question, but I am having a hard time wrapping my head around it. So my understanding with linear regression, is that it shows how much a change in X, will cause a ...
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33 views

Unexpectedly large coefficients in logistic interaction model

I would like to know if you could provide any insights regarding large and unexpected coefficients in logistic models with interaction terms. When running the interaction model, the coefficients for ...
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1answer
37 views

How can I apply a Logistic Regression model in real life? [duplicate]

I just run a LR multivariate analysis to class probability check. From this analysis I could see that the combination of 4-variables would increase my test accuracy. Here is the output of this ...
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1answer
30 views

how to calculate VIF in logistic regression?

No book told me that... Using McFadden’s Pseudo-R2 ? OR do traditional linear regression to get VIF?
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How can I analyse the association between a categorical variable (binary outcome) and a continous variable especially in R?

I want to analyze the association between a binary variable and a continuous variable in R. But I am not clear about what steps I should follow. I explored the continuous variable by the histogram ...
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What is the effective difference between PCA/SVD feature selection as input to logistic regression and Lasso regularization? [duplicate]

I have a problem with where the number of features (around 10k) is almost of the same order as the number of records in my data (around 100k). I'm using this data in a supervised classification task ...
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1answer
15 views

intuition behind classification model confidence intervals

What do confidence intervals mean in classification problems? I recently did a study with glmnet in R, and got this confusion matrix : ...
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5 views

Multi level logistic regression with ordinal level dependent and independent variables

I am currently trying to run a multi level logistic regression model and struggling to identify the best way forward using STATA.Details below: Independent variable: ordinal with 5 levels Dependant ...
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1answer
10 views

Logistic regression log-likelihood - meaning of μ

I'm trying to implement my own logistic regression, but I'm not sure I understand some of the notation. In Machine Learning : A Probabilistic Perspective (Murphy, 2012), the negative log-likelihood is ...
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1answer
17 views

coefficient multiple logistic regression flips sign when adding second predictor [duplicate]

I have a binary outcome variable (word not learned = 0; word learned = 1) and two continuous predictors: how many phonemes/sounds the word contains (phonemic length) phonotactic probability (average ...
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23 views

Predictor variable with uneven group sizes

I'm running a logistic regression with a categorical independent variable. My categorical IV (an ordinal none, low, medium, high) has a pretty uneven distribution: None (4.28%), Low (36.30%, Medium 30....
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1answer
21 views

Log odds Standard Error

I am reading a paper on how the authors calculate the variance/standard deviation of what appears to be log(odds). The paper is a medical paper (Discontinuation of Oral Antivirals in Chronic ...
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21 views

Odd Ratios Change After Including Other Independent Variables… What does that exactly mean?

I am currently writing my master's thesis and I want to identify whether Austrians living in Vienna are more likely than immigrants in Vienna to become self-employed. In order to find out whether this ...
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1answer
35 views

Normalize discrete variables in logistic regression?

I am running the a logistic regression model to test the effects of task variables on choice (left/right). I set up a logistic regression model per subject and test the regression coefficients against ...
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16 views

Logistic Regression: overall categorical elements significant, dummies vary

I am conducting a logistic regression on n=31669 sales records to see which categories impact outcome; I'm trying to see what variables have the biggest impact so as to focus management. Am using ...
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1answer
45 views

Determining Intercept for Regularized Logistic Regression

Going off of the standard set up, we have $N$ observations and $P$ predictors stored in the data matrix $\mathbf{X} = \{ x_{i,j} \}$ for $i = 1, \ldots, N$ and $j = 1, \ldots, P$. The response is ...
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logistic regression vs OLS - comparison of variable significance

I am modeling usage of a particular app like this: predicting week 3 engagement (number of days of the week the product is used) based on prior engagement (week 1 and week 2) and usage of particular ...
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1answer
19 views

When to exponentiate: the mean of the chain or at every step in the chain?

I am interested in when it is best to exponentiate a difference in log-odds Here is a sample problem in the stan language, three groups of forty binary observations, group 1 with hit probability = 0....
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3answers
144 views

Should I cross-validate a logistic regression model that will not be used to make predictions?

Apologies if this question doesn't make much sense and if it is overly long. I had some basic stats training at university, but there are lots of gaps in my knowledge which I've gradually been trying ...
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1answer
40 views

Logistic regression: use of the term “prediction”

I would be grateful for any advice on this. I am currently working on an analysis where we are trying to identify what variables would be most useful in predicting a particular binary outcome. We used ...
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1answer
26 views

Logistic regression with only dichotomous (0,1) predictors and response

I'm doing some glm in R, where I have response of not being depressed (0) and being depressed (1). I have three predictors, first one being relationship situation (in a relationship = 0, single = 1). ...
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30 views

GLM Logistic regression in R: one category is significant, but others are not. Should I drop the variable? [duplicate]

so I am using GLM for logistic regression in R and I have some variables with many factors. I ran the model and has the result like this: My question is: 1. Is this variable significant? ...
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2answers
61 views

Non-significant results from logit model with one categorical independent variable

My model consists of a dependent variable $y$ that can take values 0 and 1. The independent variable $x$ is a categorical variable that can take values, 1, 2 and 3. The logit model looks like this: $$...
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38 views

How can I make input data for logistic regression?

I have dataset with 6 category variables. each category variable shows some machine error codes ranging between 0 and some big number like 50000. I want to try Logistic Regression to build a ...
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31 views

Multicollinearity in logistic regression: how to estimate proper model?

I have a data set with highly correlated predictors (CIC-IDS 2017: data set about traffic on computer network). Some predictors have even correlation 1, rest of them are very highly or quite highly ...
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1answer
20 views

The appropriate statistical model for categorical/binary DV + mixed design

What R function should I use to build the appropriate logistic regression model if I have the following structure? Independent variables A categorical variable that varies between-subjects A ...
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36 views

Optimal Threshold On Single Input

Suppose we have a sensor that measures "how red" an object is. Using this single input, we would like to classify whether or not the object is round. We have a data set comprised of tuples where the ...
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1answer
48 views

don't understand the derivation of logarithmic cost used in gradient descent [closed]

I am learning Machine Learning.I have seen that in logistic regression there are two cost 1)θj := θj − α / m ∑i=1m (hθ(x(i))−y(i))x(i) 2)Cost(hθ(x),y) = −ylog(hθ(x))−(1−y)log(1−h(x)) While updating ...
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1answer
19 views

Binary vs ordinal logistic regresson

I have made my response variable as both a binary and a ordinal variable and performed binary logistic regression respective ordinal logistic regression. If I want to test which model fits the data ...
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What is the *formal* definition of separation in *binary* logistic regression?

I am trying to understand complete and quasi complete separation in the context of logistic binary regression. However, I have not found a clear source. I know the seminal paper https://www.jstor....
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34 views

Credit scorecard using Logistic Regression on R

I tried developing a scorecard to assess creditworthiness using the "Scorecard" package on R. The problem I encountered is when I scale the card and calculate the points for each attribute of each ...
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2answers
26 views

logistic regression response variable ~ Bernoulli(pi)? [duplicate]

I am a newbie to logistic regression. So far, I know how to derive the coefficients of logistic regression, how it basically works. What I don't know are the assumptions & inference stuff for ...