Questions tagged [logistic]

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

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39 views

Logistic regression with binomial independent variable

I have a table of observations, with three columns --- (a) class labels (can be 0 or 1), (b) counts of successes (out of a certain number of Bernoulli trials) and, (c) numbers of Bernoulli trials. I ...
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derivative of cross entropy yields log-odds, does that make sense?

I am looking for a proof how to derive the logistic regression from cross-entropy loss, i.e. derive the form of a sigmoid from cross entropy. my thoughts are these: $\ell = y_i \ln{p_i} + (1-y_i)\ln{...
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Literature request: (in)appropriateness of negative binomial for count data with an upper bound

I conducted an analysis where I used binomial logistic regression to analyze x successes in n trials (where n varies between observations) in aggregate (using the R syntax ...
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Why can negatively correlated variables have similar beta-coeficients in logistic regression?

I try to predict whether households use a certain service (TRUE or FALSE) based on various variables, using logistic (LASSO) regression. Among many others, I have the variables percentage man and ...
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1answer
87 views

A divergence that can be extended to logistic functions?

If I have data $\{(x_i, y_i)\}_{i=1}^n$ where the dependent variable is binary $(y_i = 0,1)$ I can model it using a logistic function: $$f(x; \alpha, \beta) = \frac{1}{1 + e^{-(\alpha + \beta x)}}$$ ...
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$\mathbb{E}[\sigma(r)^2]$ with $r \sim \mathcal{N}(0,1)$

Start with a random variable $r \sim \mathcal{N}(0,1)$. Now consider the random variable $\sigma(r)$ formed by passing it through a standard logistic function $\sigma(x) = \frac{1}{1 + e^{-x}}$. I ...
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70 views

Why do regression parameters change when adding more explanatory variables in ordinal logistic regression?

I have been using ordinal logistic regression with the ordinal package in R and the clm() function to complete an analysis of ordinal survey research data. In ...
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831 views

Delta Method Average Marginal Effects Multinomial Logit

Following the incredible demonstration in Statalist by Jeff Pitblado on how to calculate - using the Delta Method - the Standard Errors for Average Marginal Effects of a Logit Model. Q: What would ...
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739 views

Why without regularization, the asymptotic nature of logistic regression would keep driving loss towards 0 in high dimensions?

While understanding the Logistic regression, I didn't completely get the behavior of its asymptotic nature which says: Without regularization, the asymptotic nature of logistic regression i.e (it ...
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553 views

Calibration of penalized (LASSO or ELasticNet) logistic regression models

I would be very grateful for any help me with the following general query regarding calibration of penalized models with a binary outcome. I would like my prediction model to be calibrated (mean ...
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56 views

Can this be solved using a binary logistic multi-level model?

Is it possible to solve the following task by using a binary logistic multi level regression? If not, how can you solve it? The concept as a diagram: I have the location of individual stores and ...
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121 views

Correcting for noise in gene expression data

I have a training set of RT-qPCR gene expression data (not run in triplicate) for a batch of samples with two phenotypes $A$ and $B$ on which I've trained a logistic regression classifier. I also ...
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191 views

Propensity matching and analysis of resultant data on a data set with repeated measures

We have extracted retrospective case-level data collected over several years. We are using the administration of rescue antiemetic in the postanesthesia care unit as a proxy for postoperative nausea ...
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219 views

How does Poisson regression (with an offset) relate to Logistic regression?

I have some data I am trying to analyze of how often someone has chosen a given option (which I'll call choice A) vs not choosing it (which I'll call choice B) during a 6 month period. Each subject ...
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52 views

'Standardising' an explanatory variable for use in a logistic regression model

(I am a clinician, not a statistician!) I have been asked to advise on a study which uses logistic regression. The aim is to identify ultrasound measurements which predict miscarriage. The outcome ...
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1answer
537 views

Scaling regression coefficients Take 2: Gelman (2008) approach

I am asking a follow-up question about interpreting regression coefficients that have been scaled following Gelman's (2008, 2009) recommendations. Original recommendation to divide continuous ...
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749 views

Multinomial Logistic Regreesion with Lasso penalty in R

I am applying regularized logistic regression (in R) to the handwritten digits data set. I have fitted a logistic multinomial model with lasso penalty to the training data. I am asked to obtain the ...
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322 views

Marginal effect of variables - Logistic regression, Boosted tree, and other tree-based models

Assuming I have a classification problem where I have binary dependent variable Y and independent variables X1-X10. The X variables are categorical. Say we are interested in the marginal effect of ...
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23 views

Predicting the winner of a contest

This is just a general question, but I ran into a few situations lately with this same framework and I'm not sure what to do with it. Suppose we have 100 contests worth of data each with 8 ...
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115 views

Assessing fit for a logistic regression

I've been working on fitting a logistic regression model to a data set. I've attached the data set below. It includes data about the occurrence of snow, SnowBinary...
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296 views

Can I compare the Mean decrease in accuracy for two different random forest models

I am investigating how performance indicators measured in sporting contests relate to contest outcome. Models produced through RF algorithms give the best results (measured as ability to predict ...
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320 views

WHY: Logistic model overpredicts probability in specific probability region

I have tried to find answers to my question by googling but haven't found anything relevant - if anyone could pass on some resources or relevant key words that would be brilliant, in absence of ...
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36 views

logistic regression - inclusion of wrongly-informative variable

So I am not sure if this question makes sense at all, but I will try to explain. I want to build a logistic regression scoring model that learns automatically (updates) when sample is updated with ...
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422 views

Alternatives to ordinal regression when proportional odds assumption not met

I'm trying to fit an ordinal logistic regression using the ordinal package but the proportional odds assumption is not met. I have read all post here on this. My specific question is that, if you ...
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1answer
668 views

A time series logit model with lagged dependent variable

I have a panel dataset for stocks. My goal is to model and predict if the stock will close positive (1) tomorrow based on today's close (1/0) and other macroeconomic and firm-specific variables.So I ...
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692 views

Logit Transformation: Interpreting the Coefficients

I'm currently doing an empirical project in econometrics. I examine the effect of globalisation and some other control variables on poverty, doing OLS cross section given a sample of 74 countries (...
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578 views

What are the benefits of the z-score interpretation of probit regression coefficients?

Logit vs. probit is often a big debate. Many prefer logit simply because the coefficients can easily be converted into odds ratios, which are "more intuitive" to interpret than the z-score ...
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1answer
428 views

Dealing with Discrete numeric variables in logistic regression model

i have one relevant variable in my model like number of additional services taken by customer with visual inspection it is clear more the number of additional services customer opts in lesser the ...
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323 views

Weakly-informative priors, complete separation and identifiability in Bayesian logistic regression

Where complete separation may result in non-identifiability of parameter estimates in Bayesian logistic regression, Gelman et al (2008) recommend using weakly-informative priors using a Cauchy ...
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211 views

Can a calibrated prediction model that is able to discriminate have a poor Brier score?

I did a logistic regression with selected covariates on a dataset with about 10000 records and event rate of 10%. The cross validated c-index was 63% which admittedly is not very high. Looking at a ...
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307 views

How do I create a lift curve?

I am having trouble constructing a lift curve from scratch. Say I have bunch of 0-1 labels, and predictive labels. In order to construct the lift curve, I do the following steps (assume I have ...
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488 views

Is there literature on use of Conditional Odds Ratios to estimate Marginal Odds Ratios? Is COR equal to 1 when MOR is?

I write my questions in brief here upon requests from IWS (thanks for your reply): 1) Has anyone ever given a proof that Marginal Odds Ratio$=1->$ Conditional Odds Ratio$=1$ (let's call them $MOR$ ...
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484 views

how to deal with limited observations of categorical independent variables during logistic regression?

I'm running a logistic regression with a selection of categorical predictors. I have split my data into a training and testing set to evaluate my model. One of these predictors is "employment" which ...
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808 views

Naive Bayes vs. logistic regression

I'm working with credit scoring models. Here's what I know: Let Y be the binary outcome variable, $Y \in \{0,1\}$ where $Y = 1$ is the outcome of default and $X = (X_{1},...,X_{m})$ be the random ...
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610 views

logistic regression vs. bayesian approach

I am working with birds dataset to determine success or failure of these introduced species and the effect of response variables on such. A sample from the final ...
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2k views

Classification on highly skewed dataset

I have two classes A and B. 98% of the data belongs to class A and 2% of it belongs to class B. Size of the entire dataset is about 2000. I am interested in correctly classifying all the data points ...
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1answer
67 views

In real clinical diagnostic data set how can we know the “true label” of a patient?

When we were taught about Bayesian probability, we often saw the following example: in a population, there are 5% of people who has disease X, and among the people who have disease X, the current ...
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6k views

Multivariate logistic regression vs multinomial logistic regression?

I have 15 independent variables and 3 correlated, binary, dependent variables. It seems like for predicting correlated dependent variables the general recommendation is multivariate regression. One ...
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1answer
338 views

Binary logistic regression with compositional proportional predictors

I am running a binary logistic regression with compositional predictors that sum to 100% (demographic categories). I've looked at several postings about this, but can't find a good solution to my ...
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168 views

Potential bias when the training set is more general than the testing set

I am using Logistic Regression (LR) to obtain Coronary Artery Disease CAD probability equation. The data set has 16 candidate predictors, all continuous. There are two groups, CAD patient group (70 ...
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1answer
70 views

Estimating Equations for Treatment Model in Treatment Effects Estimation — How is this Equation Derived?

While reading the STATA 14 Treatment Effects Reference Manual (http://www.stata.com/manuals14/te.pdf), I'm having difficulty understanding how they arrive at the equation for the treatment model, that ...
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119 views

Including Predicted Treatment Probabilities of LHS variable on RHS of a Logistic Regression

I would like to see whether black and white participants are treated (0/1 treatment indicator) differently in my participant level data. However, black and white participants have different underlying ...
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3k views

Threshold for and Variations of Exact logistic regression

According to this UCLA tutorial exact logistic regression (elrm::elrm in R) should be prefered to the logistic regression ...
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2k views

How is the solver parameter and MLE related in Logistic regression for scikit-learn

I'm trying to understand the implementation of scikit-learn's Logistic Regression. I am new to the framework, and have only a basic understanding of logistic regression. http://scikit-learn.org/...
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77 views

Differences from logistic regression and mixed effects logistic regression - rounding error or conceptual mistake?

I'm a bit confused. To my understanding, the standard logistic regression should be equivalent to a mixed effect logistic regression where the statistical unit is defined as random effect - but I ...
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91 views

Unstable p-values in logistic regression

I'm tweaking a logistic regression model in R. The model's been optimized and tested pretty extensively so far. I need to remove one variable for non-statistical reasons (...
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1answer
997 views

Train accuracy < Test accuracy with regularization

With a friend we were playing with the notMNIST data, logistic regression and regularization. Without regularization, we could achieve a training accuracy (10k samples) of 78%, and test accuracy (15k ...
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205 views

How to present predicted probabilities for multiple predictors

I have performed a multinomial logistic regression using the multinom function in R. I have one categorical response variable with 3 levels, 3 continuous predictors and 3 categorical predictors (with ...
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898 views

Identifying outliers in logistic regression model

I'm looking to identify outliers in a logistic regression model, e.g. ...

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