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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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GDA vs Logistic Regression

Given an arbitrary dataset, how would one decide whether to use GDA or Logistic Regression? Is the only way to choose via trying both and selecting the one with better performance or is there some way ...
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Checking dataset distribution [duplicate]

While reading about the difference between Gaussian Discriminative Analysis and Logistic Regression here, I came across the idea that GDAs will have better performance on Gaussian data as it makes the ...
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statsmodels logistic regression with binned variables has large coefficients and standard error for some variables

I'm fitting a logistic regression (binary) using Python's statsmodels, and here's a snippet of summary from the model: I have noticed that the large coefficients ...
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“Down” “Null” “Up” logistic regression

I am familiar with binomial (logistic) regression and with multinomial regression based thereon. Is there a technique specifically adapted to "trinomial" data, where the data can be represented -1, 0, ...
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flight delay prediction [on hold]

Suppose that there is an airport and we have the average of flight delays for every day of the first month of 2018. Lets say the first day had an average flight delay of 2000 seconds and the second ...
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Scientific research studies using multinomial logistic regression [on hold]

I am having difficulties determining the types of statistical testing for my study. This is a clinical research study collecting medical data to classify them into different disease state. I am ...
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Constraints across related dependent variables

I'm working on model that uses a set of features like track_type, driver_age and some lag variables to predict the number of <...
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Should I use statistical inference on this “sample”?

The dataset gets its data from thousands of individuals throughout the US who update the same spreadsheet of about 5000 rows. This dataset contains address for individuals and is updated by the ...
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How to code a categorical variable for logistic regression with overlap in the categories/subgroups?

Suppose I have a categorical variable consisting of four levels: a, b, c, and d. When these levels are mutual exclusive, I would use dummy coding - so three dummies with for example level a as ...
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1answer
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How does a Logistic regression model converge if most variables are not linear with the log odds of the dependent variable?

I have a dataset (unfortunately cannot disclose any part of it) which has a binary response variable. For each independent variable, I calculate the log odds of the positive cases given each value of ...
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How do I check my logistic regression for linearity?

My understanding is that logistic regression assumes a linear relationship between the logit of the outcome and each predictor variable. I'm working on a case study from this MIT course. My model is ...
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Logistic regression on aggregated counts [duplicate]

Normally when we do logistic regression, we would have a dataset something like: X1 X2 Y 1: A 3 0 2: A 4 0 3: A 3 0 4: B 4 1 (4 observations) However,...
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Does BoxCox transformation work for logistic regression?

I'm working on a case study from this MIT course. I'm practicing classification problems. Here is the code for my model. (The dataset can be accessed from the link. I can add it to this post) ...
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Linear Regression in my time series class [on hold]

I need help on creating sas code for a linear regression for electric consumption versus time in years from april 1997 to april 2018. A sample of my data is shown below in the images. I am using SAS. ...
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Linear Regression (Time series Analysis) [on hold]

How do I do a linear regression of electrical consumption against year (time) from the electrical data set for the years March 1997- March 2018. A sample of my data is shown below in the images. I am ...
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Comparing Logistic regression Pseudo-$R^2$ between model with Interaction effects and model without Interaction effects

I have two Logistic regression models, one including manually selected (hierarchical) interaction effects between few independent variables and one model without any interaction effects. Both models ...
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How to report Logistic Regression Pseudo-R^2 in publication or reports?

I have a Logisitc Regression model with a McFadden Pseudo-$R^2=0.7113$. Based on the answers to this question: McFadden's Pseudo-R2 Interpretation, it seems my model has a good fit. However if I ...
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1answer
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pymc3: acceptance probabilities and divergencies after tuning

I coded two models in pymc3, which I thought are quite simple. Logistic Regression The first is a logistic regression in an experiment that models correct and wrong answers for specific tasks in a ...
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1answer
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Understanding the parameters needed for a distribution in Bayes networks?

Since I have a discriminative mindset hardly can I intuit the so-called parameters needed to specify a distribution in a generative Bayesian Network. I'd like to borrow an example from this blog. If ...
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allEffects-Interpretation and missing p-values

I need to run a logistic regression with random effects, about wheelchair users and hinderance due to environmental barriers: ...
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How to combine restricted cubic spline with ordinal logistic regression with package rms in R [on hold]

which function can be used to combine ordinal logistic regression and restricted cubic spline in R
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1answer
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How can I make simulated logistic regression model more noisy?

When I want to simulate Y coming from the linear regression model, $$Y_i = X_i ^T \beta + \epsilon_i,$$ I can use code like: ...
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Two predictor variables are partially related. How do I handle them before performing logistic regression

I have a predictor variable which has three levels (success, failure, nonexistent). For all nonexistent values another predictor variable value is 0 but success and failure could fall within a range ...
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Strategy & interpretation for investigating possible interaction between continuous & categorical variable

I am working with glm in R. My predictors are one continuous variable (X_conti) and one categorical variable (...
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2answers
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What measure should I use as cross-validation error with logistic regression in K-fold cross-validation?

What measure should I use as cross-validation error with logistic regression in K-fold cross-validation, especially when the Type I error is more serious and what we want to avoid at all cost?
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Is there an upper bound on number of logistic regression responses that yield infinite estimates

Suppose a logistic regression problem has N observations of {0, 1} and that there are p parameters. Also assume the design matrix, X, is full rank with p < N. We know that there will be certain ...
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Consequences of unbalanced subgroups of categorical variables in logistic regression?

I have a dataset of around 120000 (120K) unique individuals. I am fitting a binary logistic regression, where I have around 150 variables to choose from. For the categorical variables, some are very ...
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What model should I use if I want to describe the relationship between the % and binary outcome

I want to model a relationship between the % of students who received a flu vaccine at a certain school and whether their school had a flu outbreak or not. Thanks
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The performance metric used in prediction is different from the objective function to train the model

For linear regression and many machine learning models, we use the same performance metric during the training and testing stage. For example, during the training stage, our machine learning algorithm ...
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multilevel logistic regression with rare events

I am running a multilevel logistic regression with a dichotomous outcome. The outcome variable measures protest participation. About 10 percent of the overall sample reports positive answers, which ...
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2answers
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How to create a logistic regression model based on a two way table

question Given a table such as : $$ \begin{array}{ll|ll} & A & {} \\ & & 0 & 1 \\ \hline B& 1 & 44 & 27 \\ &0 & 443 & 95 \end{array} $$ If I ...
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1answer
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Logistic regression suddenly starts missing

Posting the following issue just in case anyone else has had experience with it and successfully dealt with it. Would appreciate any ideas. I have a logistic regression based model that gave excellent ...
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Assess impact on results of participants recruited via additional outreach efforts

I am currently working on a project that evaluates certain study recruitment strategies in regards of increasing participation among different subgroups. One of those strategies is reminder letters. ...
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1answer
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logistic regression with high correlation but no significative variables

I am working with logistic regression in R by means of glm. I have fitted a logistic (0-1) regression model with seven predictor variables. I obtain a model where the variables have high p-values (>0....
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Alternative-specific coefficients in mixed logit in R

I am trying to estimate a random coefficients logit model in R mlogit where random parameters occur for the cost of travel the <...
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Sparse solutions: linear systems vs logistic regression

It is known in the field of compressed sensing/sparse approximations that if $$Ax = b$$ has sparse solution (with $s$ nonzeros), then there is a condition which states that it is unique, if $$s \leq 0....
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Is there a systematic method to do transformations on independent variables in logistic regression?

Is there a systematic method for Logistic Regression to do transformations on the independent variables, in order to conclude that the most optimal logistic regression model is fitted? Illustration ...
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What is the best way to choose interactions between continuous variables for Logistic Regression?

I have a logistic regression model that I am working on for a school project. I have about 55 predictors, all of which are continuous. I am relatively new to the idea of "interactions" between ...
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Modeling with non-negative skewed predictor

I'm trying to estimate a fractional outcome through weighted logistic regression. One of my IVs is continuous and cannot be negative. And about 45% of the values are 0. Most of the zeros are related ...
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Logistic Regression(multi class) accuracy too small

I try to solve a problem with 3 features and 6 classes(label). The training dataset is 700 rows * 3 columns. I use one-Vs-all method, but I do not why the prediction accuracy is too small, just 24%. ...
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Quasipoisson model variable selection and find best model

I am running a Quasipoisson model in R with a lot of variables. This is my outcome: I want to find out which variables have an influence on the dormouse abundance (number of nests). After doing the ...
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1answer
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Curved regression lines

I had already asked a similar question here, but I'm experiencing the same problem for a different data-set and for a different family of mixed models. My response variable is a binary outcome of ...
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Mixed-effects logistic regression

I'm new to data analysis and I'm trying to perform a mixed-effect logistic regression. My data look like this: ...
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What information can be extracted from plotting two variables of a multiple logistic regression against the prediction?

I have a multiple logistic regression model that has the form of: disease ~ treatment + x2 + x3 + x4 + x5 Where disease can take values 1 and 0 (diseased or not ...
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Quadratic model of data?

Is it possible to fit a quadratic or polynomial model with this type of data? Two inputs, input one is a temperature sensor: Input two is a valve opening on a scale from 0-100: This is a scatter ...
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How should clustering be accounted for in logistic regression, when there are very few clusters?

I have survey data from 1000 patients. This is a convenience venue-based sample. In a specific city, at 9 hospitals that happen to have a psychosocial program, patients can opt into the program if ...
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Stata Logit model - sample size and clustering question

I would like to check if there is a relationship between mothers' fertility and grandparental childcare. I am using a cross-national survey dataset. I restricted the sample to 6 countries of interest ...
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question about the logit model for credit risk

i have this question in one of the past exams . Discuss which model you would choose to calculate the probability of default of corporate firms and give a rationale for including OR excluding the RE/...
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Repeated measures to predict binary outcome

I would like to predict outcome of an event based on repeated measures. The problem is the following one: I have 100 patients with measures of a certain feature at different times, but all the ...
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Kolmogorov–Smirnov test in logistic regression

When applying KS-test (as goodness-of-fit test) on logistic regression (class: 0,1), where x-axis = probability of being classified as class 1, sorting ascendingly. Here are the 2 questions: Why are ...