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

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Can I do a t-test to compare t-statistics?

I was trying to fit a 2-level "hierarchical model" all in one go, in MATLAB. But then realised it might be better to do the lower level first, then the higher level. Simply, I have 80 subjects, from ...
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7 views

glmer and warning message and random effect

I have a data set that I expect there to be some variable among individuals; therefore, I chose to include ID as a random effect in the glmer model. However, when I run the model I get the following ...
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1answer
32 views

Cross-validation and logistic regression

I'm interested in building a set of candidate models in R for an analysis using logistic regression. Once I build the set of candidate models and evaluate their fit to the data using AICc (...
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5 views

mlogitroc problem with Stata 13 [migrated]

I have a question about the additional module "mlogitroc", which should plot a ROC curve based on a multinomial logistic regression. More in details, at the end of computation the software displays ...
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3answers
113 views

Saturated model - why is it perfectly fitted?

I can't understand why is saturated model perfectly fitted? I know the definition, I just don't have any intuition.
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6 views

SPSS Multinomial Logistic Regression Interaction Term Reference [migrated]

I am building a multinomial logistic regression model in SPSS. The dependent variable has 4 levels. There are two categorical factors; one factor has 4 levels, the other factor has 5 levels. I am also ...
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36 views

Sample size for logistic regression. How to determine the number need for positive and negative cases?

I would like to apply logistic regression for my research. And before that, I want to calculate the minimum number of sample size, positive cases, and negative cases. ...
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2answers
35 views
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1answer
26 views

Odds ratio and likelihood of A given B

I've observed 500 nurses touching different surfaces during 500 episodes of patient care. I've also recorded whether they wash their hands after they finish. I'd like to find out if touching the ...
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1answer
37 views

Is there any neural network whose output can be probabilistic, just like multi-class logistic regression?

I want to add nonlinear character into multi-class logistic regression. I know kernel logistic regression can do it. Is there any kind of neural network which has similar characteristic?
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How to Rank the Effects (Coefficients) of a Categorical Variable

I have a categorical variable, 'Ethnicity' with 12 levels, and an output variable 'has_condition' stating whether a particular subject had a particular genetic condition (1 means favorable, 0 means ...
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2answers
69 views

Analyzing residuals in logistic regression

Greetings statistics experts, I am having a try with the kaggle titanic dataset and am wondering what to do with the residuals after fitting models. In the case of linear regression you can look at a ...
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2answers
38 views

Logistic regression : non exclusive predictors

I am doing a logistic regression . My outcome is a categorical (yes/ no) pain after surgery. The predictors i wish to model for includes the type of anaesthesia , among other predictors. The problem ...
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111 views
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Obtaining adjusted proportions with lme4, using the glmer-function

I aim to estimate the annual proportion of patients (% of patients) that are smokers in a population whose age and sex must be taken into account. In other words, I want to calculate the adjusted ...
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16 views

How do I report the weights of the most influential features for logistic regression?

I am currently using logistic regression to compute the probability of some event. I randomly split my training/test data and perform cross-validation on the training data, getting a "best model" for ...
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26 views

Deforestation Scenarios using Logistic Regression (Stata)

I used Logistic Regression to model the contribution of a range of explanatory variables on deforestation processes (being my dependant variable - Deforested=1, No Deforestation=0) in the Brazilian ...
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0answers
5 views

Test for a Difference in Two Odds Ratios [migrated]

I run a logistic model for young people and another logistic model with the same prognostic factors for old people. I would like to compare the two ORs for each prognostic factor between the two ...
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20 views

Obtaining adjusted proportions with logistic regression

Can I obtain adjusted proportions of a binary variable by using logistic regression? I have a binary variable (normal/abnormal), which I'd like to obtain adjusted prevalence for (i.e the proportion ...
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0answers
11 views

How to predict the predict upper bound of a learning algorithm?

I am selecting features for a Logistic regression classifier. I have tested a lot of feature selection algorithms. however, it seems that there exist a fixed upper bound AUC value for a fix feature ...
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1answer
41 views

pruning Neural Network

Since a feedforward NN with a logistic function as activation function is not linear, does it make sense to reduce variables first with principal components or discriminant analysis? Because ...
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2answers
51 views

How can I model a binary outcomes in time series using logistic regression?

My data has a binary outcome (attack or not attack), day (20 day in repeated measured design) and some covariates (nestling’s movement). The objectives of my experiment are testing the effect of time ...
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test of correlation among binary variables prior to running logistic regression analysis

I am running a logistic regression analysis with binary variables on SPSS: dependent variable: preterm birth (Y/N) independent variables: hypertension (Y/N), diabetes (Y/N), C section (Y/N), ...
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prediction with string similarity

Assume we have an input of an email and we want to predict if it is spam or not spam. Without being a statistician, i would think one of the predictors takes the subject of the input email and ...
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1answer
70 views

Logistic regression with +1/-1 labels

I am trying to implement logistic regression where the label space is {-1,+1} instead of the usual {0,1}. I know that I can model this as a 0-1 problem but nevertheless I wanted to see if I can derive ...
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Does it make sense to report equally-fit, more complex, model, if it fits better a theory?

I have two (logistic) regression models for which the deviance is not significantly distinct (p = 0.7). One of them has education, gender and age explaining variable Y. In the other, I have added a ...
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Logistic regression and IV that depends on another IV value

I am modeling the effect of aspects of house change and marital status change on a (binomial) DV. Each observation in my data is a 3-year period in someone's life. Thus, for family change, I have a ...
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1answer
23 views

Logistic regression: should I remove observations with IV combinations that cannot lead to DV=1?

I am studying the effect of changes in household state on transport mode changes in people's life trajectories. My model is such that each observation I have is a 2-year period in a person's life. My ...
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23 views

Can anyone explain this error message in R? [duplicate]

I am running a mixed effect logistic regression, with two categorical predictors each of which are dichotomous. This is my formula, with variable names changed: ...
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20 views

Question about interactions in logistic regression, and reporting them [duplicate]

I am running a logistic regression with two dichotomous categorical predictors, and of course a dichotomous outcome variable. My questions are: How do I interpret a significant interaction? Do I ...
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Comparing two correlated dependent variables

I have two dependent variables that I want to predict. One is a normally-distributed continuous variable, and the other is a binary categorical variable (0 or 1). They're moderately correlated so that ...
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9 views

Number of parameters in multinomial logistic regression

In Chapter 10 (Directed graphical models) of Murphy's Machine Learning text, the author claims that multinomial logistic regression has $O(K^2 V^2)$ parameters, where $K$ is the number of discrete ...
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14 views

Function predict in glm applied to new data [migrated]

This question could have been discussed before, but I failed to find it. The question is: let's suggest, I'm fitting a logistic regression and I would like to train it on training set and then apply ...
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31 views

Python - SkLearn Logistic Regression: One-by-one train instance

Here is my question, I have a huge train set so I can't load it in memory and apply this code. ...
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14 views

Interpretation of logged term in logit (generalizing previous answers)

I have a logistic regression model, where one of my variables is logged. It is of the following form: $\ln(\frac{p}{1-p}) = B_1\ln(X) + B_2Y + ... + \epsilon$ , where $\epsilon$ is an error term. I ...
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2answers
110 views

Determine Maximum Likelihood Estimate (MLE) of loglogistic distribution

I am given two data sets containing dates and losses (in some currency). I have to determine the maximum likelihood estimates of the parameters of loglogistic distribution. I googled and found a ...
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Gllamm, gllapred and correct way of plotting results? [migrated]

I am trying to run a random intercept, random coefficient (usually referred to as random slope) multilevel logit model for cross-sectional data with cross-level interactions in Stata with the command ...
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1answer
53 views

Interpretation of variance in multilevel logistic regression

Please help me to interpret the findings of my model. The specifications of the model are: Dependent variable: treatment (1) or no-treatment (0). Independent variables: age, number of drugs used, ...
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1answer
55 views

Why doesn't Mahout logistic regression give a good AUC when the model is tested on training data?

0 down vote favorite I'm using the logistic regression of Mahout (version 0.9) but when I check the created model on the same data set it was trained for, I do not see a high value for AUC. I would ...
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2answers
31 views

Multiple test correction for categorical variables with many levels

I am creating a binary logistic regression model with the inputs as a single categorical variable with 100 levels. My goal is to find which level of the categorical variable is most likely to result ...
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Does collinearity of one-hot encoded features matter for SVM and LogReg?

Sometimes I encode categorical features as binary values - one feature per possible category value indicating whether that feature name matches the original category value (i.e. one-of-K scheme). Now ...
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487 views

How fair is it to use the word “predict” for (logistic) regression?

My understanding is that even regression does not give causality. It can only give association between y variable and x variables and possibly a direction. Am I correct? I've often found phrases ...
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1answer
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Why including some observations twice changes the coefficients of logistic regression?

When I simply duplicate a subset of observations and build the same logistic regression model with the extended data, the coefficients of covariates change. If I duplicate the whole dataset, they ...
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2answers
28 views

Emphasize a link between two predictor variables (Machine Learning)

I am creating a machine learning application which will utilize logistic regression (though I haven't ruled out bayesian regression). I have multiple predictor variables that I believe to be ...
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How to summarize a series of cumulative variables and extract their contributions to the variation explained by the summarized variable?

I want to use a mixed logistic regression. My explanatory variables are ten variables corresponding to cumulative variables measuring the same value over the 10 years preceding the year of interest, ...
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1answer
108 views

What does a very high odds ratio in binary logistic regression indicate?

I am developing a predictive model to apply to raster layers for land cover classification. So, I have a thematic category that is classified as agriculture but an accuracy assessment indicates ...
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1answer
35 views

Is it possible to compare probabilities of 2 logistic different models?

Is it possible to compare probabilities of 2 logistic different models? For example if I have one model that returns the probability that someone answer a phone call on Mondays, and then I have ...
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14 views

Weighting particular cases in logistic regression

I am new to logistic regression and I am trying to determine whether it makes sense to weight a particular case in my data which is oversampled in order to model my data better. I'm not even sure if ...
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1answer
68 views

Help me understand adjusted odds ratio in logistic regression

I've been having a hard time trying to understand the use of logistic regression in a paper. The paper available here uses logistic regression to predict probability of complications during cataract ...
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30 views

Test of Independence Between Two Nominal Variables With Many Levels Each

I am looking to test whether there is a significant relationship between two nominal variables, one which has 100 levels and the other with 10 levels. I initially considered doing a $\chi^2$ test of ...