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

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Error “initial value in 'vmmin' is not finite” when changing factors in ordinal logistic regression

I've generated some fake data to give a simple example of ordinal logistic regression. My data set (raw data here) looks like this: ...
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26 views

Need help setting up multilevel logistic regression

I am trying to see the effect of a certain intervention in schools. The outcome variable is binary. We have students within schools. Also students' age is a covariate (doesn't changed before and after ...
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208 views

Why does this logistic GAM fit so poorly?

I am trying to create a logistic regression model with mgcv::gam with what I think is a simple decision boundary, but the model I build performs very poorly. A local regression model built using ...
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21 views

Trying to understand the basics of a mixed-effects logistic regression model for a 10-step continuum

I am trying understand how to correctly build a mixed-effects logistic regression model in R. I believe my model is pretty simple and straight forward but I'm lacking in experience and uncertain I'm ...
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46 views

Logistic Regression: determining significance of independent variables [on hold]

I am trying to do Logistic Regression in R. My data set contains more than 50 variables. Some of them are factor (qualitative variable) and others are independent variable(quantitative). I would like ...
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1answer
36 views

Range of predicted probabilities by logistic regression

I have a binary classification problem with unbalanced classes, e.g. I have 500 examples of negative class(0) and 20 examples of positive class (1) and I need to estimate the probability of positive ...
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39 views

Ordinal logistic regression with non-negative independent variables

If I understand things correctly, we want to look at $log(p/(1-p))$ since we want the independent variables to be able to take on any real value. But what if you know your independents can never be ...
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16 views

Examining the Win Probability of a Particular Play-style in a Set of Tournaments

Something I've been playing around with in my head, which I'd like some advice on. Assume you have a game with four different "play-styles" - this can be a particular strategy, different team ...
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10 views

multinomial logistic regression with transition period

given data that has to periods t0 and t1 and in each period there are two categories that a subject can be in {a,b} would there be an inference problem to formulate a multinomial logistic model as ...
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Basic question about getting esimated probabilities in R

I've got what I think is a fairly basic problem. I'm not sure if it is a conceptual question or software question, but I'm fairly new to using R and these kinds of stats, so it could be either or ...
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37 views

Independent/Dependent variables & type of statistical test

If someone is investigating differences in means between 2 groups, does it matter which we consider to be the IV and the DV? For example, can I use a t test to examine the difference in the age of ...
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27 views

Modelling interaction

How does adding interaction term in the model adjust for it or why do we need to add interaction? I am working on logistic regression model with treatment and race as predictors. I have added ...
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15 views

Logistic regression in R: Leave-one-out interpretation of coefficients technique

I apply multiple logistic regression in R. I need to approximately be able to interpret the coefficients and quantify the contribution of each independent variable. I am aware that direct ...
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39 views

How to interpret the results of bootstrapping and Monte Carlo simulation utilised to test lasso logistic regression results?

My situation: sample size: 116 binary outcome (32 events) number predictors: 42 (both continuous and categorical) predictors did not come from the top of my head; their choice was based on the ...
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34 views

Stochastic Gradient Descent for Logistic Regression always returns a cost of Inf and weight vector never gets any closer

I am trying to implement a logistic regression solver in MATLAB and i am finding the weights by stochastic gradient descent. I am running into a problem where my data seems to produce an infinite ...
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1answer
97 views

What is the difference between logistic and logit regression?

What is the difference between logistic and logit regression? I understand that they are similar (or even the same thing) but could someone explain the difference(s) between these two? Is one about ...
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33 views

Are there local maxima in the standard 2-pl model or is there proof that there aren't?

I'm looking to use iterative logistic regression to find the parameter values of the 2 pl model: $ P = \sigma(\alpha_{i} (\theta_{s} - \beta_{i})) $ where $ \sigma(x) = \frac{1}{1+e^{-x}} $ I know ...
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Aggregating Standard Errors for Predicted Probability Estimates

I obtain predicted values from a logistic regression for a certain outcome (e.g., mortality) at the hospital level – the data is at the patient level – and need to compute the average across ...
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23 views

Logistic Regression - Non normal distribution

I have a computer science background & I am trying to teach myself stats by solving some regression problems I have some sales data which is gamma distributed(I guess) I can send this to a ...
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Diagnostics for multinomial and ordinal regression models

In the case of a binary outcome and a number of explanatory variables, logistic regression can be used and a number of diagnostic tools can be applied to assess the relative (e.g. AIC, if one wishes ...
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Estimate standardized coefficients (beta) using lm.beta() from package 'QuantPsyc' [migrated]

I want to estimate the standardized coefficients (beta) from a multiple linear regression object using lm() function in R. I use the lm.beta() function from the package 'QuantPsyc', but I do get a ...
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1answer
39 views

I am having trouble understanding (and implementing) logistic regression for classifying into three classes

(For reference, i am using Kevin P Murphy's Book "Machine Learning: A Probabilistic Perspective" and implementing with MATLAN - without any toolboxes) I have a dataset with 392 samples (rows), each ...
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254 views

Nonlinear vs. generalized linear model: How do you refer to logistic, Poisson, etc. regression?

I have a question about semantics that I would like fellow statisticians' opinions on. We know models such as logistic, Poisson, etc. fall under the umbrella of generalized linear models. The model ...
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How to approach logistic regression on skewed dataset [duplicate]

I have a dataset with about 1M negative examples and 4700 positive examples. I'm trying to create a classifier that tries to predict the % of an example being positive. Given how much the data is ...
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1answer
26 views

Compare Two Logistic Regression Models

I have worked out two models to fit the data (blue) - the first (in green) is the baseline model with the intercept only. The second (red) is the model with the intercept and 2 parameters. Obviously, ...
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multimodel inference when using rms package

I would be glad to have some advise about how to proceed with multimodel inference to obtain weighted estimates based on AICc after running ordinal logistic analyzes with "rms' package. I used the ...
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1answer
46 views

Probability to Likelihood

I have a problem on calculating the likelihood of observing a data point x given the predicted lable. My application is on text classification where I have to detect Spam and No Spam documents. I ...
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Multiple Class Logistic Regression Coefficents unstable when classes well separated

The following is a quote about the performance of Logistic Regression on multiple classes when the individual classes are well separated by the book ISLR: "When the classes are well-separated, the ...
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1answer
46 views

Effect of scaled down variables in Logistic regression

I have a logistic regression model with 5 continuous independent variables and a categorical variable. I scaled down one of the continuous variable using the formula Scaled_Value = NewMin_value + ...
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37 views

Change in objective function optimization - Regularization in Logistic Regression

If I have the objective function of Logistic Regression to optimize by maximizing it, would it change to a minimization problem when I add regularization term to it? Or can I still solve the ...
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38 views

Can factor analysis improve the fit of a predictive regression model?

My company is working with a client who have built a logistic regression model to predict whether kids with psychiatric disorders will successfully complete a State intervention program (Yes or No). ...
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Multiple logistic regression and public behavior

I'm trying to develop a model to forecast the behavior of the public... specifically, in horse racing. Most models in horse racing use whether or not the horse won as the dependent variable and then ...
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1answer
20 views

Wald test in logistic regression and its relationship to Z-statistic

If I have Z-statistic values in regression analysis, how can I convert them to Wald statistcs? Can Wald value be negative?
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Cost keeps on increasing in Multinomial logistic regression, instead of reducing

I am trying to implement multinomail logistic regression using gradient descent, following http://ufldl.stanford.edu/wiki/index.php/Softmax_Regression My data set has 7 ratings classes from 1 to 7. ...
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Plot one predictor and its quadratic term versus response variable (GLM binomial distribution)

I have the following model with four independent variables: Model_A <- glm(GRSP~ppt+tem+density+land+I(land^2), family=binomial()) When I plot the variable ...
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52 views

Multicollinearity among categorical variables - Is it normal?

I'm building a logistic regression model in which almost all of the input variables are categorical. There are multiple sets of categorical variables, for example, day of the week, age range buckets, ...
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Logistic regression variance [duplicate]

So far I have checked the tolerance value, VIF and condition indexes. But checking the variance of the regression coefficients I have to wonder: how little variance of the regression coefficient ...
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Model building and selection using Hosmer et al. 2013. Applied Logistic Regression in R

This is my first post on StackExchange, but I have been using it as a resource for quite a while, I will do my best to use the appropriate format and make the appropriate edits. Also, this is a ...
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How to measure classification accuracy based on presence only data?

I have a binomial GLMM which I calibrated with data on recreational visits (presence) compared with random controls where no visits were recorded (absence). I generated the controls myself, whereas ...
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Fitting a logistic curve to cumulative data using glm()

I'm trying to fit a logistic curve to cumulative data, derived from satellite imagery. Previously, I have point observation data which were either 0s or 1s. Os being 'forest' and 1s being ...
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Diagnostics for logistic regression and how to include/interpret interactions between categorical and continous variables?

I am working on a project that aims to identify the factors that affect the probability of detecting targets placed in different habitats in aerial photographs. I have done a lot of reading concerning ...
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1answer
46 views

Multilevel logistic regression with a random slope(s)

I would like to specify the two-level logistic regression model with random intercept and random slope. Dependent variable: hospitalization (1) or no-hospitalization (0). Independent variables: age, ...
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One model or 178 models?

I am doing a school project, where I am modeling next quarter's stock price using the information about the stock in the current quarter. The main goal is to see if we can find any statistically ...
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1answer
85 views

How to prove predictive use of a biomarker?

I have a binary endpoint (cured/not cured) and a continuous biomarker measured on each patient. Every patient recieved one of two treatments. The biomarker predicts the effect of the treatment, if ...
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How can I improve my sklearn logistic regression model

My objective is to classify sentences into useful (denote in boolean as 1) and not useful (denote in boolean as 0) categories. I have about 525 features where 300 features are the most frequent and ...
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51 views

How to apply a logistic + an OLS model to the same data set?

I have a data set measuring rock detection depths $Y$ based on the distance from some point of interests $X$, which are classified based on geophysical criteria. Each observation $Y$ is set after ...
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1answer
43 views

How to test main effects of categorical variables in a binary logistic regression including an interaction?

I measure two binary responses from each participant (ChoiceVA = V or A, AestheticOnly = 0 or 1). There are two experiments (between-participant). I want to test the following hypotheses: ...
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19 views

Logistic regression: Is it legitimate to exclude a main effect (part of interaction term) when predicting new values? [duplicate]

I have two main effects and an interaction term. The interaction (IsolateTemperature) term and one of the main effects (Isolate) is significant. The other main effect (Temperature) is not. I want to ...
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Logistic-Regression: Prior correction at test time

Using sklean.linear_model.LogisticRegression for a binary classification problem. My classes are unbalanced. The positive class comprises about 20% of the training set. When fitting the model I use: ...