Tagged Questions

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

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43 views

How can I remove multicollinearity from my logistic regression model?

I am working on Sales data. i have binary variable win/loss the opportunities and rest are the activities done by sales force (sales guys) with 40+ variables (different types of activities done for ...
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1answer
25 views

How to analyze elastic net fitted model coefficients

SOLVED: an elastic net model, as any other logistic regression model, will not generate more coefficients than input variables. Check Zach's answer to understand how from an (apparent) low number of ...
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11 views

Categorical Variables - Factor Reduction - Can I use the dependent variable?

I am working on a basic fraud detection model. I have about 10 independent features and I am trying to predict if a given transaction is genuine or fraud. Most of the features are categorical and each ...
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1answer
30 views

Which p-value to report in a comparison of different logistic regression models using marginal effects?

I am running logistic regression models to compare the impact of different indicators using Stata. As these comparisons may lead to false conclusion due to confounding and rescaling if log-odds or ...
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13 views

Negative binomial instead of ordinal logistic?

I have data with one metric and a discrete outcome that I'm trying to estimate the probability of. The outcome is a count, but it's a safe assumption that the increments aren't i.i.d. I thought an ...
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1answer
20 views

Missing factor levels after logistic regression glm()

I am quite new in the R universe, so please excuse me if the question is too simple.. I would like to perform a logistic regression on a marketing data set (only categorical variables), of the form ...
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18 views

How to report mixed effects logistic regression

I have several models predicting different binary outcomes as a function of time (binary variable: before/after intervention) and age (ranges 4 to 14), measured in different students within different ...
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3 views

Multiple binary dependent variables

I want to model multiple binary outcomes with some predictors. Does MANOVA can handle this or is there any other techniques I can use? Thanks !!!
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241 views

Was this the appropriate regression model?

I was recently proof-reading a friend's thesis (for their writing, not stats usage) when I came across a usage of a regression model which I would regard as incorrect. However, I'm pretty new to the ...
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51 views

Multinomial logistic regression does not match actual data

I was wondering if someone with experience running multinomial logistic regression could look at my data file and results, and explain why the results turned out the way it did. The background: I've ...
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1answer
72 views

Unintuitive interpretation of probabilities when doing logistic regression

The observations in my dataset can be split in two classes. The observations in class 1 are for sure correctly labeled. The observations that has been designated to class 2 have a huge percentage of ...
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28 views

Ratio of Odds Ratios?

How would one compute the ratio of odds ratios for unlinked (but theoretically overlapping samples)? I basically have one dataset that can be considered my "population" or "universe" of data, and ...
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8 views

multilevel mediation with a proportion dependent variable sem

I am attempting to test an indirect path in a multilevel dataset with an outcome that is a proportion. The data are a collection of variables related to various qualities of potential support ...
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36 views

R Logistic regression model - Error

I'm trying to run following command in R, but I'm getting an error ! any one could help and explain a reason for that ? ...
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2answers
91 views

Logistic Regression sample size & bootstrapping

The data for this example can be retrieved here so that you can reproduce these estimates. It is the low birth weight dataset- http://www.umass.edu/statdata/statdata/data/ There are 59 1's and 130 ...
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1answer
51 views

How to check linearity in binary logistic regression with many covariates having 0 as a value

I'm trying to check linearity in my binary logistic regression. According to my handbook (Discovering Statistics Using SPSS, by Andy Fields: ch.19.8.1) this should be done by adding var*log(var) to ...
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1answer
43 views

Linear model decomposition

Is is possible to decompose fitted linear model? What I mean by that: I have parameters of fitted linear model as following: y=2.3a-1.23b+1.65c+1.76d Now I have ...
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23 views

Possible to code contrasts comparing each level to grand mean with no reference category?

I'm working on a health care outcome regression model using the deviation contrast scheme described on the UCLA SAS help page here for a collection of dichotomous predictor variables measuring medical ...
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21 views

Shortcomings of logistic regression [closed]

I've recently started exploring logistic regression for modeling purposes and well... it's just performing pretty poorly. Apologies for a very broad question, but I just can't figure out why! Here's ...
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16 views

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

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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29 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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1answer
216 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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29 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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49 views

Logistic Regression: determining significance of independent variables [closed]

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
39 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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2answers
42 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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0answers
49 views

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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1answer
40 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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1answer
29 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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16 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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41 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
99 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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34 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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12 views

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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24 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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15 views

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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6 views

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 ...
1
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1answer
42 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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1answer
269 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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14 views

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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4 views

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
47 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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0answers
22 views

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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41 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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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). ...