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

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Iinterpretation of coefficients of multiple comparisons in a logistic regression model

I'm confused about how to interpret coefficients in relation to the reference categories. I have two variables, A and M. A is a 3-level variable and M is a 4-level variable. The reference category for ...
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2answers
22 views

Research on debt recovery

My final year project is on debt recovery data for a debt collection firm. Data such as original/current balances,payments made,DOB, number of contacts made,whether or not a debtor has made insuarance ...
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14 views

Use of Deviance Residuals for Leave-One-Out Cross Validation

I am a newbie to stats and having some difficulties understanding how to use deviance residuals for leave-one-out cross validation for a logistic regression model. The problem that I am trying to ...
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32 views

How can I (Should I?) use logistic regression/the logit function to predict outcome of a tennis match in a simple simulator?

I am trying to create a tennis simulator. Specifically I am trying to make a 'random' simulator so that I can see how many times streaks of wins or losses occur, and then compare this to historical ...
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14 views

Conditional logistic regression model does not converge but logistic regression model does

I am running an analysis where I have 2500 cases and 2500 controls. The cases have disease A, and the controls do not. I am trying to see if having disease A increases the odds of various diseases. ...
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10 views

Using an odds ratio when data is sparse

Suppose I have around 20 exposures that potentially affect an outcome and I want to see which exposures have bigger impacts on the outcome. So I want to calculate each exposures' odds ratios by ...
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1answer
101 views
+50

How to evaluate fit of a logistic regression

I have a set of data points, which exhibit a solid linear correlation $r\approx 0.9$. I am basically plotting population in certain areas against the number of occurrences of a certain phenomenon (so ...
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1answer
37 views

VIsualizing the effect that only one predictor has on the outcome (R)

So I have performed a logistic regression on a data set with multiple predictors. I want to graphically represent the relationship between the outcome and only one of the predictors. What would be the ...
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13 views

How to calculate marginal effects for categorical covariates using mlogit in R

I am trying to use the mlogit package in R and have been following the vignette trying to figure out how to get the marginal effects for my data. The example ...
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binary logistic regression in spss version 22

I'm trying to run a Binary Logistic Regression. I have multiple IVs and 1 Binary DV. Can anyone show me how to do this with SPSS v.22? (or which one to select from this list) thank you
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23 views

Logistic regression with multi-class features in R

I'm working with a data set like the following: X = ...
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1answer
47 views

How to solve for the parameters in a logistic function? [duplicate]

I want to find the parameters of a logistic function. I read the guide here. It has a very clear explanation, but it did not have the final solution that I need. Now, we will consider a basis ...
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1answer
56 views

Great model prediction, but no significant variables

I am performing a binary logistic regression. I have developed a simple model which I am testing using the SPSS application. This first determines the predictive ability of a baseline model without ...
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1answer
11 views

Help with determining model for cross-sectional data where all variables are dummies

I am currently working on my dissertation project where my data are essentially all dummies. From my dependent to my independent variables, everything is a dummy variable (0,1), at least for the ...
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2answers
101 views

How to cope with missing data in logistic regression?

I'm investigating optimal bidding in auctions, and am using logistic regression to predict the probability of winning an auction given a set of explanatory variables (e.g. the price I bid, number of ...
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20 views

Constant RMSE margin between training and teseting set

I have a large number of independent datasets of varying size but same feature meaning. Features and outcome are both binary. I am trying to fit logistic regression to the data. I estimate ...
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18 views

Preconditioning the intercept for Logistic Regression

I am working on implementing a Logistic Regression model, using the newton-cg and lbfgs optimsers provided by scipy as the backend. I find the problems in which I fit the intercept, to be 50% slower ...
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13 views

Getting the rule from cross validation

I've got a question. Let's say I have a medical data representing 2 classes of patients (healthy and unhealthy) and some number of predictors which characterize these patients. Choosing different ...
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12 views

How to use regression analysis to set an optimal price

I am working on a side project with very small dataset where i am trying to figure out the optimal price i should set for a transaction fee (something like payPal). Currently i am using an arbitrary ...
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6 views

“Error in drop(y %*% rep(1, nc))” error for cv.glmnet in glmnet R package [migrated]

I have a function to return the auc value for a cv.glmnet model and it often, although not the majority of the time, returns the following error when executing the cv.glmnet function: Error in ...
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14 views

Weighing a variable based on distance to a known date

In a bankruptcy model, you want to assign a higher weight to a variable as a big event date approaches (such as a company's quarterly earnings announcement date) and you reverse this weighing as you ...
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39 views

Predicted probabilities from simulated betas and hypothetical data after conditional logit?

I'm working with conditional a conditional logit model to avoid bias that comes with FE logit models, when it comes to generating some hypothetical substantive effects, however, I run into trouble. ...
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Clarification on interpreting Wald's test and Likelihood ratio tests

I am running multinomial logistic regression analysis on my data. The response variable is the number of calves produced each year (0,1, or 2). I am trying to evaluate the influence of the X ...
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16 views

Softmax regression or $K$ binary logistic regression

For a multi-class classification problem, we can use $K$ binary logistic classifiers, or one softmax regression classifier, so how to make the choice between the two? IMHO, the $K$ binary logistic ...
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7 views

Use a different loss function for cross validation in liblinear

I am trying to learn a L2 regularized Logistic regression model in liblinear. I need a way to specify the C parameter which I do by cross validation. However, the loss/accuracy measure in cross ...
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Specifying the validation dataset for liblinear

I am trying to use the liblinear logistic regression model with L2 regularization. I don't want the training data to be splitted for the cross validation. I want to specify my own validation set for ...
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16 views

Cutoff Value in Logistic Regression [duplicate]

In R, the logistic regression output gives you predicted probabilities. Is there away of determining the threshold value $\alpha$, such that any $p > \alpha$ is classified as a $1$ and and $p \leq ...
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49 views

Is cross validation needed?

Suppose we have training data set and a test data set. The outcome variable is binary. Is it usually necessary to split the training data set so that there is a cross validation data set? Or can you ...
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63 views

What is the “Logistic Regression”? I cannot have a unified concept

I'm interested in logistic regression for modeling a classification problem. I tried to study logistic regression with two books, "Discrete Choice Methods with Simulation" (Train) and "Applied ...
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60 views

Logistic regression and error terms

In logistic regression, if we considered residuals, could they only take on the values $0$ or $1$? The data points themselves take on only $1$ or $0$. The logistic curve can take on any value between ...
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6 views

Liblinear logisitic regression with L2 regularization for classification

I am trying to use the liblinear library for logistic regression with L2 regularization. However, I am finding some issues with it. For eg when choosing the cost parameter, I chose the C parameter to ...
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9 views

How to improve results when using sampling in skewed binary classification?

I am using a data set with 18 features with True/False output (Related to mobile ad targeting). True values occurs only 0.4 % of the time. So, I have used sampling to keep the ratio of True and False ...
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1answer
21 views

What methods can be used to transform data?

I am solving a binary classification problem with 4 predictor variables. The variables didn't seem to be linearly separable. I have used Neural Networks and Kernel SVM which work and give desired ...
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1answer
46 views

Binary or Multinomial Logistic Regression in SPSS: Interpretation and Reference Categories

I am trying to analyze my data using Multinomial Logistic Regression whereby my dependent variable is a clinical outcome (sick vs healthy) and 1 independent variables (Factors) are in several ...
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20 views

glmnetcr - error in R - regularized continuation ratio logistic regression

I'm trying to run regularized ordinal logistic regression with glmnet.cr() on 28 predictors, a mix of continuous and categorical. Here are the relevant lines of ...
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19 views

How to deal with a skewed class in binary classification having many features?

I am doing data analysis in the mobile ad targeting domain. I have around 18 features and for a combination of these features, the result is either True or False (1/0) depending on whether the ...
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2answers
52 views

High model fit but no significant impact of any of the predictors

I am applying binary logistic regression as my dependent variable is a dichotomous variable with 740 sample size. I have used enter method to input my variables and have designed two blocks. In block ...
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1answer
93 views

modelling data that contains only ones and zeros

I'm new to modelling this type of data, and I got punished for asking this on stackoverflow... I have a dataset where the predictive variables contain only ones and zeros, and the response variable ...
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26 views

Interaction in a repeated measures logistic regression

I want to test for the effect of interaction between two variables using a repeated measures logistic regression but I don't know how. I am using Stata and the following lines: ...
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31 views

multinomial logistic regression with alternative specific variables

I am working on a multinomial logistic regression problem which involves features from the dependent variable. It might be better to describe the problem by using the example in mlogit mlogit manual ...
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26 views

How to use the delta method with location and scale parameters instead of intercept and slope?

I'm doing some failure time analyses where I'm trying to determine a failure rate function, and use the delta method to determine a confidence interval for the time when 25, 50%, etc. failure occurs. ...
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8 views

Interpreting the marginal effects in terms of standard deviations

I have a very simple logistic regression in which the binary variable Y is regressed on three continues variables, X1 and logX2 and X1*LogX2. X1 is a proportion (is between 0 and 1), logX2 is the ...
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Strategy to deal with rare events logistic regression

I would like to study rare events in a finite population. Since I am unsure about which strategy is best suited, I would appreciate tips and references related to this matter, although I am well-aware ...
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Odds ratios from logistic regression on subsets of data using R

I have 15 subjects each with 200 trials & I'd like to run separate regressions for each subject. If I just run the regression on the whole dataset I am able to generate odds ratios / confidence ...
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1answer
47 views

Why use chi-square (or other) statistic over regression modeling for 2x2 contingency tables?

I have a question regarding the use of logistic/log-linear regression vs. contingency test statistics, such as chi-square. Can someone explain to me why it would ever be preferable to use test ...
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How to obtain estimates for all levels in a mixed effects model that uses effect (deviation) coding?

I am running a binomial mixed effects logistic regression in R using glmer for a sociolinguistics project. I was asked to used deviation (effect) coding. From what ...
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2answers
63 views

How to quantify the Relative Variable Importance in Logistic Regression in terms of p?

[I already searched the site and I could not find the answer to this question] Given a simple example: A logistic regression model is used to predict whether an online shopper will purchase a ...
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1answer
40 views

Variance Covariance for logit with elastic net

How do you calculate an estimate for the variance covariance matrix of a logistic regression with elastic net regularization? Starting from the variance-covariance matrix of a plain vanilla logistic ...
2
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1answer
47 views

Exact logistic regression, R, and elrm: data formatting and output

I use SPSS, but am forced to use R for exact logistic regression. So I'm brand new to R (and hating it so far) and also new to logistic regression. I've read the original elrm paper and looked at ...
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Is multiple logistic regression the right choice or should I use univariate logistic regression?

I have a set of data (~ 90 cases) and an outcome of a diagnostic test. I have collected factors that were determined before the test that could predict the outcome of the test. Now some of the data ...