0
votes
0answers
5 views

Predicting whether a potential sale will be won or lost

I am currently working on a project using a sales system and trying to come up with a way to use the current pipeline of potential sales to predict the amount of product that will be sold in the ...
0
votes
0answers
15 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. ...
2
votes
1answer
38 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 ...
0
votes
0answers
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 ...
1
vote
0answers
23 views

Logistic regression with multi-class features in R

I'm working with a data set like the following: X = ...
0
votes
0answers
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 ...
1
vote
0answers
20 views

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 ...
0
votes
1answer
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 ...
0
votes
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 ...
1
vote
0answers
29 views

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 ...
1
vote
0answers
16 views

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 ...
2
votes
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 ...
2
votes
0answers
38 views

How to use a parametric statistical test with R?

I would like to test the null hypothesis that all coefficients of my categorical variable with 4 Levels are really zero using Wald test & R. I'm new to the R family. And just have some problems to ...
-2
votes
0answers
16 views

Inference about relogit model

I have run the relogit model on my data. Given below are the deviance and AIC value. Can anyone help me to interpret these values that how good is my mode. ...
1
vote
1answer
35 views

multiple choice data simple logistic regression or multinomial logistic regression

I have a survey question where the respondent can check one choice or two choice maximum. Question looks like this: What is the more important characteristic when you buy chocolate? ...
0
votes
1answer
44 views

Dependent variable coding for logistic regression in R

Given the outcome variable in a dataframe is a factored/categorical variable, when regressing the dependent variable (DV) onto a set of independent variables (IVs), what is the model predicting? The ...
0
votes
0answers
21 views

Adjusting a Logistic Curve through R

I have data of certain proportion $p$ in a population. I need to approximate the behaviour of this population through a Logistic curve of the form: $p=\frac{1-e^{-\gamma t}}{1+ \alpha e^{-\beta t}}$ ...
0
votes
0answers
45 views

Logistic regression power analysis with moderation between categorical and continuous variable

I've been reading Simulation of Logistic Regression Power Analysis - Designed Experiments, http://sas-and-r.blogspot.com/2009/06/example-72-simulate-data-from-logistic.html, and Power analysis for ...
3
votes
1answer
114 views

Calculate a 95% confidence interval and p-value for the change in C-statistic using bootstrap with R

I am using boot() and boot.ci() to furnish confidence intervals for the difference in the $c$-statistic (AUC) between models ...
0
votes
0answers
31 views

Logistic Regression – Evaluation Metrics

I have more of a programming background, and I am fairly new to statistics. I am currently trying to solve some sample exercises to get more familiar with data science / modelling. Problem ...
1
vote
0answers
31 views

Logistic Regression doesn't converge if I use a particular baseline

Apologies if the question is too broad, then please close the thread. Or maybe this belongs in StackOverflow? I observed something strange and wonder if someone more educated can shed some light on ...
1
vote
0answers
50 views

Comparing ROC-curves

I would like to find if there is a significant difference between two ROC-curves. I've found the roc.test in the pROC package. However, I cannot seem to find any information on how this test is ...
0
votes
0answers
15 views

Weights in Cumulative Link Models - package Ordinal

I am running a cumulative link model on an ordered response variable that represents an assigned preference value between 0 and 4. The setup of my research is a questionnaire in which respondents are ...
0
votes
1answer
28 views

Predicting binary dependent gives non-binary predictions

I am trying to predict the result of an experiment (binary dependent variable) based on a number of continuous independent variables. When I do this using a largish model (9 main effects + 2 factor ...
1
vote
0answers
46 views

In an experiment w/binomial responses, some subjects gave the same answer for all trials. [How] can a Mixed Effects model (R's lmer) deal with this?

I recently ran a pilot of an experiment on Amazon's Mechanical Turk. In the experiment, participants read 5 items, and answered a yes/no question about each one. A between-participants factor was ...
3
votes
2answers
75 views

Removing attributes with few observations in R

I have roughly 15 variables / attributes characterizing 6k customers in my data set. As they are categorical I have transformed them into 1 attribute for each possible value (1-out-of-K coding). An ...
1
vote
0answers
47 views

Creating observed/expected ratio using logistic regression

I am using logistic regression to benchmark the performance of some students in different years. I created a scenario as below: ...
0
votes
1answer
62 views

Interaction in logistic models with R. Using * operator or create an interaction variable?

I want to test the presence of an interaction term in a logistic regression with glm(). The formula is: ...
2
votes
2answers
282 views

How to select a subset of variables from my original long list in order to perform logistic regression analysis?

My situation: small sample size: 116 binary outcome variable long list of explanatory variables: 44 explanatory variables did not come from the top of my head; their choice was based on the ...
0
votes
1answer
75 views

High p-values for logistic regression variable that perfectly separates?

I'm using R to run some logistic regression. My variables were continuous, but I used cut to bucket the data. Some particular buckets for these variables always result in dependent variable being ...
0
votes
0answers
73 views

“Convergence for 1st lambda value not reached”-error using GLMNET package and specifying lambda parameter

I get a weird problem when I specify lambda in the function glmnet, that does not appear if I let the function go through all the lambdas. When I run the following lines, it works great: ...
0
votes
0answers
21 views

Logistic Regression Performance on training data set V/s AIC

I am fitting a logistic Regression on data set having 700 variables (after Chisquare test) and 15000 rows. For that I did best subset analysis using glmulti package in R on first 70 variables and got ...
4
votes
5answers
462 views

Logistic Regression on Big Data

I have a data set of around 5000 features. For that data I first used Chi Square test for feature selection; after that, I got around 1500 variables which showed significance relationship with the ...
1
vote
1answer
59 views

Logistic regression: can weights be used as a predictor variable?

I counted the number of birds in a flock, which gave counts like these: ...
4
votes
2answers
109 views

Adding interactions to logistic regression leads to high SEs

I am trying to test whether there is a significant interaction between an ordinal (A) and categorical variable (B) in R using ...
4
votes
2answers
106 views

Plotting a categorical response as a function of a continuous predictor using R

I would like to plot the relationship between a binary categorical response variable and a continuous predictor to study its shape. The goal is to prep a logistic regression. This image may clarify: ...
1
vote
0answers
45 views

Binary Logistic Regression – Extremely Low Log-Likelihood Value

I am a novice statistician using R. I am running a BLR to determine the probability of good or bad sites to build a structure. Each location has a composite "score" that was generated from index ...
1
vote
0answers
53 views

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique?

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique? I have implemented this code using ...
1
vote
0answers
99 views

Frequency weights, rare events and logistic regression

I'm working on a model that requires me to look for predictors for a rare event (less than 0.5% of the total of my observations). My total sample is a significant part of the total population (50,000 ...
1
vote
1answer
102 views

Understanding R output in Logistic Regression

I am following an example here on using Logistic Regression in R. However, I need some help interpreting the results. They do go over some of the interpretations in the above link, but I need more ...
2
votes
0answers
51 views

If you know a factor is significant, what is a reason why R might think it's not? [duplicate]

I'm running a logistic regression model where anecdotally I expected age to be a very large factor. If you see from the charts I made in Excel before running the model through R, this is how the ...
0
votes
0answers
12 views

R Prefmod for paired comparisons

I'm trying to use the prefmod package to analyzed paired comparisons, but unfortunately the documentation is a bit poor and the author is no longer with us. I have a survey with 32 questions, split ...
2
votes
2answers
107 views

Evaluating accuracy of binary logistic regression on skewed data

I've been having an argument with a friend of mine, and it's very possible I'm wrong here. We are performing binary logistic regression on a dataset with 10000 observations, classifying action as ...
0
votes
0answers
31 views

How can I calculate ePCP and/or Brier scores for a mixed-effects logistic regression in R

I am trying to calculate ePCP and Brier scores in R for a mixed-effect binary logistic regression. It cannot seem to find any packages that work for mixed models. I have tried the packages OOmisc and ...
1
vote
1answer
59 views

About logistic regression in R

What I have is a medical data set with several variables, all 0-1 variables. I want to make inference about them with logistic regression. I have a few problems: I have location variables for the ...
0
votes
1answer
117 views

Logistic Regression in R - Steps and Output [closed]

I am doing statistics for the first time in my life and I am not quite sure what to include and how to interpret the results. I am doing a logistic regression in R. Here is what I have so far: ...
3
votes
1answer
91 views

How to interpret this residuals vs fitted plot for logistic regression using R

I am working on a logistic regression on some fundraising data where "gave" is a rare event (approx 3.5%). My current model has 64% accuracy on test data and an AUC of .604. When I run the standard ...
1
vote
1answer
109 views

Parallel logistic regression

I need to perform stepwise binary logistic regression (The horror! The horror!) on 1.5 million observations. This takes far too long in SAS, so I'm wondering if I can use R to process it in a ...
1
vote
0answers
65 views

Stata's xtlogit (fe, re) equivalent in R?

Stata allows for fixed effects and random effects specification of the logistic regression through the xtlogit fe and xtlogit re ...
2
votes
2answers
151 views

Difference between regression methods

I have a set of data where the response is a proportion. For each event in the experiment, a system will correctly tag X of Y ...