1
vote
0answers
8 views

geepack: parameter estimates change sign depending on correlation structure

I'm working on a dataset with the following variables: ...
0
votes
0answers
14 views

Measures of goodness-of-fit using multiply imputed data in Zelig

I am running a logistic regression model in R using multiply imputed data created using Amelia II, which I am then analyzing using Zelig. I would like to be able to report some measures of ...
7
votes
3answers
89 views

testing logistic regression coefficients using $t$ and residual deviance degrees of freedom

Summary: Is there any statistical theory to support the use of the $t$-distribution (with degrees of freedom based on the residual deviance) for tests of logistic regression coefficients, rather than ...
0
votes
0answers
19 views

Is there a way to customize my likelihood function for logit models using speedglm/biglm/glm packages?

My goal is to fit a custom logistic regression/survival analysis function using the optim/maxBFGS functions in R and literally ...
0
votes
0answers
16 views

Fitting mixed effects logistic regression with random effects

I have a data frame of 134 observations, 9 independent variables, and a binary, categorical response; please see its structure below: ...
0
votes
0answers
17 views

How can i make a fraud detection dataset (I have the data ready but unordered)

I'm a little confused with the creation of the dataset for a fraud detection predictive model. Here i put a link with a sample of the dataset that I made. (the real dataset have ~950.000 clients). ...
0
votes
1answer
38 views

Binary logistic regression with interaction terms

I have been reading several CV posts on binary logistic regression but I am still confused for my current situation. I am attempting to fit a binary logistic regression to a series of continuous and ...
1
vote
1answer
46 views

Standardized beta for logistic regressionin R

For my survey data analysis, I ran an Ordinal Logistic regression using the 'polr' function. The summary of the regression is as follows: My question is: Do I need to standardize my beta values? ...
0
votes
0answers
49 views

Is this a case for an ordinal logistic regression? Problems interpreting output

I'm a beginner in statistics and R, sorry if this question may seem trivial. I've collected data measuring several different parameters in 40 subjects at two time-points (t1 and t2). There are 3 main ...
0
votes
0answers
21 views

logistic regression using probabilities of class labels

My goal is to train a logistic classifier. My samples in my dataset have some label noise but for each label I can give a probability how correct this label is. What is the best way to incorporate ...
0
votes
2answers
44 views

Multinomial logistic regression with geepack in R

I am working on fitting a GEE model to a multinomial logistic outcome using the R package geepack. My understanding is that the package uses ...
2
votes
1answer
37 views

Using proper scoring rule to determine class membership from logistic regression

I am using logistic regression to predict likelihood of an event occurring. Ultimately, these probabilities are put into a production environment, where we focus as much as possible on hitting our ...
0
votes
0answers
16 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
23 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
41 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
22 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
30 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
23 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
29 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
95 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
34 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
18 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
67 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 ...
1
vote
1answer
41 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
49 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
58 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
152 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
37 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
34 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
60 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
19 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
36 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
49 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
83 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
56 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
65 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
292 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
79 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
97 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 ...
5
votes
5answers
501 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
62 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
112 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
129 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
48 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
60 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
111 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 ...