0
votes
0answers
3 views

Strange GAM results, logistic regression

I am trying to fit a Generalized Partial Linear Model using the package 'gam' in R. I have one continuous predictor (EDUC) and 3 categorical predictors (MaxDem, SEX, HispAA). This is my model: ...
0
votes
0answers
30 views

estimate the log odds-ratio in R

I fit the logistic regression model for gender and drink for the data ihd using the following command ...
2
votes
1answer
122 views

Does fixing coefficients in a regression make sense, and if so how to do it?

I have a generic question about whether it might sometimes make sense to fix specific regression coefficients to predetermined values. And if this makes sense in particular cases, how do you best go ...
1
vote
3answers
47 views

Correlation using Logistic Regression and Pearson

I am so sorry, I am beginner in statistic analysis, I have project using R to analyze the correlation between dependent variables and independents variables. In this case I have two dependent ...
0
votes
0answers
11 views

package in R for BMA of a logistic model?

I am trying to perform analysis similar to Gerlach et al. (2002). it involves predicting the posterior probability of a particular binary outcome using the previous 5 observations. I was just ...
1
vote
0answers
17 views

geepack: parameter estimates change sign depending on correlation structure

I'm working on a dataset with the following variables: ...
0
votes
1answer
24 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
105 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
25 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
25 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
26 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
43 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
47 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
52 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
32 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
48 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
35 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
42 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
26 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
43 views

Logistic regression with multi-class features in R

I'm working with a data set like the following: X = ...
1
vote
0answers
29 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
36 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
96 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
36 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
22 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
81 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
44 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
53 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
59 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
161 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
42 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
36 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
63 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
20 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
37 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
53 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
84 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
67 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
299 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
86 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
110 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
23 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
527 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
63 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: ...