Tagged Questions

2
votes
0answers
30 views

Variable selection / Dataset reduction for large datasets (in R)

I'm working on a behavoural scorecard modelling exercise, and many of the decisions taken to date have been based on the experience of a consulting credit analyst (whose experience software-wise is ...
0
votes
0answers
26 views

Confusion matrix with low incidence rate

I am trying to use a binomial regression to predict customer churn. A reproducible example is below. In the example, there is about 5% latent attrition and customers with a price above 200 have a 15% ...
2
votes
0answers
24 views

Generate predictors with fixed predictive validity in R

Let's say I have a dataset: x=rnorm(1000, mean=0, sd=10) I would like to create five variables (a,b,c,d,e) that I can use to ...
1
vote
0answers
22 views

Nested vs. conditional logit regression

I am trying to estimate a logit regression model with travel mode choice (categorical) being the dependent variable; explanatory variables include age (categorical), income (categorical), gender ...
2
votes
0answers
32 views

How to report most important predictors using glmnet?

I want to find the most important predictors for a binomial dependent variable out of a set of more than 43,000 independent variables (These form the columns of my input dataset). The number of ...
0
votes
2answers
40 views

How to detect a quasi separation problem for a data set?

Suppose that we have a two-column data set. One column consists of a hundred x=0 and a hundred x=1, whereas the other one consists of y's (1 or 0 response). Besides, suppose that the P(Y=1|X=0) = ...
-1
votes
1answer
44 views

Methods For Estimating Trend in R [closed]

Do you know how i can get a code for estimating trend by Mitcherlich and logistic method in R?
0
votes
0answers
21 views

Measure the relation/association between the outcome and the independent variables

I am running a model (logistic regression) with 20 independent variables in R. Before running the model I calculated the correlation between all the variables and finally selected my variables by ...
0
votes
0answers
29 views

Restricting model parameters in logistic models in R

Is there any function in R that can solve the problem like this in SAS? Thanks in advance!
1
vote
0answers
24 views

account for spatial autocorrelation with a binomial regression model

I am using a binomial regression model for presence/absence, with 20 independent variables to test. The data has x and y coordinates and I would like to understand how can I take into account the ...
0
votes
0answers
50 views

Using R in Java Project

I hope this question is not off topic on CV: I am currently fitting some different models (naive bayes, logistic regression...) in R which I up to now thought of as prototypes for a later Java ...
1
vote
1answer
48 views

How do I conduct a simulation using a logistic model with multiple covariates using R?

I'm investigating the asymptotic normality of the estimators of the logistic model. I wish to do a simulation to show that the standard error decreases as sample size n increases. Assume i have ...
3
votes
1answer
46 views

Recreate logistic regression equation from table of odds data

I'm reading the technical manual for a linking study between two assessments. It's pretty clear that the table is model output from a fitted logistic regression equation. Here's what pass odds look ...
4
votes
1answer
187 views

Meaning of p-Value of logistic regression model variables

So I'm working with logistic regression models in R. Though I'm still new to statistics I feel like I got a bit of an understanding for regression models by now, but there's still something that ...
1
vote
0answers
55 views

How to implement a fractional polynomial transformation in R for logistic regression

I'm working on a data set modeling road kills (0 = random point, 1 = road kill) as a function of a number of habitat variables. Following Hosmer and Lemeshow, I've examined each continuous predictor ...
1
vote
1answer
142 views

How to interpret statistics (Emax, D, U, Q, B, etc.) of bootstrap validation of logistic regression

I'm only a linguist, so my knowledge of statistics is very basic. I fitted a logistic regression model with R (with lrm(formula, y=T, x=T)), and when I use the ...
0
votes
0answers
43 views

Adding Predictors to a Logistic Regression Model

I am trying to understand how to add further predictors to my logistic regression model and still use the model coefficients to determine the predicted probabilities. ...
0
votes
1answer
97 views

How are the p-values of the GLM in R calculated?

I have been running some binomial logistic regressions in R on a data set and I realised that the p-values of the estimated coefficients are not computed based upon a Normal distribution. For e.g. I ...
0
votes
2answers
163 views

Binomial GLM and different sample sizes

I have a data set which consists of binomial proportions, let's say the success rate of converting a customer depending on the advertisement, the customer age, and various other factors. For some ...
0
votes
0answers
146 views

Using lme4 for case-controlled logistic regression?

I would like to use lmer for a conditional (or case-controlled or matched pairs) mixed effects logistic regression. However, I am not aware of any published use of ...
1
vote
0answers
104 views

Is conditional logit a specific form of GLM? And what are its specificities?

Background: For a project, I am fitting a conditional logit model where I have 5 control cases for every realized case. To do that I use the clogit() function in ...
0
votes
0answers
72 views

Compute categorical variable importance for logistic regression

I am dealing with huge(2 lac rows = 200,000 rows) dataset with a combination of categorical and numerical variables for predicting binary values. My data set format looks like : ...
0
votes
1answer
53 views

Getting a data frame of logit probabilities and their confidence intervals

I have the following model and have used the effects package to plot the predicted probabilities and the confidence interval lines. However, I was wondering how I'd go about spitting out a data frame ...
1
vote
1answer
98 views

How to validate and compare models predicting a binary variable?

I have a question about determining which models are "better" and how to assess that info. Let's say I have three models, each which predicts our bid on won ping. Our bid is a continuous variable and ...
0
votes
1answer
137 views

Simulating data for logistic regression with a categorical variable

I was trying to create some test data for logistic regression and I found this post How to simulate artificial data for logistic regression? It is a nice answer but it creates only continuous ...
2
votes
1answer
186 views

Logistic Regression - Bayesian Approach - Assessing Classification Precision

I have recently begun to read about bayesian statistics and I am playing around with the R2WinBUGS package. I'm trying to fit a logistic regression to the spam data (that can be found on the webpage ...
7
votes
1answer
253 views

Understanding the predictions from logistic regression

My predictions coming from a logistic regression model (glm in R) are not bounded between 0 and 1 like I would expected. My understanding of logistic regression is that your input and model parameters ...
0
votes
0answers
286 views

Intepretation of crossvalidation result - cv.glm()

My logistic model has been suspicious due to enormous coefficients, so I tried to do a crossvalidation, and also do a crossvalidation of simplified model, to confirm the fact that the original model ...
2
votes
2answers
326 views

What is the difference between logit-transformed linear regression, logistic regression, and a logistic mixed model?

Suppose I have 10 students, who each attempt to solve 20 math problems. The problems are scored correct or incorrect (in longdata) and each student's performance can be summarized by an accuracy ...
0
votes
1answer
100 views

How do factor categories with no variance influence logistic regression?

I'm modeling the effect of a categorical predictor on a binary dependent variable using logistic regression. I'm comparing models with/without the predictor using a likelihood-ratio test. Two ...
3
votes
1answer
350 views

Power calculations, logistic regression with continuous exposure--cohort

I'm trying to estimate power in a logistic regression with a continuous exposure in a cohort study (ie, the ratio of the sampling probabilities is 1). I have population cumulative incidence ...
2
votes
0answers
91 views

Variable selection with restricted cubic splines

Is there any function in R for doing variable selection (backward elimination) in a multiple logistic regression using restricted cubic splines like mvrs procedure for STATA?
4
votes
1answer
197 views

What's the most pain-free way to fit logistic growth curves in R?

This isn't as easy to Google as some other things as, to be clear, I'm not talking about logistic regression in the sense of using regression to predict categorical variables. I'm talking about ...
-1
votes
1answer
127 views

Logistic Regression with holdout sample [closed]

I am trying to run a logistic regression in R on my data where my independent variables are 13 continuous variables and my dependent variable is binary. I want to segment my data so that I train on ...
1
vote
1answer
77 views

Simple way to fit large number of single factor logistic regression models in R - automatically

I have a dataset with one binary target variable called “target” and many many factors “F1”, F2”… “F200”. I’m trying to come up with code to fit 200 single factor logistic regression models and return ...
2
votes
2answers
485 views

Plotting logistic regression interaction (categorical) in R

Hello I have the following logistic model with a categorical variable interaction which I wish to plot in R but I am struggling to find any solutions - ...
4
votes
1answer
533 views

How to simulate artificial data for logistic regression?

I know I'm missing something in my understanding of logistic regression, and would really appreciate any help. As far as I understand it, the logistic regression assumes that the probability of a '1' ...
1
vote
1answer
370 views

Determining which variables have been dropped using cv.glmnet in R

I have a large amount of vegetation data that has been broken down into 13 habitat classes. I am trying to determine which vegetation tends to fall into or is absent from which habitat with any sort ...
1
vote
0answers
54 views

Model for multivariate ordered categorical data with a time-varying continuous covariate

I would like to develop a model for multivariate ordered categorical data that also allows inclusion of a time-varying continuous covariate. This is for different types of adverse events, that can ...
14
votes
1answer
410 views

Logistic regression in R resulted in Hauck Donner phenomenon. Now what?

I'm trying to predict a binary outcome using 50 continuous explanatory variables (the range of most of the variables is -∞ to ∞). My data set has almost 24,000 rows. When I run glm in R, I get: ...
0
votes
1answer
88 views

Interpreting Logit Interaction Term Coefficients (continuous * categorical)

I have the following output from a logistic regression model. ...
0
votes
1answer
53 views

Implementing a Logit Model With Multiple Predictors

Let's say I have the following equation: Won = B0 + B1*(Bid) Once I know B0 and B1, I can generate the probability curve and find the probability of "won" for ...
0
votes
1answer
429 views

Interpreting multinomial logistic regression output in R

I am trying to perform multinomial logistic regression on my data which is as below(just the header). "category" is my target variable and all other variables are independent variables. category has ...
0
votes
1answer
499 views

Interact categorical variables in GLM in R

I am trying to predict child nutrition (binary) using a set of variables. The two that I want to interact are maternal education (none, primary, middle, HS) and wealth quintile (1,2,3,4,5). Thus far ...
2
votes
1answer
420 views

Percent correctly predicted of logit model

Is there a standard way to report the percent correctly predicted when predicting a binary outcome? Using glm in r, the results are predicted probabilities. However, in order to make a comparison to ...
1
vote
1answer
461 views

R: mlogit error on data - “system is exactly singular”

So I have data from a randomized blind trial of 1mg of nicotine gum on dual n-back working memory scores; I analyzed them as usual with a t-test and found a small increase in means but a large ...
2
votes
1answer
130 views

Logistic regression-like model for non-discrete outcomes

If I have a set of continuous predictors $X$ and a binary outcome $Y$ and I wanted to build a predictive model of $P(Y|X)$, I would start with a logistic regression model. However, in my particular ...
0
votes
1answer
128 views

Checking the regression model's performance

I am R-tool beginner. I have a question regarding how to know the performance of a linear regression model by using validation data. My approach was Create training and validation data sets from ...
0
votes
1answer
131 views

Logistic Regression model keeps kicking out 1 dummy

I have a dataset in which each row belongs to one of 8 categories. I'm running a logistic regrssion on it using R. I created dummy variables for each of these categories. In my logistic regression ...
0
votes
2answers
65 views

logistic regression always yielding increasing f'n when should sometimes be decreasing (using R)

I'm modeling a set of outcome data the depends on two parameters: time, T -100 < A < 100 I've done logistic regression using R with the command: ...

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