Questions tagged [logistic]

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

Filter by
Sorted by
Tagged with
0
votes
0answers
12 views

Do the covariates in a logistic regression model need to have a linear or log-odds relationship with the predictor?

Question is really in the title. In linear regression, the assumption is the covariates have a linear relationship with the dependent variable. So for logistic regression, is the assumption that the ...
0
votes
0answers
6 views

Which variable is better for prediction using different datasets

Suppose you want to predict a binary response variable $Y$ for which you decide to use a logistic regression. Now suppose there is a latent feature $X$ which you believe is very important for the ...
0
votes
1answer
23 views

Understanding Propensity Score Matching

I am trying to better understand the motivations and the applications behind Propensity Score Matching. I read the following that explains the motivations behind Propensity Score Matching: Suppose ...
0
votes
0answers
7 views

Variance contributions of random effects in mixed model

I am trying to understand how variables lead to persuasion and I have a within subjects design (people read messages from all levels (variable name: Level) ) of my IV and rate how persuaded they are (...
0
votes
0answers
26 views

Variable Importance in Logistic Regression

my question is related to this post using glm for logistic regression and scaling. My question is, why in the solution proposed by @gung - Reinstate Monica the chi-squared statistic obtained from the ...
1
vote
1answer
22 views

How to determine which user features are associated with conversion through a funnel?

I have a dataset of user demographics (i.e. region, age, gender etc.) and each step of a conversion funnel that each user reaches (i.e. site visit, placing item in cart, checkout page, purchase). I ...
0
votes
0answers
13 views

Bootstrapping average marginal effects in bonomial logistic regression

This is more of a theoretical question than a practical question, but I was wondering if it is common to bootstrap average marginal effects in R for a binomial logistic model? I assume it would make ...
0
votes
0answers
36 views

Binary Logistic Regression all binary categorical variables

I am running a binary logistic regression for my data using mini-tab. I feel as though I am doing something wrong because the p-values given for each of binary categories for an independent variable ...
-1
votes
0answers
14 views

The Realizability Assumption [closed]

I'm reading the the first chapter of Understanding machine learning from theory to algorithms: I do not understand the meaning of the following assumption: definition 2.1 (The Realizability Assumption)...
0
votes
0answers
19 views

How to deal with unbalanced binary independent variables in logistic regressions

Suppose I want to investigate the impact of some binary independent variables (let’s say: sex and height [tall/short]) on my binary response (alcohol consumption for instance). The distribution of my ...
2
votes
1answer
66 views

How many predictors can I include in my logistic regression model

If I am dealing with a small sample size (n = 48; n = 29 have disease vs n = 19 without disease), what are the maximum numbers of the predictors I can include in my multivariable logistic regression ...
0
votes
0answers
7 views

How to determine what predicted probability to use in the Risk stratification table?

I am new to the prediction model and would be very grateful for the advice regarding the likelihood ratio test. I want to construct a risk stratification table like the one in this study (see Table 4)....
0
votes
0answers
10 views

Minimal sample size or missing data requirement for Multiple Imputation by Chained Equations?

I am wondering whether I should use Multiple Imputation by Chained Equations for my sample size. I have a small sample (n=50) and there is one important predictor which I hope to include in my ...
2
votes
1answer
19 views

Lower bound and upper bound of beta estimate in regression is negative and positive, respectively, for each predictor

I have a logistic regression model as follows: dependent ~ var1 + var2 + var3 + ... + var24 The results of the model show some significant beta estimates, but the ...
0
votes
3answers
73 views

Is a logistic regression relevant to my problem?

Hi so for my proposal I plan on conducting a logistic regression but I'm not sure if it is the right method. My independent variable is a composite variable made up of 8 items, 4 reverse coded but all ...
1
vote
2answers
44 views

Binary predictors with very wide 95% CI in the Logistic Regression

When I fit a binary predictor in the logistic regression model, I got a high odds ratio and a very wide 95% CI (e.g. OR=11, 95% CI [1.5-229.5]; p = 0.041). My binary predictor is smoking status and my ...
0
votes
0answers
58 views

Average of a Variable vs. the "Average Effect' of the Same Variable in a Statistical Model

I am trying to better understand the difference between the Average of a Variable vs. the "Average Effect' of the Same Variable in a Statistical Model. To illustrate my example, I use the R ...
0
votes
0answers
16 views

Do you remove variables from a StatsModel logistic regression when you have a VIF of NaN?

I am building a logistic regression model to create a confusion matrix and decision tree. However, when checking for multicollinearity, I have a few variables that have a VIF of NaN. Do I remove them ...
0
votes
0answers
5 views

How to see the out of sample GLMNET LogReg results to build a confusion matrix? [migrated]

I would like to get the confusion matrix from all out of sample predictions when using glmnet logistic regression model with LOOCV. The simple example below uses data frame with 10 observations. Is ...
0
votes
0answers
19 views

Binomial GLM with Logit Link on Continuous Data given Frequency Weights [duplicate]

I'm wondering what R is doing in the background when given rate/proportion data and frequency weights. The Binomial GLM should only fit {0,1} data but the results still seem fairly accurate. Does it ...
0
votes
1answer
15 views

Multivariate logit: evaluate contributions of predictors to estimated probabilities

In a logistic regression with multiple regressors, is there a way to analyze the contribution of the predictors on the dependent variable? (e.g. how would one understand why did the probabilities ...
0
votes
1answer
14 views

Minimizing population risk for logistic loss

I am working on trying to show that the minimizer is equal to as given in this question. However, I can't this exact result and am starting to my book exercise has a typo. Here is my work:
1
vote
1answer
39 views

Estimating a conditional logistic model with hierarchical splines in mgcv leads leads to error "indefinite penalized likelihood in gam.fit5"

One can estimate a conditional logistic model in the R package mgcv by using the cox.ph family, which I have done successfully. I also estimated a logistic ...
0
votes
0answers
32 views

Cross-Entropy VS sum of Binary-Cross-Entropies for multiclass

Most of the classification models that I've encountered so far perform classification using CE loss. For example, if we have 2 possible classes and the GT class is 1, then: the CE loss will be $-\log{\...
1
vote
1answer
37 views

How to ask if correlation between two binary variables varies between groups in R

This seems like a simple coding/statistics problem, but I've been working on this and reading about it for days, and I just can not seem to wrap my head around it ... I am a biologist, not a ...
30
votes
4answers
3k views

Why is the exponential family so important in statistics?

Why is the exponential family so important in statistics? I was recently reading about the exponential family within statistics. As far as I understand, the exponential family refers to any ...
1
vote
1answer
55 views

Logistic LASSO regression model in R (glmnet) - predictions very close to 0.5 and bad misclassification error

EDIT: Earlier this question got closed because my question was not precise enough and really contained several questions. I have now tried to make the question more precise. I hope it's ok now. I ...
0
votes
1answer
27 views

Should we include a potential predictor into a prediction model if its P value is >0.05 but it improves AUC and/or model fit?

I am in the process of finalizing my logistic prediction model. However, I am not sure whether to include some specific predictors. I read about many papers and they left predictors in the final ...
0
votes
0answers
34 views

Calculating willingness to pay in mixed logit model with lognormally distributed price parameter

I am analyzing data from a discrete choice experiment (five attributes, including price attribute). For the mixed logit specification, I assumed normal distribution for the four non-price parameters; ...
0
votes
0answers
24 views

Diagnostic probability plots in logistic regression

There is some discussion on StackExchange about diagnostic plots for logistic regression, but all are focusing on "residuals", for which there is not even a consensus how to define them for ...
0
votes
0answers
18 views

Is it possible to conduct a coefficient test within a multiple regression?

In an analysis of employment, a difference in means test shows that gender is important. Multiple logistic regression using several specifications robustly identifies a positive coefficient on gender, ...
0
votes
0answers
21 views

Standard error of coefficients in Poisson Regression?

I see that with logistic regression that the standard error can be computed as in How to compute the standard errors of a logistic regression's coefficients which amounted to taking $\sqrt{(X^TVX)^...
0
votes
1answer
21 views

Probability Calibration of Statistical Models

I am trying to better learn about the Probability Calibration of Statistical Models . For example, if a Random Forest model is trained on a binary supervised classification problem : ...
3
votes
1answer
40 views

Interpreting logistic regression in R with huge OR: Strategies to interpret

My dataframe looks like this -> dput see at the end: ...
2
votes
1answer
59 views

Why not always use Polynomial Regression to solve classification problems? [closed]

Consider this simple classification problem: You can solve it using Logistic Regression. But there's another way. As @whuber noted in this answer, in hypothesis $h(x) = \frac{1}{1 + e^{-P(x)}}$, ...
0
votes
0answers
15 views

how run the k fold cross validation for ordered logistic regression?

I need to compare the unordered (multinomial ) logistic model and ordered logistic model and Poisson model to see which one fits better my data, I want to use k fold cross-validation. how should I ...
0
votes
1answer
32 views

Spline regression for binary dependent variables

I am trying to analyze the relationship between a discrete quantitative independent variable and a binary qualitative dependent variable. My hypothesis is that higher levels of the predictor promotes ...
2
votes
1answer
50 views

Why is my logistic regression outperforming neural networks?

I have 5 samples (each one contains ~380K records, 33 predictive variables and 1 binary Target): one sample is used to train the models the remaining 4 samples are used to validate the models The ...
0
votes
0answers
35 views

How to incorporate time element in logistic regression to build a failure prediction model?

I would like to build a model that can predict the probability of failure for individual components of a system. What I have is historical data of component failures recorded in the last 30 years. I ...
0
votes
0answers
10 views

Equivalence of different methods of multinomial logistic regression?

Suppose I have data $X \in \mathbb{R}^{n\times d}, Y = \{ 1, 2, 3, \dots k \}^{n} $, that is I have $n$ observations with $d$ features each, and each observation belongs to one of $k$ classes. Now I ...
1
vote
1answer
51 views

How can I calculate a beta regression prediction from the coefficients?

I have applied the R betareg function to my data using the default logit link and phi precision log-link for the categorical data. My equation is: ...
0
votes
0answers
14 views

How can you determine if the optimization process really found the hypothesis which minimizes learning error? What does it depend on?

I'm currently at a University studying data science. In one of our lab exercises there is a question which I wrote in the title: How can you determine if the optimization process really found the ...
0
votes
1answer
38 views

is the test dataset needed for cross validation?

I read about cross-validation and I want to fit ordered and unordered logistic regression models on my data and consider the performance of these models. should I split the whole dataset before doing ...
0
votes
0answers
27 views

How to produce to standardised regression coefficients in R for multivariable logistic regression

I am very new to R and epidemiology and am trying to create a model of how metabolic syndrome is associated with disease 'Y'. I have been asked to calculate a standardised odds ratio for the effect of ...
1
vote
0answers
41 views

Which formula to use for logistic regression with different predictors?

I'm doing a logistic regression with "Choice" (Yes or No) as dependent variable and 3 different predictors, including reward, demand (5 level each) and condition (0 or 1) and their ...
0
votes
1answer
24 views

R: How to fit a partial proportional odds model with vglm

I am trying to fit an ordinal regression model in R with the vglm function from the VGAM package. My dependent variable is Fnreports which is a factor with the ...
0
votes
1answer
28 views

How do I find coefficients for logistic regression manually-user defined function?

I got data from wikipedia. Hours show the number of hours each student spent studying, and Pass shows passed (1) or failed (0). Hours=...
0
votes
0answers
26 views

Interpretation of a regression coefficients plot

I am a noob of regression so this might be a very simple question. I have seen many plots of the regression coefficients but I am not sure how to interpret and make these plots. For example, below is ...
0
votes
0answers
30 views

Principal component Analysis using median as the center

Please I’m performing an analysis which requires data reduction technique. After preliminary analysis the data is suitable for principal component analysis and I’m comfortable using R but I want to ...
0
votes
1answer
91 views

Zero-inflated ordered logit model interpretation

Consider this Stata code and selected results: ...

1
2 3 4 5
149