All Questions
Tagged with predictive-models logistic
306 questions
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Taking the sum of predicted probabilities from logit model?
I am using a logit model to predict the probability that students pass a particular course. I run the logit, generate predicted probabilities for the students in my sample, and want to compare the ...
3
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1
answer
167
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How to use and interpret results from glmer() in R, when the predicted risks are lower than observed
I previously asked this question on stack overflow, but was redirected here.
I have a dataframe of patients, with an outcome of cancer flagged, and other variables to be used as covariates (around 20 ...
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0
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23
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Mixed-effects logistic model generating lower predicted values than observed in R [duplicate]
I have a dataframe of patients, with an outcome of cancer flagged, and other variables to be used as covariates (around 20 of these). The dataframe is made up of multiple cohorts which are flagged in ...
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31
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Intercept calibration in logistic hierarchical regression model
i am following Debray et al. 2013 (A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis) to estimate a risk prediction ...
- 165
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30
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Are diagnostic tests and clinical (risk) prediction models in medicine essentially the same thing?
In medicine, are diagnostic tests (e.g. covid test, HIV test, ...) and risk prediction models essentially the same thing? If not, in which aspects do they differ (from statistical point of view)? ...
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17
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Logit model not predicting any values < 0 despite class imbalance
I am building a logistic regression model to identify potential channelling factors that predict whether a patient will initiate of one of two antidiabetic drug classes at a specific stage in their ...
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39
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Logistic regression for win probability: parameterization
I am modeling the outcome of baseball games using a logistic regression. I am struggling to understand the results of the analysis, and I believe this relates to the parameterization of the model. ...
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33
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Improving a logistic regression where multiple signals separately yield the same accuracy, and combining them does not improve the model
I have a logistic regression that estimates the probability of an event occurring. There are roughly 10,000 data-points, and I have roughly 20 model features. The model features are each quite ...
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54
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Understanding PRIOR option in SCORE statement for PROC LOGISTIC (SAS)
Say I have a binary response which I want to model with logistic regression on covariates $x$. Fitting a model with PROC LOGISTIC will fit MLE coefficients for the model
$$
\text{logit}(\pi) = \alpha +...
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69
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Predicting current area-level counts from repeated cross sectional presence/absence surveys
Problem statement
I’m trying to predict the “current” distribution of wood-burning fireplaces at ZIP code level across 9 California counties based on 15 years of surveys with presence/absence data on ...
- 101
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31
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Logistic regression with a lot of predictors/ general understanding
i'm currently planning to write my bachelor thesis but it's been a while since my last statistics seminar, i'm extremely rusty and so any guidance here would be appreciated.
I have a relatively small ...
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76
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Abnormally large confidence interval with binomial gam when p->1 at max of predictor range
I am running a gam (mgcv in R) to model a non-linear effect of time on a binomial reponse (positive or negative sample). This is a minimal example of such a model:
...
0
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1
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34
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Predicting binary outcome when predictor variable increases
Suppose I have a simple dataset of numerous observations, each with a continuous numerical variable $x$ and a binary numerical variable $y$ (with values 0 for unsatisfactory, 1 for satisfactory).
How ...
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2
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70
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Chi-Squared for demonstrating confounding in Logistic regression (or not...)
I am using logistic regression for inference and classification, using data from 190 X-rays/subjects. We want to see if certain X-ray measurements could predict development of a disease (Case vs ...
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1
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98
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How can I calculate residuals of a dependent binary variable, using a glm (logistic) model that was fit on a different sample?
I have a data frame D1 in R with a dependent binary variable Response (0/1) and a set of covariates like age and gender. I want to know how "typical" ...
3
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2
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77
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How can I assess case-level uncertainty of classification using logistic regression?
I'm hoping to fit a binary logistic regression to be used to predict the binary outcome for new cases/observations. I'm wondering if there is any way to gauge uncertainty of a prediction for ...
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31
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compare the outcome of logistic regression (predictive probabilities) before and after an event
To train a glm model, I'm using using clinical data (~10 features) of a large cohort of patients and healthy subjects. I'm using a smaller test group (around 20 people) and predict their outcome (...
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3
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2
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543
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Variable selection in logistic regression [duplicate]
So I'm trying to make a multivariate logistic regression model in R studio. I'm not sure how to go about this. What seemed to make sense to me was to model every predictor against the response ...
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2
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262
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Can I perform logistic regression or any other type of regression on this dataset?
My data set contains information regarding the number of road accidents separated by gender, age, area, and other factors. Can I perform logistic regression analysis using this dataset to predict how ...
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2
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0
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18
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Obtaining Marginal Forecasts
I am trying to make predictions on a dummy variable. What I am predicting is whether or not a separate variable ever changes from a zero to a 1 in a year from the observation date. The dummy variable ...
2
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1
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1k
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Imbalanced classes and possible ways to increase precision, recall and f1-score of the prediction model
I've just started my data science internship, and this is my first time in the field. I'm sure I'll face challenges in the future where I might need your help. It's also my first time asking a ...
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2
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203
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Statistical tests for knowing the effect of a campaign on sales
I am currently working on my very first real life Data Science problem and I am facing a bit of a challenge in formulating the solution.
The question is to find out if conducting a campaign has an ...
1
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1
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174
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Analyzing importance of continuous and categorical variables in linear regression in R
I am using R. I have a data set with a binary (0,1) response and both continuous and categorical predictors. I would like to test the overall importance of these predictors one by one, and I am ...
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48
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The meaning of an explanatory variable in computing accuracy of a prediction model
I am following the logistic regression predictive modeling example found here, chapter 10. To the pred object the variable ...
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4
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2k
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Is Logistic Regression a classification or prediction model?
In this forum, there are opposite opinions(1), (2) on the uses of logistic regression. Ones say, it is a classification model and others say it is a prediction model.
Therefore, the question that I ...
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168
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Binary logit regression - specificity vs sensitivity
I have a dataset of 393 people and I am running binary logit regression. The goal of this regression is to examine which predictors are significant in predicting the dependent variable.
The dependent ...
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1
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1
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219
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Actual proportions vs predicted probabilities in Logistic Regression over trained model
I am running a Logistic Regression model on a very upsampled data (upsampled by repeating certain observations). It appears that the expected predicted probabilities of majority class for certain cuts ...
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3
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2
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579
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Finding better machine learning model for default prediction
I have two logistic regression models, model 1 and model 2. I want to find out which model is better. I'm predicting the default rate. I have compared the two models using Gini, plotted gini on month ...
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1
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176
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Using logistic regression vs Cox regression
Say I am interested in looking at the 5 year occurrence of an serious adverse drug reaction including mortality occurring in a group of patients being treated for a disease.
I would imagine that ...
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0
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23
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Predict the prevalence of a characteristic in a group
I've got sample data of the prevalence of a certain characteristic in two different groups, with prevalence in group 1 being 65% and prevalence in group 2 40%:
...
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174
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Why does my logistic regression model over predict for certain groups and under predicts for others?
I am running a logistic regression model to predict whether a particular business location would purchase from a company X. I have a few predictor variables related to the business location, ...
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44
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Election Predict Using Machine Learning
I want to predict the election results in a country. Firstly I want to check and specify probabilty. For doing this, I intend to use the election results of the past years and the estimation results ...
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0
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380
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Interpreting logistic regression interactions predicted probability versus logit
I have a logistic regression, and I am interested in the interaction between two categorical variables: one (let's call it A) is a continuous variable categorized in 20 quantiles, the other (B) is a ...
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164
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Can I use logistic regression from individual-level survey data to make predictions at an aggregate level?
I have a logistic regression model that predicts the likelihood of an individual getting PTSD after a flood based on their race and gender. The regression is based on a survey of individual flood ...
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220
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Best way to perform logistic regression for two dependent variables simultaneously
Explanation:
Lets say we have a dataset, df with 'n' columns/variables. Two of 'n' variables are named as Case 1 and Case 2. Case 1 and Case 2 are categorical variables with value levels "Low&...
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84
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Why predictions are non-linear in logistic regression and are they interactions?
Consider this logistic regression on the Titanic dataset, with two predictors (one factor, Pclass and one continuous, ...
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399
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What is the proper way to compute predicted probabilities in a fixed-effects logistic regression?
Predicted probabilities are quite helpful to interpret the output of logistic regressions. One can compute a predicted probability as follows:
$$
P = \frac{exp(\beta + \beta_0)}{1 + exp(\beta + \...
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2
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1
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4k
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Logistic Regression on multiple classes (Shouldn't it be only on binary?)
I'm a bit confused with the usage of logistic regression for multi-class classification. My understanding is that a logistic regression is dichotomous (two possible classes), so in the example of the ...
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1
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1
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80
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Logistic regression predictions dont work
I have this problem with logit, that when I want to create confusion matrix, it simply displays the real values in the first row and in the second row, there are never any numbers. I created a lot of ...
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0
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99
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Ranking probabilities of logistic regression models M1 and M2 taking confidence intervals in account
I have two models M1 and M2 and each models the probability of having cancer with logistic regression. M1 is based on independent variables IV1 measured on a given sample of individuals and M2 is ...
- 393
3
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1
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682
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Appropriate way to get cross validated performance metrics
For cross-validation of a logistic regression classifier, it seems to me that there are a number of different approaches to calculating each performance metric:
The performance metric is calculated ...
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136
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Calculating individual predicted probability from logistic model and 95% confidence interval for shiny app
I have developed a logistic model to predict the risk of an outcome (TRS) based on some predictors. This was developed on a number of imputed datasets generated by mice (imp2) as follows:
...
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180
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Penalized Regression for Predicting Rare Events
I have a data set where my binary dependent variable is rarely equals one (about 0.3 % of all observations). My goal is to predict the dependent variable based on a few variables and a constant term. ...
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1
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2k
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Predicted Probability with XGBClassifier ranging only from 0.48 to 0.51 for either class
Why does my XGBClassifier predicts probability only from 0.48 to 0.51 for either class?
I'm very new to XGBoost, so any suggestions are greatly appreciated! Here's ...
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2
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102
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How is the direction of intercept determined?
Let's say I have a equation like as below (linear regression)
Y = intercept + x1+x2+x3...xn
intercept = 30
positive coeff sum = 40
negative coeff sum = -10
So, the final outcome becomes like as below
...
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44
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Modeling a binary outcome based on multiple predictor variables (when measures within subjects exclude one another)
The study design is as follows:
N subjects received MRI examinations. In a subset of cases, one or more sequences (i.e. separate “components” of the examination) were of insufficient image quality (e....
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2
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1
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64
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Calculate predicted values after validation of logistic model
I have a simple logistic model, and I internally validated it using rms::validate in R. The estimated overoptimism for the intercept is -0.015 and for the slope is ...
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1
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1k
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Linear assumption for logistic regression
I wanted to ask regarding the linearity assumption of the logistic regression, is the assumption between
A) independent variable (e.g. pre-score) vs logit of the outcome?
or B) predictive probability ...
- 361
1
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0
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42
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What is the prediction model to predict the probability?
In a paper, Dasgupta, 2019 used Difference-in-Difference approach to see whether anticollusion laws implemented by different countries (staggered implementation) affect firms financial flexibility.
...
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423
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How to obtain odds ratio (and 95% CI) from ridge regression model
I am currently working on a ridge logistic (predictive) model. I was able to complete most of the steps and obtain the coefficient but I keep getting an error message when it comes to the odds ratio &...
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