All Questions
Tagged with predictive-models logistic
306 questions
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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 ...
CommunityBot
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1
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1
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63
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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 ...
- 41.1k
1
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1
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582
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Data setup: Attrition/Churn Modeling with Time Dependencies
Beginner Data Scientist here...
I'm setting out to build a predictive model for our client in the hotel/hospitality industry to explain the factors contributing to the attrition of their Loyalty ...
CommunityBot
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6
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2
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How to compare (probability) predictive ability of models developed from logistic regression?
I know some well-known measures are $c$ statistic, Kolmogorov-Smirnov $D$ statistic. However, as far as I know, those statistics take into account only of the rank order of the observations, and is ...
- 98.4k
2
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2
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How to get predicted values from cross validation?
This question is regarding cross validation and prediction with regularized logistic regression, so by parameters here I mean the beta-coefficients for each predictor variable, for output I get ...
- 149
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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 ...
- 82.8k
3
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1
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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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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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1
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2k
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Offset option in Proc Logistic (SAS)
What difference does it make in estimation of model equation if a variable is specified in offset option in proc logistic?
I know, if I specify a variable in offset option; the variable will be ...
CommunityBot
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4
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1
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In real clinical diagnostic data set how can we know the "true label" of a patient?
When we were taught about Bayesian probability, we often saw the following example: in a population, there are 5% of people who has disease X, and among the people who have disease X, the current ...
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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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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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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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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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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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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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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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3
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1
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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:
...
- 50.4k
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 ...
- 131k
2
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0
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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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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 ...
- 3,088
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1
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99
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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" ...
- 101k
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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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2
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546
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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 ...
- 128k
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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 ...
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2
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204
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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 ...
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 ...
- 67.1k
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 ...
- 20.4k
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1
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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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1
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158
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Which statistics method should I use to model events that barely occurs? [closed]
I have a dataset with information of different individuals and I want to create a model to predict if the individual will take some action or if he won't (1 or 0). E.g.: the individual will buy a ...
- 86.5k
4
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2
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382
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Prediction using a logistic regression model
Given a logistic regression model:
$y \in \{0, 1\}$
$ P(y=1|x;\theta) = h_{\theta}(x) = \frac{1}{1+\exp(-\theta^T x)}$
And given the value $\theta^*$ which maximises the conditional likelihood $P(y|X; ...
- 67.1k
1
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0
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169
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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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1k
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Goodness and prediction measures for conditional logistic regression models
As mentioned in this comment and answer How to get fitted values from clogit model, it is not clear that predicting from a conditional logistic regression model is meaningful.
It seems to me that it's ...
CommunityBot
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224
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Logistic regression predictive modeling
I would like to use a logistic regression for estimating the parameters of the logit function by using the maximum likelihood estimate. This amounts to minimizing the log-loss function, instead of ...
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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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2
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9k
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Goodness of fit, predictive power, discrimination
I'm making a couple of logistic regression based predictive models and intend to compare them and see which is "best". "best" here is obviously ill-defined, but as I'm looking for common metrics for ...
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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 ...
- 69.5k
1
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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 ...
- 101k
0
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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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1
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2k
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How to improve Recall and Precision?
I am working on a big data set which has 25 features with 237862 number of rows.
I am trying to predict return .
1 is for return and
0 for no return.
My data set has 12% of data which returned. So ...
CommunityBot
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1
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Modeling delayed feedback using logistic regression
Suppose we are trying to model the probability of a user clicking on an ad using logistic regression. We will receive only the positive feedback so, we define $Y = 1$ when success was observed, $Y=0$ ...
CommunityBot
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2
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Model Selection in Propensity Score Matching
I am trying to fit a logistic model to create propensity scores. Looking though the literature, there appears to be some disagreement on which covariates to include when designing such a model. Some ...
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3
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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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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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3
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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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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 ...
- 82.8k
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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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