Questions tagged [binary-data]
A binary variable takes one of two values, typically coded as "0" and "1".
1,417
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Applying OLS regression on model with binary dependent variable to run diagnostic tests
My dependent variable is binary and am therefore using a logit regression but since the diagnostic tests to run for logit are different can I not just regress the variables with OLS and run the ...
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How can I write this optimization problem? [closed]
I have a matrix $M$ of size $n \times n$, wich contains the compatibility scores between people (this is a measure between 0 and 100). In my problem I have 56 people.
I want to group this people in ...
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Regression analysis with single outcome variable and binary independent variables
This is a meta-analysis. I'm looking at factors associated with vaccine acceptance in many countries. Looking at previous studies in different countries, I recorded factors that are associated with ...
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Weighted Binary Variable? [closed]
I have a dataset composed of a binary variable, indicating whether agriculture land was state-owned (1) or not (0), repeated for 10 time points. It also includes an interval variable that indicates ...
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Measure alignement between continuous and binary variables
I am trying to compare different evaluation metrics to assess performance of LLM-based solutions. To do so, I was planning to compute different metrics values (continuous outcome) and compare these ...
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Alternative test instead of logistic regression for binary dependent outcome variables?
I have a dataset of patients who underwent an operation, and I collected information on post-surgery complications such as necrosis (binary outcome variable). Now, I would like to investigate whether ...
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1
answer
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Binary logistic regression results interpretation when one IV is ordinal [closed]
I don't know how to interpret the ordinal variable 'Stress' in my binary logistic regression analysis.'Stress' was measured on a 10 point scale where 1 is 'Least stressed' and 10 is 'Most stressed'. ...
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Multicollinearity Between Binary Explanatory Variables
I have a count data and most of my explanatory variables are binary(0/1), from A to H. They represent different types of support given to a group. I will run a ZINB model. But first, I checked for ...
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Is there a better alternative for the Jaccard index to obtain the relationship between binary indices?
I currently have data from $n$ sources. Each source sends a binary signal each minute. I have a register of $p$ minutes.
I have used Python to calculate the Jaccard indices of each signal as
...
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1
answer
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What non-parametric test for multivariate binary data should I use?
I have two different groups of participants ("g" and "b") answering the same set of questions. Group "g" answered questions in the same order. Group "b" ...
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Unbalanced binary response variable causing poor model fit
I am trying to model what environmental data increases the probability of my response variable occurring. My data covers 30 years of daily observations. I have narrowed my predictor variables down ...
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How to Combine Correlated Binary Variables
I have a count data, and most of my explanatory variables are binary (they represent different types of support given to a group). Three variables seem to be correlated with each other. I don't want ...
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How to do a moderation analysis with dichotomous IV, continuous MV and continuous DV
I’m trying to do my data analysis (SPSS) for my thesis and I’ve been stuck for days. My supervisors also don’t know what test is best or they don’t respond to emails.
I have 1 continuous MV (sleep ...
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answer
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Deducing from Ordinal to Binary Data
Assume I have two rank vectors $r^A, r^B$ of size $p$ - that is, each of them is some permutation of $1,...,p$. For the sake of simplicity, assume that $p$ is odd.
Now, I take these vectors and recode ...
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Embeddings/tokenizers for a transformer with binary-valued data
I'm trying to train an encoder-decoder transformer model for completion of binary-valued data. The each input is basically a length-n bitstring $x = (x_1, \dots, x_n) \in \{0,1\}^n$, generated ...
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Given that quasibinomial regression models extra-binomial variation, why ever do binomial regression if quasibinomial is more flexible?
In reading about quasibinomial regression:
The quasi-binomial distribution, while similar to the binomial distribution, has an extra parameter 𝜙
(limited to |𝜙|≤min{𝑝/𝑛,(1−𝑝)/𝑛}
) that attempts ...
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Logistic Regression Power Analysis with Multiple Predictors
So I'm working on my dissertation and I'm trying to figure out a binary logistic regression power analysis to show how many participants I should collect. My proposed analysis is as follows and the ...
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How to model risk with presence-only data?
I'm working on a dataset of bird electrocutions. There are 300 instances of electrocuted birds and I have a range of environmental data that I want to input as my predictor variables. The aim is to ...
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Correlation among 10 binary variables
I have a dataset like this:
All these social determinants are binary variable. How can I find the correlation among them? By chisq.test? Since I have 11 variables and it will be 55 pairs. Is there ...
Louis
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Longitudinal Studies with a Binary "Since Baseline" Variable
I came across a study design that I can't seem to find specific literature on:
Like most longitudinal studies, the subjects are re-measured at different time points
There is a binary outcome variable,...
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Is this GLM approach appropriate for binary data and determining difference between 8 groups?
I have been given a dataset to analyze looking at some herbicide treatments for invasive trees in three states with 3 sites in state 1, 2 sites in state 2, and 1 site in state 3. We hope to answer ...
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Is this glm approach in r appropriate for determining differences (if any) between 8 groups with binary data?
I have been given a dataset to analyze looking at some herbicide treatments for invasive trees in three states with 3 sites in state 1, 2 sites in state 2, and 1 site in state 3. We hope to answer ...
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Mixture Model: Data Consist of Continuous and Binary Features
I have a features like below
id
x1
x2
x3
x4
x5
id1
0.4
1.4
5.6
1
0
id2
-0.01
0.5
-3.4
0
1
where x1, x2, x3 are continuous features and x4 and x5 are binary. The goal is to find $k$ clusters using ...
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Can I use multiple linear regression with binary output?
I have a dataset with $10$ inputs containing real numbers and an output which is binary ($0$ or $1$), and I need to make predictions. So, I thought of using multiple linear regression to predict an ...
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Sample size calculation for paired binary proportion - non-inferiority study?
I want to conduct a retrospective study, validating an algorithm. My data will be something like the following:
id
doctor
prediction
1
0
0
2
1
1
...
...
...
n
0
1
My study design is non-...
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Timeline "spike" similarity metric?
Imagine you have a single axis. Along the axis are placed several target points, at differing distances between each other.
You now have a black box that shoots a variable number of points on to the ...
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1
answer
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Splines, logistic regression and sample size considerations
I have around 500 observations with a binary outcome at 25% prevalence and will be building an internally validated prediction model. I want to use splines to model non linearity in my continuous ...
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Creating a scoring system in binary logistic regression
I have used forwards binary logistic regression to determine which predictors are significant in classifying patients into two clinical categories. Three significant predictors were identified. Could ...
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Predicted class probability in threshold moving
I am training a model for the task of Binary classification using H2O.ai. The final output to the user is the probability of class_1.
Recently, I found that by ...
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Statistical test for nominal data, multiple variables and within-subject design in R
I have run a study comparing if a cheap ultrasound device (T) is as efficient at determining osteophytes as an expensive device (V). There was four examiners who reviewed each participant (ID) and ...
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1
answer
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Optimal perturbation of feature vector to get an outcome
I am struggling with a problem: Suppose that I have a binary classification model which is trained on some data and outputs probabilities of classes 0 and 1. I now have a new feature vector, say $\...
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Machine learning classification: best way to know if my variables are unable to distinguish between two classes
I am working with an imbalanced dataset containing 42 variables and around 136,000 observations, in order to perform a binary classification (96% of the observations belong to one class). I tried ...
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How to account for overdispersion for GLMM with binomial distribution in R?
I am pretty new to R and am having some trouble finding a straightforward solution to overdispersion in a GLMM with binomial distribution. I have a few different questions listed here. I am mostly ...
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Why would you smooth a logical variable in a GAM?
I just used the gam.scope function in the R-package gam to create possible scopes of each explanatory variable of my model to ...
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Cox regression with binary time-varying covariate
I am researching the association between menopause and the incidence of diabetes(outcome).
I have a baseline and three follow-up assessments. Given that women transition from non-menopausal to ...
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GEE Using a Bernolli Model and Log link
Conceptually I am interested in a pretty simple question: Do screening rates (dichotomous outcome) differ between an intervention and control group. We have a number of clinics that patients are drawn ...
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Are we allowed to use classifiers to estimate the outcome in the first stage of Double Machine Learning when the outcome is binary?
It is clear to me how to proceed when the outcome is continuous, since the EconML and all other references I checked work with this type of examples (continuous outcome case). We simply apply a ...
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Predict on continuous variable for Logistic Regression model in which feature was trained as a binary variable?
Let's say I have a binary logistic regression model trained on several binary categorical variables (i.e. the model is only trained on 0s and 1s for these variables). For example, Feature A can only ...
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1
answer
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Dichotomizing a continuous predictor leading to differing effects on 2 outcomes
I am fairly new to statistics as a Phd student. I am trying to understand how dichotomizing a continuous variable can lead to distinct effects on two dependent variables.
So in a cross-sectional ...
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1
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Can I conduct a PCA on binary presence-absence data?
I have presence-absence data for 53 wildlife species at 60 different sites. I am a bit confused as to whether a PCA would be appropriate for this sort of data. If so, is there a specific R package I ...
BiggestNoob
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Logistic regression with binary and ordinal variables (SAS)
I have survey results (n=14, small size, I know) which scored several health measures from Poor (1), Fair (2), Good (3), Very Good (4), and Excellent(5). I want to see if having a physician (0=no, 1=...
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For a logistic regression, how to include continuous independent variable that also depends on binary independent variable?
Hi trying to better understand the statistical approach for the below problem.
We'd like to build a logistic model (binary outcome) with two independent variables: one binary and the other continuous.
...
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Binary data correlation with many variables [duplicate]
I'm struggling with something that at first sight seemed simple to me but turned out no to be. I have a big df (112 samples x 58 characteristics), these characteristics are all binary (presence/...
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Negative Coefficients for Interaction Term in Dichotomous Variables
I've come across an issue while analyzing some data and haven't been able to find a similar question on the site.
I'm working with data concerning the impact of certain genes and smoking on the ...
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PCA to reconstruct Binary Data
I'm working with binary 3D matrices. I calculate their PCA (or REOF or SVD) and as a test I would like to reconstruct these matrices from the PCA results. However I realized that because I only keep ...
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Difference-in-differences approach validity when binary outcome is 0 during pre-treatment period & always 0 for control units
In the context of evaluating the effectiveness of some intervention on a binary outcome, using a difference-in-differences design, if the outcome is 0 for all study units during the pre-treatment ...
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Univariate odds ratio calculation - by hand versus log regression
If I have only one binary predictor variable for a binary outcome, is there any meaningful difference between doing hand calculation of odds ratio (OR = ad/bc), versus doing a univariate logistic ...
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Binary and count variables as endogenous variables
I set up an APIM (actor-partner interdependence model) in R (lavaan).
No I'm facing the following issues:
Model: My endogenous variable is a count variable that follows a poisson-distribution.
Model:...
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Predict binary outcome with longitudinal data
I have a dataset with experiments. Each of them was performed with different settings. The outcome, binary, is only known once the experiment is over after 60 minutes. We collect data every 30 seconds,...
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Can the size of beta coefficients and t-values from a linear probability model be trusted?
I have a series of predictors and want to see how each of them predicts a binary dependent variable that takes on the values of 1/0 (i.e., yes/no). I am running a series of linear probability models, ...
