Questions tagged [binary-data]

A binary variable takes one of two values, typically coded as "0" and "1".

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10 views

Correlation between two vectors of binary values

This may simply be a problem of me not knowing how to describe my issue properly, if so, apologies in advance for the duplicate. Some context: I am studying the distribution of genetic mutations in a ...
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7 views

Binary DV across versions

I'm trying to figure out the correct statistical analysis to use for an unusual design. The DV is a choice of one of 4 videos options. 2 of the videos are live and 2 are taped. I'm not interested in ...
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No group differences between group A and group B emerged for sex p=0.6 - How was this tested?

I wanted to report the demographics of my sample, which is a common thing to do in medicine. It means to report mean age, gender proportion etc of your groups. I turned to a paper that conducted a ...
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1answer
23 views

Sample size for binary outcome with rare events

I want to compute the sample size to compare two groups for a binary outcome where we expect rare events. I will do an example with R. Assume the following expected probabilities of observing an event ...
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23 views

How to get a probability value for a binary data observation every minute of the day

I am observing the electrical power availability on the main line at my home as either existing (0) or not existing (1) every minute of the day (we get a lot of power outages in this part of the world)...
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One Class Classifier for balanced binary dataset

Can I use one class classifier for the balanced binary dataset? For example, consider a text sentiment analysis dataset in which a number of positive and negative samples are equal Can I use one class ...
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Binary data of MCQ for paired T test

I am designing an experiment where I need to measure developer awareness after the introduction of a tool. basically taking 4 questions in pre and post-survey to measure increased awareness using the ...
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7 views

Weighted similarity coefficient for binary data?

I would like to evaluate the accuracy of land degradation maps I have estimated using remote sensing compared against observed field land degradation maps. The maps are classified in a binary way and ...
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11 views

Obtaining estimated probabilities and 95% confidence intervals from binomial GLMM

I have a dataset where I am testing whether, overall, individuals are more likely to mate (mating_response) with individuals of the same type rather than a different type . The response variable is ...
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17 views

Calculate Correlation/Distance Between Two Sets of Binary Vectors

Given two sets of binary vectors, what are some optimal ways to calculate their correlation? For example, Set A: [1,1,1,0,0,0] [1,0,1,0,1,0] [0,0,1,1,1,1] Set ...
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Filtering segments to balance classes in classification

I have a binary classification cohort where the False/True classes are imbalanced 20:1. It is possible to determine the quality of the data collected for each sample in the cohort. In my case, quality ...
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can i use cramers v to calculate correlation between two binary vectors?

i have a table with a mix of binary vectors and numerical. How can i calculate the correlation between the binary vectors (which contain 0s and 1s). Can I use cramers V for this? or should I use phi, ...
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Can you estimate average precision from log loss?

I am doing my final thesis in the field of Deepfakes and their detection. The final outcome is to have a binary classifier which could predict which video was updated and which was not. In other words,...
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Regression analysis with binary independent (categorical) variables and continous dependent variable

I am working on a dataset with 14 binary (0 or 1) independent variables (product features) and trying to measure a continous dependent variable (product price). I tried doing a regression analysis to ...
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why is the standard error so high for my probit model [closed]

I have created two probit models, and even though p values are significant and sample spaces are large- 10000 samples in both- standard errors seem to be about 6.27e. What could be the reason for that?...
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1answer
35 views

AUC-ROC interpretation for a binary classifier

I have this confusión matrix results: ...
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Binary Logistic Regression using SPSS for Non-Dichotomous Independent Variables

Im using SPSS for binary logistic regression but one of my independent variables is non-dichotomous and categorical (genotype - there are 5 gene combinations possible). I am trying to see if a ...
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1answer
14 views

Should I use predict_proba or predict when computing metrics

I need to compute some metrics for binary classification. I see that many times some people use the probability: ...
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1answer
344 views

Why are means not relevant to binary variables?

Trying to learn Basic Statistics from the Coursera. At the time 29 second, the video says: Means are not relevant with such a binary variable. Why?
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nested logistic regression model [duplicate]

I had a dataset that consists of 20000 chess matches. In this dataset, there are columns and variables- such as the players' ratings- that might have an impact on binary data, a white player is more ...
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How would I bias my binary classifier to prefer false positive errors over false negatives?

I've put together a binary classifier using Keras' Sequential model. Of its errors, it predicts with false negatives more frequently than false positives. This tool is for medical application, where I'...
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1answer
25 views

which hypothesis testing model to use for binary data

I have a dataset that contains 20000 chess matches. I hypothesize that 'is white more advantageous?', and there are features like standard match time of each match and the number of turns in each ...
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11 views

Which models can be used to explain data with oscillating binary variables?

The title may be confusing so let me show for demonstration purpose a one-dimensional feature vector x = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] and the corresponding ...
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31 views

Leave one out cross-validation performance

I am using LOO CV with XGBoost for binary classification of a set of biomedical data and getting very different results in terms of the AUC value compared with a 10-fold CV on the same dataset. For ...
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32 views

Granger Causality Analog for Binary Time Series

Is there a generalized form of granger causality that can be applied to two binary time series? By binary time series I mean an ordered series of values that take values 0 or 1.
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5 views

Binary Repeated Measures with One Group

I have a set of experiment data that has one group of participants who answered questions under different experimental conditions (about 5 questions per experimental condition combination). The ...
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1answer
37 views

Categorical independent variable and binary dependent variable

Which test can I use for analyzing the effect of a categorical independent variable, such as preoperative ASA score (1/2/3/4), on a binary dependent variable, such as postoperative complication (yes/...
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14 views

How to tune hyperparameter with imbalanced data

I am doing an hyperparameter tuning through GridSearchCV for a binary classification. ...
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1answer
20 views

No Activation Function on Output Layer for Binary Classification

In this pytorch example, the output layer does not have an activation function even though the neural network is being used for a binary classification task (i.e. ground truth values are either 0 = ...
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1answer
47 views

How to analyse binary responses for various factors, including interactions: chi square, mixed models, logistic regression, or ANOVA on percentages?

I run an experiment where subject had to recognize an emotion from various musical stimuli (which were composed with a certain emotional intent). There were 4 levels of emotional_intent, subjects ...
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Which are some formal approaches for predicting multiple binary time series?

I have 10000 roughly similar individuals. For each individual I've got a response (binary time series), 200 explanatory features (also time series), and 10 static features that represent ...
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27 views

Binary classification, imbalanced dataset optimization: AUC vs logloss

I'm running optimization on an imbalanced dataset and need to define my optimization metric. I'm working on disease detection so maximizing AUC might not be the best solution, as the certainty of the ...
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1answer
62 views

Post-hoc Power analysis to question a non-significant difference?

so we did this study about surgical success-rates in two groups (n=84 respectively). The outcome is binary (success vs. failure). A priori we expected them not to differ and, indeed, there was no ...
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1answer
46 views

Unbalanced dataset classification problem

I have a binary classification problem and I'm working with an unbalanced dataset. The count for each class in the training set looks like: ...
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2answers
30 views

Calculate probability of outcome of a medical procedure

I have data on medical procedures completed at hospitals in major U.S hospitals. Each medical procedure is assigned a code, for example: Kidney Transplant is X6571. I define the success criteria and ...
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28 views

Which Kappa to use in R to calculate agreement for binomial data (0 or 1) between two raters?

I have a dataset in which two raters (Human raters VS. ML model) assign "0" to pseudowords if they consider it as being masculine or "1" if they think they are feminine. So, it is ...
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1answer
32 views

How to analyze contingency table for multiple responses in SPSS or JASP?

I have two categorical (binary) variables: Gender (female vs. male) and 3 subject exams (English, Math, Science: Pass or fail). Everyone took all the subject exams (repeated measures). How can I ...
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24 views

What is an appropriate model for K continuous parameters on [0, 1]?

Question Summary What kind of model is appropriate for estimating K parameters on [0, 1]? In particular, what kind of joint posterior should a model put on K parameters with support [0, 1]^K? ...
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11 views

Help in calculating diagonal covariance matrix for generative model for binary classification

I am given this data. I want to fit a generative model $\cal{N}(\mu_0, \sigma_0^2 I_2)$, $\cal{N}(\mu_1, \sigma_1^2 I_2)$ for the $0$ and $1$ classes respectively using $\textbf{MLE}$ and plot ...
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Low birth weight in infants: A binary data example

Using the birthwt data from R's MASS package, I'm trying to solve the problem as posed in Modern Applied Statistics with S-PLUS ...
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76 views

Is it possible to use Transformer model for binary classification of unbalanced panel data?

So I have unbalanced panel data, i.e. multivariate time series with different lengths for each individual and a binary label at each time point. I was thinking to use some deep learning approach and ...
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Using Theils' Mixed Estimation (Dummy observations) to handle zero counts

Consider a binary response $Y$ and two binary predictors $X_1$ and $X_2$. Here is some synthetic data to illustrate the problem. ...
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Bounding error of percentage estimation on binary data for small populations

Let's say you have a set $X$ with $N$ elements belonging to one of two categories. So, $x \in X$ can be of type A or B (these categories are mutually exclusive). The elements, however, are not ...
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13 views

Intervention Analysis with binary time series

I need to do a intervention analysis to see if a marketing campaign affected conversion rate. I would normally would use Causal Impact package to train a time series and then forecast it on the post ...
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11 views

Fuzzy Augmentation and Logistic Regression: Percentage Dependent variable

Let's say the dependent variable is 1 = Good and 0 = Bad. Using Fuzzy Augmentation, I obtained an observation with a dependent variable of 0.6. Is using Logistic regression with more than "2"...
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How to find the [marginal] effect of X on Y when Y is binary and very rare. Can I make groups of similar X and model counts of Y instead?

tl;dr How to model the causal impact of X on binary Y when Y is very rare. Can I make groups and model count instead? Background/What I tried I want to know what the effect of the number of "...
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1answer
30 views

What is the standard way of plotting confusion matrix for binary classification?

I don’t understand the confusion with the matrix for Binary Classification. I was referring different documents for this, meaning sometime I see that the confusion matrix is plotted Actual Class Vs ...
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1answer
91 views

Can we treat gender as ordinal variable?

I know this question is stupid, but it is really make me confused. If we have the gender variable, and then encode it as 0 (female) and 1 (male). Most people would say we should treat gender as ...
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3answers
260 views

Plotting binary vs. binary to identify relationship

What would be the best plot for binary vs. binary to identify the relationship between two variables? Say I have a dataset like this. ...
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In probit model, why demeaning the data of a regressor lead to no change in numerical values for estimated coefficients except for the constant?

Supppose I have data $\{Y_i,X_{1i},X_{2i}\}_{i=1}^{n}$ generated by model $Y_i=\mathbf{1}(a+b_1X_{1i}+b_2X_{2i}>e_i)$, where $\mathbf{1}(\cdot)$ is the indicator function. I try to estimate this ...

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