Questions tagged [binary-data]

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

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Binomial Regression and Grouping Data

I'm currently trying to model Data where the dependent variable is either 0 or 1. Binary outcome. This would be the same as to say the data comes from a binomial distribution B(1, p). So I could use ...
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9 views

GLMER Model Failed to Converge: Convergence code 0 unable to evaluate scaled gradient

I'm attempting to perform univariate mixed-models logistic regression. Data: https://pastebin.com/dkwLzRka Here we have multiple observations of a given individual. The outcome is binary, and the ...
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39 views

Why are there two ways to calculate the standard deviation of a binary variable?

I've always been told that the standard deviation of a binary variable is sqrt(npq). However, there also appears to be a different way to calculate it: ...
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22 views

Is there a problem using a t-test of means to compare proportions from two samples?

If a binary variable is recoded into 0 and 1, then a mean of it tells us the proportions. A lot of people compare proportions using a t-test of means. For instance, proportion of people enrolled in ...
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Duplicate observations and complementarity in the outcome

Consider the following scenario. I have a data set with information on several bouts, for both boxers and for the three judges within each bout (we are speaking about boxing fights). I want to ...
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17 views

How to include longitudinal information in logistic regression?

I have a binary outcome $y_i \in \{0,1\}$, $i=1,\dots,n$, and some covariates $x_i\in{\mathbb R}^p$. I am planning to model these using a logistic regression model. However, I also have information ...
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Interpreting GLM with poisson distribution outputs for assessing affect of two categorical variables on frequency

I'm currently trying to see if the frequency of a behaviour measured in a binary format (yes/no (where yes means the behaviour is present) is related to 1. the month in which behaviour took place and ...
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11 views

Logistic regression: Controlling for unequal distribution in categorical variable

My question title is poorly worded but I hope I can explain my problem here. I have a dataset that contains a binary outcome variable (RP), which I would like to predict using two categorical ...
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1answer
32 views

How to calculate the relation between 2 lists of boolean/binary (true/false or 1/0) values?

We have performed analyses on REST API endpoints to detect if they violate REST linguistic principles (i.e. if the URIs are well designed) or if they violate other REST design principles (for example ...
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1answer
31 views

Pearson residues applied to the binary model

My question would be about Pearson residuals applied to the binary model. When we build confidence intervals for a proportion, p: we have a sample, and we count the number of individuals who have a ...
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10 views

can Durbin Watson be used for binary valued times series

I have multiple time series and for each time series, each series is either one or 0. So for example, it is like the following: ...
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1answer
27 views

Normalise different thresholds for binary prediction

I'm working in a module that outputs the risk of an event happening i.e. risk of a crime happening depending on the district of the city. What I've done is to calculate for each district a binary ...
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Interaction versus split sample

Let's say I want to do a linear regression with data on the dependent variable Y, a dummy variable D and one more binary ...
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What are some techniques to improve generalization for subsets with varied distributions?

Suppose I have a binary classification problem in which I have a set comprising subjects, and each subject contributes with a varied number of positive and negative samples to the whole set. The ...
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1answer
35 views

How to do statistical test for the difference between two very small proportions?

I have a typical A/B test setup where I have a control and treatment sample of equal size with very small success proportions. An example could be the following data with a sample size of 505000, ...
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11 views

What statistical test to compare reader binary classification metrics with and without aid?

I have a dataset of MR images of 50 patients with either benign or malignant liver lesions. I asked 3 readers to read the dataset and tell for each case if they thought it was benign or malignant. Two ...
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Binary classification statistical significance

Consider a binary classification task and a trained model (e.g. logistic regression) gives predicted labels. The predictions can be done on a hold out test set or obtained using a cross-validation ...
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13 views

Poisson Regression for binary outcomes - why is legitimate?

I have learned - and taught - that to build a regression model for a binary outcome one should use a logistic regression, for a outcome that has discrete counts one should use the Poisson regression, ...
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20 views

Is resampling multi-variate time series data a useful practice in increasing binary classifier accuracy?

Let $x$ be defined as a multi-variate time series with length 30 seconds a sampling frequency $F_s = 60\text{ Hz}$ columns $\{C_1, C_2, C_3\}$ My first question is, in general, would resampling $x$ ...
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1answer
93 views

Linear probability model with fixed effects?

If I want to estimate a linear probability model with (region) fixed effects, is that the same as just running a fixed effects regression? Maybe I'm getting tripped up with the language and whether I ...
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17 views

Estimating a linear probability model on a subsample

I am dealing with a situation where I have a binary outcome variable $z \in \{0,1\}$ for treatment under a program that ran from 2000 to 2010 (so units were treated throughout the period). In my data, ...
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10 views

Interpretation of hierarchical clustered binary dataset

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25 views

Is better to use a multiclass classifier or a set of binary classifiers?

I have to build a general method to perform multiclass classification. The number of class in the target variable is not fixed (it is probably in a range between 3 and 10). I would like to know if it ...
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9 views

Is conversion of binary variables to Likert scales considered valid?

I am developing a questionnaire for my PhD and plan to use established scales. To make the items fit my research questions, I make minor changes in words. I plan to ask all questions with the possible ...
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13 views

What is a good metric for a binary classifier when we are more interested in Precision than Recall but care about confidence scores?

I have an heavily imbalanced dataset and am training a binary classifier (which produces scores in the range 0 to 1) and need a single summary metric to tune hyperparameters with. For my problem, ...
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1answer
37 views

Is logistic regression the way to go?

My data has two dichotomous variables: culture (A and B), emotion (X, Y). Participants in two countries (A and B) rated 16 sound-clips on these two variables. RQ1: Are people able to distinguish ...
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40 views

Exact distribution of number of transitions in a binary vector of length $n$

I am trying to derive an analytic solution for the exact distribution of the number of transitions in a binary vector of length $n$ conditional on the observed number of $1$'s and $0$'s and under the ...
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22 views

Is there an ex-post effect size to compare across binary response models?

Specifically, I am facing difficulties to define a dependent variable (comparable effect size) for a meta-regression, because most source-studies apply probit- or logit models. Of course, data ...
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1answer
29 views

Finding optimal point in roc curve giving weighs to true positives and false negatives

I have a binary classification model whose ROC curve looks like the one below. The black point is the optimal probability threshold to use by calculating the geometric mean. However, that's a pretty ...
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11 views

Quantifying Co-occurrence

I have a problem where I need to quantify the co-occurrence of two events. I've been using a working metric I'm calling "normalized co-occurrence rate". It's the proportion of events that occur ...
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17 views

Bootstrapping in logistic regression with sparse binary variable

I would like to estimate the probability of a relation between two entities. The data set includes information of many relations between many entities, and information on covariates for each entity. ...
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15 views

Longitudinal data model choice, given data and question

I'm wondering if anyone would have any ideas about a modeling approach that might work for an analysis I want to do: I have a three-level dataset in which people completed up to 7 surveys each day ...
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18 views

Multilevel binary logistic regression assumptions

I am struggling to work out the assumptions of hierarchical binary logistic regression, to test whether my data is suitable for such an analysis. My data is repeated measures (each participant ID ...
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16 views

How do I calculate the expected value of a binomial distribution for a genetics example?

I have model with 20 genes which can take on a value of 1 or 0 (the alleles). What is their expected value and variance assuming the alleles are selected with equal probability? Is this just a ...
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1answer
23 views

Regression interaction terms in stata

I am currently studying the relationship between having a supervisory job and having traditional values when it comes to child care (woman staying home). I want to find the relationship with ...
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1answer
15 views

Accuracy of repeated measuring of binary data

Suppose there is a device that can measure binary data (0 and 1) with 90 percent accuracy. I have used this device and measure the same data twice (or in another scenario three times). If in both ...
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38 views

Clustering a dataset and creating a model per each cluster

I was wondering if it makes sense to cluster a dataset to find closely related data points and train a binary classification model for each of this clusters as they would be minidatasets. I'll ...
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71 views

Logistic regression for predicting event probability in time-series data

I have found similar questions here but am not certain any of those fits for my modelling problem. I have a repeated experiment with a set of participants (say 15, each participant has done the ...
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8 views

Cross correlation to binary time series with stochastic noise

I have tested usual cross correlation to binary time series, where the values just mean "1" = "off" and "0" = "on" (nominal data type) and I have quite good results in finding "similarity" (see later) ...
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Is the random slope for a binary, categorical variable in a mixed model also reported in reference to one of the categories?

I'm wondering if I should be interpreting an estimated random slope for a binary categorical variable in the same way that I should be interpreting it if it were a fixed effect. That is, is it ...
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13 views

Help Correlating Particle Count (Dirtiness) to Chip Pass/Fail

I have two datasets that I’d like to correlate in a way that is helpful and predictive. In our process, we a have a single work piece that should be perfectly clean that will eventually become many ...
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18 views

FFT for a binary time-series

I have a multivariate time-series of a binary values where 0 means that some state was not observed in the given second and 1 meaning that it was observed. I know that for a time-series consisting of ...
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45 views

Unexpected fitness values: Neat-Python

I am currently working on implementing the Neat-Python library to run some neural networks. The below code works and I have also included the configuration file I have used. The problem in question ...
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16 views

At what level of x (continuous measure) do two binary measures diverge?

Participants at different ages (continuous-data) responded to yes/no questions (binary-data) in two conditions (within-subjects). Younger participants responded similarly to both questions, whereas ...
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1answer
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How to pick a classifier?

I have multiple datasets of comparable shape. I want to train a separate binary classifier for each of those datasets. These datasets have two problems Too many dimensions: (E.g. 1 dataset has 160 ...
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2answers
46 views

Multilevel between-subject design using glmer

I want to test the effect of different learning strategies across time. Conditions were manipulated between subjects. Each participant answered the same set of binary questions across 3-time points....
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45 views

Unsupervised analysis of sparse binary variables

I have a dataset with approx 5,000 customers (ID). Each customer bought between 1 and 20 different items (I) (total of 10,000 different items) ordered within classes of items (C) (total of 450). All ...
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11 views

How can i analyze retrospective binary data?

I have a population of data sampled form 2019. The total number is 118. I am looking at several different variables. The main variable is whether or not a test is performed so 1 yes or 0 no. And ...
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24 views

What's wrong with my binomial logistic regression model please? (SPSS) [closed]

I am running a binary logistic regression in SPSS (standard, no stepwise) containing 20 predictors (binary and continuous) and have the following problems: 1) it correctly classifies ~the same % as ...
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66 views

Mixed effect model with zero inflated binary (0,1) response where one level of fixed effect has all 0s. Won't converge

I am trying to use a mixed effect model to determine the relationship between year, season, and depth (my fixed effects) on nutrient outlier presence (dependent variable, 0 or 1). I have two random ...

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