Questions tagged [binary-data]

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

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Binary Classification Problem with Predicted Probabilities distribution skewed

I have a balancedrandomforest model which was trained on unbalanced data (92/8) for a binary classification problem. The AUC is around 0.98 and the precision and recall are also acceptable being 0.89 ...
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How to mean center variables based on binary condition in r [migrated]

I have a dataframe ("md") containing several variables, of which one is binary ("adopter"). I would like to mean center three of the other (continous) variables, let's say X, Y, ...
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Binary regressor - what happens if people move from one category to the other?

Suppose I have the following regression model: Monthly alcohol consumed A as independent variable, regressed on a binary regressor S (S = 1 if smoker, S = 1 if non-smoker), and through OLS I get an ...
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Regression of binomial response when the predictor range is limited

I am looking into a dataset for which I will be doing a regression. When considering the option of a logistic regression, I started doing univariate regressions to get a feeling for the possible ...
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Categorical IV with probit second stage

In a panel setting, I have a binary endogenous variable $X_{ijt}$ where $i$ indexes the individual, $j$ indexes the region, and $t$ indexes the year. I have a set of mutually exclusive binary ...
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How to interpret fitted coefficients in a multiple regression model: binary, continuous, and interaction terms

Suppose I have a multiple regression model: $y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_1x_2 + \epsilon$ where $y$ is continuous $x_1$ is dichotomous (0 or 1) $x_2$ is continuous If $x_1 = 0$, ...
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Predicting probability of choice across different choice sets

I have data where people saw a series of 2 forced choices. Those choices were a random selection from a set of 4. So, from a set {A, B, C, D} participants saw two random options (e.g., {A, D} or {B, C}...
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Statistically increase mean difference between two data sets?

A dataset will be used to train a binary classification model. For better understanding/visualization, the data set was divided into 2: one set with all the rows that result in prediction value of 1 ...
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Biased logistic regression in pytorch

My model has decently high AUC=90%, but is biased, underestimating the probability $y=1$. This is systematic across some of the input features as well. How can I nudge the bias term, or otherwise ...
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Under what conditions will prices of shares in a binary prediction market accurately represent probabilities?

I often see that prediction market sites say that the prices of the shares on outcomes can be interpreted as the likelihood of the outcome occurring. But under what conditions is this true?
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Comparing Coefficients of Binary Logit Model

I'm using a binary logit regression to predict the likelihood of homeownership. I got the natural log of the coefficients. I was wondering if the coefficient of one variable can be directly compared ...
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Binary logistic regression with dummy variables for several different IVs

I want to carry out a binary regression where the DV is 0 = Never considered giving up pet, 1 = have considered giving up pet. I have several categorical variables that I want to enter into the model: ...
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Dependent variable has no variance error in logit regression

I m running a logit regression with over 90,000 observations. However the case when dependent variable =1 , is only 115 observations as per the data, the rest are 0. The Eviews software shows "...
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Are all dummy variables stationary?

If a time series model contained only dummy variables as dependent and independent variables. Is it always stationary?
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How to interpret independent dummy variables in logistic regression?

I have both quantitative and dummy independent variables in my logistic regression. Dependent variable is binary. I have 2 questions. How to interpret a quantitative variable that is negative? How to ...
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Is Chi square appropriate to show one set of binary data comes from a different population than another set of binary data?

I am comparing the accuracy of different computer programs on making predictions on the same set of data inputs. For example each of 5 computer programs read in the same 100 data points, and make a ...
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Predicting repeated binary response from contacts over time

From their initial entry date, people must be contacted each month for three months. It often takes several unsuccessful attempts before you establish contact. Once you reach someone, contact attempts ...
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How to get the True Negative Rate from this code?

I want to calculate the TNR. I am in a larger code project and we have this one binary classifier. The major problem is that I don't find the information about the variables in the code. What is the <...
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Error in wp.logistic: ‘p0’ must be numeric in (0,1)? What to do when p0 is negative?

I am trying to find out the sample size I need for a future study using a reanalysed existing dataset to enter the values in a WebPower script. I am using the intercept and odds ratio/estimate of my ...
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Which model should I use for Time series data?

I need to regress one dependent variable (dummy variable), against several other independent variables (dummy and non dummy variables). (FYI : I'm not using the past performance of dependent variable, ...
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How do I derive the variance of OLS estimators when I have dummy explanatory variables?

I know this isn't the smartest question, however I need to derive the variance of the OLS estimators in a Simple Linear Regression Model when the explanatory variable is a dummy one and all the ...
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Determine whether two binary sequences are correlated

I have two arrays of 2048 binary values (1 and 0) and I'd like to find out if their content can be considered correlated. I'd like to have less than 1:1000000 chance of a false positive in determining ...
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How to fit joint models for longitudinal and binary (outcome) data?

Joint Models are mainly viewed in the literature within the context of longitudinal and time-to-event data. For this reason R packages as JMBayes were built to fit these kind of models. Nonetheless I ...
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Averaging Point-biserial correlation coefficient

What will be an appropriate way to report the Point-biserial correlation coefficient if I have 5 random seeds of the same experiment (5 trained models on the same data). I am measuring the correlation ...
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What statistical test is appropriate when the independent variables are binary but tied to multiple sites and the dependent variables has many 0s?

I have a data set of microplastic particles/kg taken from various beaches. Each beach has several binary criteria which are the independent variables of the study. My issue is that in some samples ...
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Correlation between binary variables

Long story short - I am lost among the ways to check for relation (whether there is any) between binary variables. Context - I am working on a side project where I try to analyze marketplace data and ...
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What statistic would I use to explain the discrepancy between two binary variables?

I have 3 variables in a large dataset: whether students passed their multiple choice portion of their final (binary: pass-fail), whether they passed qualitative portion (binary: pass-fail), and ...
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Variance of OLS estimator with binary treatment

I know that in general, given a (stacked) regression of the form $ y = X \beta + \epsilon$, where $\mathbb{V}(\epsilon_i) = \sigma^2 \forall i$, then letting $\hat{\beta}$ denote the OLS estimate of $\...
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Assessing combined effects of binary predictor variables

I'm looking to analyse the effect of 20-30 binary predictor variables on a continuous response variable. I'm no statistician, so first off I'm not sure whether a regression with this many binary ...
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Making binary prediction with GPBoost (or MERF)

My question is regarding this post from 1.5 years ago: Modelling clustered data using boosted regression trees My label is a binary variable (yes/no). Is it possible to use GPBoost / MERF in order to ...
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binary classification with labels of varying quality

I have a binary classification problem, where half my development data is labeled by a reliable source, and the other half by a less reliable one. Note that each instance gets a label from only one of ...
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Need guidance for comparing dichotomous data and Likert scale data

I am comparing a job satisfaction survey tool and a leadership questionnaire. One has Yes, No, Uncertain answers and the other one is a 5 point Likert scale. What I am specifically trying to do is ...
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Collision chance for subsampled binary IDs

I am wondering if my following conclusion holds true: let 2^x = 2^(y+n) where x, y, n can be any integer >0 when generating a y-bit number (y-val) from a x-bit number (x-val) through a process ...
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If multiple variables add up to 1, are they independent of each other?

I am trying to test for association between continuous fractions of cell types in a sample (e.g. immune cells, cancer cells, fibroblasts...) and tumour grade (categorical/binary/ordinal, grade 1 or 2)....
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When to convert an ordinal variable to a binary variable?

I have seen some people convert their ordinal variable to a binary one, especially in the public opinion literature. For instance, when there is a four-scale question with responses including "...
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Need a predictive (binary outcome) model for a set of binary variables and one continuous variable

I have a data set of about 1600 binary results, that I want to predict from 9 binary variables and a continuous variable. The relationship between the continuous variable and the result variable by ...
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Creating a binary attribute for each of the M nominal states

I am preparing for an exam in data mining and need help with the following question: Assume we have categorical data. One method to define a distance between two data objects is (p-m)/p where p is ...
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Sequential Bayesian updating with binary data (in a case where a beta-bernoulli setup seems inappropriate)

An unknown parameter $\theta$ is randomly drawn at time $t=0$ according to prior p.d.f. $\mu_0(\cdot)$ that has support $[L,R]\subseteq\mathbb{R}$. At each time $t\in\{1,2,...\}$ an agent makes an ...
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Sampling uniformly using binary representation of a number

I have a $6$-sided dice and I would like to sample integers uniformly from $0$ to $k$ with $k > 6$. I think that $k$ should be written in its binary representation. Let's say its binary ...
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Comparing the probability of co-occurrence between two pairs of vectors

Say I have two binary vectors $x,y$ of length $N$, with $n_x, n_y$ the number of $1$'s in those vectors and $n_{xy}$ the number of $1$'s that co-occur in the same spot. The probability that $n_{xy}$ ...
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Appropriate correlation statistic for binary and count data

I have two variables where I want to report their correlation. One is a count variable that ranges from 0-3, and the other is a binary variable that is 0/1. ...
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Can NaN class be assigned to a certain class in imbalanced datasets (binary classification)?

I'm working on a spam detection binary classification problem, but the dataset is very imbalanced (99% to 1%). I know there are techniques like over/under sampling, but I don't think it can be used in ...
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What hypothesis testing to use for continuous to categorical variables?

For example, I'd like to know if a person's age (a continuous variable) is related to whether the person drinks (a categorical/binary variable of Y or N). What method should I use to know If there's ...
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Interpreting SHAP interaction values

I have a trained model where gender, var_a, var_b, .. , var_g are binary features and an age variable too. Gender = 0 : male and Gender = 1 female. Similarly var_a and other features are binary. While ...
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Effect of zero-variance variables on logistic regression

Imagine that due to pipeline/workflow issues a logistic regression model that's in production has some binary variables in it that are positive or negative for all observations in the modeled ...
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How to check if any combination of binary variables is correlated/has impact on an ordinal dependent variable

I am working on a case to finish my (not so advanced) data scientist course, now I am stuck again and cannot find an existing answer to my problem. My data comes from a bike shop and I want to see if ...
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Model Selection Logistic Regression: Wald vs LRT

To select a model I use stepwise with the likelihood ratio test but I have seen that people use the z test (the one that appears in R when obtaining the summary) to include the variable with the ...
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Population overlap of random distributions of binary choices

I’m trying to figure out how to calculate the overlap (concurrence) of certain building features, for example: high-efficiency windows, thick insulation, efficient lights, etc. I know the probability ...
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Use regression_forest from the grf package to predict probabilities

I am wondering if it would be alright to use the random_forest command from the grf package in R for a binary outcome to predict probabilities. As far as I understand, this should be the equivalent to ...
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If going with the opposite prediction of a bad predictor gives good predictions, why not do that?

Let’s restrict our consideration to binary outcomes. I have a friend who is terrible at predicting the future, always predicting the opposite of what winds up happening. For instance, my friend ...
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