Questions tagged [binary-data]
A binary variable takes one of two values, typically coded as "0" and "1".
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Suggestions on binary classifiers for high dimensional categorical data set?
I have a binary classification problem with 210 variables (2 levels 0/1) and I am wondering how should I approach this problem as algorithms which I used (logistic regression, random forests) did very ...
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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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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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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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Compare multiple groups that have binary data with a control group
I have a dataset of 90 individuals with 12 binary variables, divided in three groups of the same size.
I want to know if two if these groups have differences with the other one (the control group), ...
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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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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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Analysing Binary data in a mixed design?
I ran a study with two IVs, a between-subjects manipulation Hands vs NoHands, and a within-subjects manipulation High and Low. The outcome of what participants did was recorded and then show to one ...
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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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How does eigenvalues work with binary data in redundancy analysis?
I am using the vegan package in R to do a redundancy analysis (RDA, a part of canonical correlation analysis). My response data is binary and my explanatory variables contains 0, 0.5 an 1. I get quite ...
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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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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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Which statistical tool can compare binary and ordinal data?
My research question is whether aptitude tests are a good indicator on how students will perform on course exams. I have already performed an analysis on total exam score compared with total aptitude ...
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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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Finding patterns in various-length binary sequences
I have a large number of binary sequences of different lengths (time-series of observations of the occurrence (1) and non-occurence (0) of some thing) and I am wondering how I could find patterns that ...
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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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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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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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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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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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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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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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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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Similarity between $n \gg 2$ binary vectors
I have $n$ binary vectors $x_i, ..., x_n$ of length $d$. I wish to compute
a similarity measure between all $n$ of them. My initial thought was to use
the Jaccard Index, since each binary element $x_{...
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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 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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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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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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Comparison of the mean of a binary variable from two independent sets
I have two sets of data, one is akin to high performing companies, and the other contains low performing companies.
I want to compare the mean of a binary value. For instance, "CEO has a bachelor ...
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How to choose optimal bin width while calibrating probability models?
Background: There are some great questions/answers here on how to calibrate models which predict probabilities of an outcome happening. For example
Brier score, and its decomposition into resolution, ...
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For a classification problem if class variable has unequal distribution which technique we should use?
for eg. if I have a class variable credit scoring with two classes good and bad, where #(good) = 700 and #(bad)= 300. I do not want to shorten my data. which technique I should use? I was using SVM ...
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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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Improving F1 scores using models with good precision and recall
I have a highly imbalanced dataset (0.21 percent positives, rest negatives) for which I am trying to build a classifier.
I tried to improve the F1 scores using hyperparameter tuning but in all the ...
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Binary logistic regression with compositional proportional predictors
I am running a binary logistic regression with compositional predictors that sum to 100% (demographic categories). I've looked at several postings about this, but can't find a good solution to my ...
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Can I use binary variables in VAR? How to interpret the IRF?
I am trying to forecast a time series based on other monthly time series variables.
The variables are:
endog -> number of users;
exog -> marketing campaigns(in euros), Number of Updates, number of ...
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Mixed Effects Logistic Regression w/ Repeated Measures for Observational Data
I am working on a study of how different scholarship programs at a university may influence student retention (i.e., if students are still enrolled at the university one year later). Each student can ...
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When does LASSO regression using coordinate descent fail to converge?
I am fitting a large dataset using the glmnet package in R. My response is binomial and I have substituted the covariates with weight-of-evidence to make them all continuous and all on the same scale. ...
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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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residualize binary outcome variable
Does it make sense and what is the correct approach to residualize a binary variable? For a continuous variable y, I simply run a regression that predicts ...
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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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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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Using binary factors as predictor variables in piecewiseSEM in R
I am looking for help with the use of categorical binary predictor variables in the piecewiseSEM package in R.
I am inspecting the effect of two categorical variables on one continuous response ...
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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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