In broader sense - synonym of "dichotomous data": any data that can take on only one of two values. In narrower sense - dichotomous data coded as 1 or 0; furthermore, sometimes "1" is supposed to mean "is present" and "0" to mean "is absent", which may require handling the two values asymmetrically ...

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10 views

Distribution of binary sequences?

I have two binary sequence and wanted to test if there is a similar patterns between the two. This is a completely new topic for me. Are there ways to define distribution of a binary sequence ...
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0answers
32 views

Meta-analysis - Multiple Outcome measures for the same population

Basically, I am trying to include some binary data into a meta-analysis and not sure how to include this dataset. If you look at the attached table, each red square that i drew depicts an ...
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3answers
169 views

Visualizing variability from graph

It is written in the book Applied Logistic Regression, Second Edition. By David W. Hosmer and Stanley Lemeshow , p.2 that a problem with the above graph is that the ...
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0answers
7 views

References regarding correlations with ranks and binary data

I have several rank variables (ranks 0-3), which can be reasonably turned into binary (significant/insignificant effect). I'm looking for potential interactions. What would be the best source to look ...
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0answers
16 views

In penalized regression models, should binary predictors be standardized?

It is generally agreed that in penalized regression models, such as ridge regression, the lasso, and the elastic net, one should standardize the predictors (such as dividing each by its SD) so that ...
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1answer
44 views

Choosing a good binary classifier to be trained by a small set of labeled data

I have a small set of labeled data (diagnosis in individual subjects): ~50 of "sick" observations ~100 of "healthy" observations In reality, only ~1% of the observations are expected to be ...
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0answers
14 views

Recode Binary to scale Variables

I'm looking to find information to recode a set of dichotomous response variables to preferable a 1-5 scale. I have several response variables which when combined with PCA clearly depict certain ...
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1answer
23 views

Interpreting Coefficients of a Dummy variables derived from an Ordinal variable

I have a variable that is measure societal complexity (SC) on a 3 point scale. 1 being the least complex and 3 being the most complex, and I think that this can safely be classed as a ordinal ...
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1answer
38 views

What does it actually mean for classes to be balanced?

I saw the following statement when reading Kuhn's APM: "The classes are fairly balanced; there are 111 samples in the first class and 97 in the second..." I thought balance would require the ...
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3answers
49 views

How can I run a t.test in this situation of two processes having binary outcomes

I have two processes, lets call them A and B. I want to infer whether their population means are equal for their experimental outcomes. Both of these processes generate 1s and 0s only. That is, the ...
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1answer
68 views

Statistical test for multiple comparison of groups of animals with Yes or No outcome

In my experiment (pre-clinical vaccine testing) I want to know what kind of statistical test to be used to compare between 9 groups of animals (72 animals randomly divided into 9 groups). Each group ...
2
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1answer
45 views

I need both quadratic and linear coefficients in a GLM with binary response. What's the best option? [closed]

I have three predictors and one response. What can I do if my response variable is binary?
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0answers
26 views

Multivariate Bernoulli, Covariances for Categorical Data

I need to find outliers in multidimensional, categorical, 1-hot encoded, binary data. Data might look like, 0,1,1,0 1,1,0,0 1,1,1,0 0,1,1,1 0,0,1,0 I toyed with ...
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0answers
21 views

Is it okay to convert binary data to percentage data?

I have a within-groups study with 4 groups (400+ users). Each user answered 10 questions for each group. The answers were scored as right/wrong (1/0). Can the percentage correct for each user/group be ...
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0answers
20 views

Fleiss' Kappa alternative for inter-rater reliability with multiple answers

I have a dataset where researchers assign a binary yes/no answers to cells in a matrix. For each row more than one, but at least one, 'x' is allowed. For example, researchers 1 may code: ...
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0answers
12 views

Recommendation for type of analysis to measure whether intervention is effective

I have a dataset of about 90,000 cases. In something like 10% of these cases, an intervention was applied to hopefully bring about a specific outcome. The intervention was not equally applied across ...
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0answers
34 views

Binary classifier via Mahalonobis distance

In a recent conversation with a colleague at univerity, they mentioned that for a certain problem, we can "just use a binary classifier". When I inquired as to how they would train, they said "No ...
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1answer
22 views

Using a measure of productivity which is determined by reviewers

Apologies for the ambigious title - I wasn't sure how a problem like this is expressed. I have a small sample of 20 individuals, of which the dependent variable (of interest) is binary with 5 ...
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0answers
27 views

A binomial test with repeated measures?

I'm working on a study with a single trained animal (ie. our only participant). He is making a binary choice on a number of consecutive trials (we are essentially trying to teach him a rule -- if A, ...
2
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1answer
18 views

Test equality of binomial variances across four groups

I have four 100x1 vectors of binary outcomes of a particular experiment. I want to test for equality in variance across all of the four different treatment groups. At the moment I have used the ...
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1answer
62 views

Bayesian linear regression with continuous and binary covariates

I am interested in learning more about applying Bayesian linear models for covariates some of which are continuous and some are binary. What is the appropriate terminology for such models so that I ...
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1answer
92 views

binary logit regression - which test apply for detecting heteroskedasticity?

After reading a lot of different papers and a lot of different posts on the internet I still don't have a clue how to test on heteroskedasticity with my logistic regression (binary). The White test ...
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0answers
15 views

Synthetic Minority Oversampling with Binary Features in the data

I am planning to use SMOTE or ADASYN for creating synthetic observations for a classification problem as the data is imbalanced. The question is, there are Binary variables in the Feature set, and I ...
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0answers
42 views

Appropriate classification model for combination of continuous, binary and categorical inputs

I have a binary classification problem for classify my samples to two classes (class_1 and class_2). I have different kinds of ...
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1answer
130 views

Ratio between positive and negative examples in a training problem

When training a 0/1 classifier, what should be the ratio of positive to negative, how to decide the ratio between them based on the classifier I use and the data set under analysis?
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0answers
12 views

Kernel Methods for Binary Vectors

I am currently involved in a project which requires a minor point in choosing a proper similarity metric for a set of binary vectors, i.e. all components are either 1 or 0 . Currently, the go-to ...
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0answers
21 views

Binary Response Models & sample data that contain a disproportionate number of 0's

Sorry in advance if this seems like a dumb question, but I am new to data modeling. I am attempting to classify customer usage as either a case of fraud or legitimate activity. I have attempted to ...
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0answers
38 views

Effect of binary variables on binary outcomes

All I have two sets of data. One where people bought and another where they did not. For each sample in the two sets, I have ~3000 binary independent variables. Each dataset has about 1000 samples. ...
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0answers
20 views

How to determine significance across categories of binary data?

I have subjects that fit into one of three, mutually exclusive groups, "favorable," "intermediate," and "unfavorable" based on their genetics. They can then be classified as either a "responder" or a ...
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1answer
68 views

Optimizing for target metrics in Weka

I'm a PhD student in Information Retrieval with some limited experience in ML. We've been working on a binary classification task with weka (I'm using weka programmatically via Java), specifically ...
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0answers
29 views

How to analyse binary outcome data with between- and within subjects factors?

I am looking for the right statistical procedure to analyse my data (mixed design) with binary outcomes. Between-subjects variable: treatment (yes or no); experimentally manipulated Within-subjects ...
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0answers
26 views

zinb estimates change when using factor variables

I use Stata SE 13 and I have a problem with the command zinb in Stata. I have binary variable female which is 1 if respondent is female, 0 otherwise (no other ...
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0answers
10 views

test to be applied

I have applied 3 treatments at 10 different concentrations of each on a bacteria to see if they affect its existence. my response variable is binary i.e. 1 for effective and 0 for ineffective. basic ...
2
votes
1answer
57 views

c-index for parametric links in binary regression

I am conducting a binary regression using different sorts of parametric links (logistic, Pregibon, Aranda-Ordaz, ... see) and I would like to compare their predictive and classification perfomance in ...
3
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1answer
147 views

Cross correlation for very sparse binary data

I have a very large (5271159x60) sparse (~2.5%) binary matrix, and I'd like to calculate the cross correlation between each of the columns (sensors) for a series of lags from -10:10, which would give ...
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2answers
71 views

Fitting decaying exponential to binary response

I have this data that I want to fit with $y = e^{-bx}$, but the y:s represent probabilities and the outcomes are either 0 or 1, so I can't say $ln (y) = -bx$ since the values will just alternative ...
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0answers
65 views

Make a classification dataset with binary features using scikit-learn

I would like to illustrate a classification algorithm by using this algorithm on a 2-class dataset with binary n-dimensional features. In the past, I have used the scikit function make_classification ...
0
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1answer
125 views

Probability distribution of binary time series

I am unable to understand concepts related to the probability distribution of binary time series. This is from the book Binary time series by Benjamin Kedem, vol 52 Let $X_t$, t =0,1,... be a binary ...
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0answers
76 views

Two step cluster analysis and a binary matching coefficient

I want to commence a two-step cluster analysis, since the database I am conducting analysis on contains important metric as well as nominal values. => Question #1: Should the binary and the metric ...
0
votes
0answers
28 views

analysis strategy for selecting and/or transforming correlated continuous biomarkers to predict binary endpoint

I am given a simulation task to come up with several analysis strategies and compare their relative performances. The horizon is wide open; I appreciate all recommendations of methods and references. ...
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1answer
900 views

Hierarchical or Two-step cluster analysis for binary data?

(This question is an edited version of a question I previously posted which one user recommended would benefit from more focus). I have 2000 questionnaires from respondents which ask 33 different ...
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0answers
20 views

Cluster analysis of binary data [duplicate]

I have 2000 questionnaires from respondents which ask 33 different questions about which issues are present in their lives - i.e. alcohol abuse, domestic violence, mental health, child abuse, learning ...
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0answers
31 views

Feature boosting via rescaling in logistic regression and linear SVMs

If I were expressing a problem in terms of binary features, all encoded as {0,1}, could I boost some features by encoding them as {0,2}? Would the effect change based on whether I used either of the ...
5
votes
0answers
61 views

Identifiability in generalized linear random effect model?

Suppose I observe binary $Y_{ij}$ for $i = 1, ..., N$ and $j = 1, ..., J$ and I want to model $$\Pr(Y_{ij} = 1 \mid \lambda_{i}) = \Phi(\lambda_{ij}), \qquad [Y_{ij} \perp Y_{ij'} \mid \lambda_i]$$ ...
0
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1answer
34 views

Correlation or clustering of continuous score and discrete variable states

I have an experiment that produces a decimal score representing quality, and a bunch (5-30) of variables that each take on one of a set of discrete states. - The states are not meaningfully ...
4
votes
1answer
113 views

Closed form expression for count of “runs” in binary sequence sharing same length, number of 1's, and location of final 1

I am struggling with the following combinatorial problem related to research I am doing. Take a binary sequence $(y_1, y_2, \ldots, y_n)$ of length $n$ with $x$ $1$'s, where the final $1$ is in ...
0
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0answers
22 views

Binary event probability optimization

I have a relatively small sample of binary events (50-100 events) that occurred during a time of day (the success rate is closely related to the time of day). I'm grouping these events into hour ...
0
votes
0answers
10 views

Advice on finding features of users who converted vs. users who didn't?

I'm a programmer (comfortable in Python and R) and I'm getting started with machine learning methods. I have a lot of data from the past year about users on my site. About 50% of the users converted ...
2
votes
2answers
114 views

Which classifiers work well with unbalanced data?

I have a binary classification problem which is very unbalanced - it can have 98% of data from one class. Which classifiers work well with this sort of data? I have an unlimited supply of training ...
2
votes
1answer
84 views

Only binary predictors — ANOVA, regression, or other?

I am trying to fit a model to predict a quantitative response variable, using several binary variables. In particular, I am interested in measuring the relationship between one of the binary variables ...