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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11 views

High asymmetric binary variables [on hold]

I have a set of binary dependent variables where most values are concentrated in one category. Which methods are adequate to analyze such data and which restrictions or difficulties are usual in this ...
1
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1answer
16 views

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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0answers
16 views

Prevalence ratio in Poisson regression for Binary response variable Using R

I have a data set on stunting (Height for Age) status of children and their socio-demographic information. If I want to find the socio-demographic determinants of stunting where dependent variable ...
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0answers
7 views

How to fix a scale of latent variable measured by dichotomous indicators in SEM

How can I fix a scale of latent variable measured by dichotomous indicators in a structural equation model to estimate the mean of that latent variable? I know the mean of that variable (because I ...
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0answers
13 views

Order of cases in clustering methods [closed]

When I run a hierarchical cluster analysis with only ordinal binary variables (asymmetric categories: present vs absent), the output (e.g. the assignment of cases to clusters) is dependent on how my ...
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0answers
15 views

Binary variables [closed]

What are the common error rates for predicting binary variables or in other words, what are the error paramters that are important while doing logistic regression? eg we look at AIC in MLR
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0answers
20 views

R: Binary outcome and semiparametric estimation

Consider the following model: $$ y = f(g(x_1, x_2) + \beta_3 x_3 + \beta_4 x_4) + \epsilon $$ where y is a binary outcome variable and $P(y = 1 | X) = f(g(x_1, x_2) + \beta_3 x_3 + \beta_4 x_4)$ ...
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0answers
12 views

Binary variance? Comparing two sacks of uneven coins or two heterogenous groups of people

I have two sacks of coins. In one sack, the coins are all uniform, each giving a fairly constant 0.5 chance of heads (based on tossing a few of them and also visual inspection). I then estimate the ...
0
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0answers
25 views

Statistically compare differences between output probabilities of two trained models

I'm using two classification models that compute output probabilistic for my out-of-sample data (MLP and SVM). I want test that ...
0
votes
1answer
33 views

Normalizing a Continuous Variable for Appropriate Use Alongside Binary Variables

I am fitting a model where I estimate my Dependent Variable based on about 20 Binary Variables (0/1), and one continuous variable. I've read about the importance of normalizing that continuous ...
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0answers
29 views

Difference between treatments with binary outcome & sample size estimation - Stata

I have 20 binary outcome variables that I want to test for association with a nominal 'treatment' variable with 6 categories (a,b,c,d,e,f). For the outcome that is significantly associated with ...
2
votes
1answer
59 views

What is the best statistical model for my binary outcome variable?

My hypothesis is: As the experimental count variable increases, the probability that the binary dependent variable equals 1 increases. I expect both the independent and dependent variables to be not ...
1
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0answers
16 views

How to analyse data from multiple binary decisions?

In an experiments participants will be presented with pairs of sentences and they will have to pick which of the two is closer to the way they would say things (two-alternative forced choice). There ...
0
votes
1answer
29 views

Naive Bayes Binary Classification with Binary Features

I have a dataset with two classes $C_0$ and $C_1$. I have around $10$ to $20$ features that take binary values (either $0$ or $1$). My dataset has around $10000$ instances, with only a hundred of ...
0
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0answers
8 views

Successfully simulated physical process, matches truncated/incomplete data…now what?

What's Being Simulated I have data from a device that tests a physical process. The data are independent Bernoulli trials. Each test series yields a distribution of these trials with different N and ...
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0answers
58 views

Trained Logistic Regression returns 'NAN' for some out of sample data

I'm using MATLAB R2015a, glmfit function for training and glmval for out of sample ...
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2answers
26 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
50 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 ...
6
votes
3answers
198 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
9 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 ...
2
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0answers
39 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 ...
0
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1answer
73 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 ...
1
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0answers
22 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 ...
0
votes
1answer
27 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 ...
2
votes
1answer
48 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
81 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 ...
1
vote
1answer
127 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
votes
1answer
71 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
47 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 ...
1
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0answers
27 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 ...
0
votes
0answers
46 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: ...
1
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0answers
16 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 ...
1
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0answers
36 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 ...
1
vote
1answer
23 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 ...
1
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0answers
45 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
votes
1answer
36 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 ...
3
votes
1answer
84 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 ...
0
votes
1answer
202 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 ...
0
votes
0answers
26 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 ...
0
votes
0answers
53 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 ...
1
vote
1answer
199 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?
0
votes
0answers
17 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 ...
0
votes
0answers
32 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 ...
1
vote
0answers
40 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. ...
0
votes
0answers
23 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 ...
1
vote
1answer
130 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 ...
0
votes
0answers
41 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 ...
0
votes
0answers
33 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 ...
0
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0answers
12 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
60 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 ...