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 ...

learn more… | top users | synonyms

0
votes
0answers
8 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
9 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 ...
1
vote
2answers
66 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
26 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 ...
0
votes
1answer
31 views

R - Analyzing Relationship Between Two (or more) Binary Variables

Say I have two vectors: Action.Taken = c(0,1,0,0,1,1,0,1,0) Success = c(0,0,0,1,0,1,0,1,0) The first tells me whether or not a specific action was taken in a ...
3
votes
3answers
57 views

Test for aggregation of binary events/successes (binomial/glm??)

this has been vexing me for a while and I can't seem to solidify an answer beyond vague thoughts about Poisson distributions. I think this is a simple problem and I'm missing something obvious. Any ...
0
votes
1answer
21 views

How to deal with a skewed class in binary classification having many features?

I am doing data analysis in the mobile ad targeting domain. I have around 18 features and for a combination of these features, the result is either True or False (1/0) depending on whether the ...
1
vote
1answer
17 views

How to analyze two-way within subjects design with binary data

I am interested in testing how users perform on three different user interfaces. On each of the three interfaces, a person will try 12 Tasks. So each participant will do Task 1 three times, Task 2 ...
0
votes
2answers
71 views

Best way to test for co-occurrence of measures

I have some data with temporal measures over time. I'd like to test whether two binary variables co-occur more often than chance would predict, and I'm wondering the best (simple) way to do that. The ...
1
vote
0answers
29 views

What to Do When a Log-binomial Model's Convergence Fails

There are times when one might want to estimate a prevalence ratio or relative risk, in preference to an odds ratio, for data with binary outcomes - say, if the outcome in question isn't rare, so the ...
1
vote
0answers
34 views

Regression analysis with binary independent variables

Should one use regression analysis when all independent variables are binary categorical (0,1) to see their effect on continuous dependent? Some suggest that regression shouldn't be used in this case. ...
0
votes
1answer
72 views

PCA on Binary Data

I having binary data set (yes/no), so can I apply PCA on that. Is it mathematically correct to do that. In my opinion Binary variable can only be subjected to logical operations, so how it can be ...
2
votes
1answer
75 views

Is it meaningful to calculate Pearson or Spearman correlation between two Boolean vectors?

There are two Boolean vectors, which contain 0 and 1 only. If I calculate the Pearson or Spearman correlation, are they meaningful or reasonable?
0
votes
1answer
26 views

How to analyze relationship between a nominal variable (2 values) and a numerical variable (integer)?

I'm trying to find out if a nominal variable A (2 values: x and y) and a numerical variable ...
1
vote
0answers
16 views

Stratified Cross-Validation with Collaborative Filtering

My dataset consists of binary preferences ($0$ or $1$) given by users on items like this: User-ID | Item-ID | Preference If a user has not given a preference to an item, then it is not in ...
0
votes
0answers
12 views

Implementation of semi parametric methods

Has anyone worked with semi parametric methods to estimate parameters with binary outcome? Examples are like Cosslett (1983) or Ichimura or Klein-Spady. In other words we are looking for semi ...
0
votes
1answer
26 views

Paired test for comparing boolean data

I have $n$ individuals, and for each individual, I have two measurements using two devices (device X and device Y). I know the ground truth for the correct measurement, and I can classify each ...
0
votes
0answers
37 views

Hypothesis test for comparing two F-measures

I have a classifier that classifies each sample point as positive or negative. Suppose I am evaluating it on a limited data set where I have ground truth and then computing the F-measure ...
0
votes
1answer
40 views

How do you correlate binary & ordinal variables?

Which test to use to calculate correlations between them? Cramer's V, Kruskal-Wallis, or something else?
0
votes
0answers
20 views

I have data that includes a record of each event and its time

I want to see if this other data I have predicts that this first event will occur. In other words, I have a data field with a record of farts, with columns for day, month, year, and then I have ...
0
votes
0answers
36 views

What's the meaning of the class indicator matrix when transforming the class label matrix into it in canonical correlation analysis?

When using canonical correlation analysis (CCA), we can integrate the dataset and label information via transforming the class label matrix Y into the class indicator matrix T. Such as: $T = ...
2
votes
0answers
29 views

Comparison of point-biserial and linear correlation coefficients

I have a continuous variable X that is associated with a continuous outcome Y and a dichotomous outcome Z. If I calculate Pearson's $r$ between X and Y, and the point-biserial coefficient $r_{pb}$ ...
0
votes
0answers
91 views

Output probabilities of binary support vector machine classifier in Matlab R2014a

I’m using SVM for classification of my binary output problem. I want probability of belonging to every class. How can I obtain it? For instance suppose this is our structure: ...
0
votes
0answers
55 views

Running a Pearson's correlation calculation on binary survey data

I have the following raw survey data output from a survey app: I was asked to run a Pearson's R on the results (1s and 0s). The format that is returned is as follows: I was further ...
1
vote
0answers
50 views

Prediction method where predictors and response variable are binary

I have a group of binary tasks performed by multiple subjects. Every task can be either performed right or wrong (i.e.,1/0). My goal is to predict the accuracy of future task given the performance on ...
3
votes
2answers
111 views

Logistic regression vs. LDA as two-class classifiers

I am trying to wrap my head around the statistical difference between Linear discriminant analysis and Logistic regression. Is my understanding right that, for a two class classification problem, LDA ...
1
vote
0answers
119 views

Factor analysis with binary variables using Stata 13

I am trying to do confirmatory factor analysis on data that is coded binary (0 no, 1 yes). UCLA suggests using a tetrachoric ...
1
vote
1answer
29 views

When looking at the association between binary variables, when are odds ratios better than risk ratios and vice-versa?

The Wikipedia page lists some scenarios: While both measures are useful, they have different statistical uses. In medical research, the odds ratio is commonly used for case-control studies, as ...
1
vote
2answers
200 views

Understanding dummy (manual or automated) variable creation in GLM

If a factor variable (e.g. gender with levels M and F) is used in the glm formula, dummy variable(s) are created, and can be found in the glm model summary along with their associated coefficients ...
0
votes
0answers
43 views

Problem with year as a factor GLMM

So I need to do a GLMM, I do it this way, with package lme4 glmer(y~x1+x2+x3+year+(1|x4),family=binomial In my data, year is a factor (4 levels). So when I run my glmer, I have my result like this x1 ...
2
votes
0answers
37 views

What is a good technique for grouping objects based on binary or dichotomous traits?

I have a set of objects each of which has a list of traits. Data on the traits is binary: an object has a trait or does not. The number of objects that I have is moderately greater than the number ...
0
votes
1answer
20 views

Which test is useful to assess if a source is the same in two samples of binary data?

I am looking for a statistical test that assesses if two samples which have binary values come from the same source or from different ones. Example: I have one set that has 10 0s and 6 1s and ...
0
votes
0answers
49 views

Best Regression with Binary Features

I'm seeking to do a linear regression for an evaluation function in a board game. My features are all (signed) binary 1 0 0 1 -1 1 0 0 0. Mostly zeros. Around 200 to an observation. I have 10 million ...
1
vote
1answer
35 views

(very basic) One-sample test for binary data

I've repeatedly measured a continuous variable and each measure has been assigned a populational percentile range it falls into (percentile ranges were estimated for general population in another ...
2
votes
0answers
71 views

Predicting Next Likely Outcome of Binary Time Series?

I'm trying to approach the following problem: Danny & Johnny are professional basketball players. Each day they meet, and play for a while. Whoever scores the most points is declared winner for ...
2
votes
0answers
59 views

Modeling binary outcomes - inaccurate model when using logistic regression?

I am trying to model the probability of a binary outcome with the independent variable being an hour variable. I understand that linear regression is not the correct method for this type of task (I ...
1
vote
0answers
59 views

I'm stuck: How to 'bin' multiple binary outcome variables and then analyze within subject?

I have what feels like it should be a very easy analysis to work out, but I've been trying for hours and I can't figure it out. I'm using SPSS by the way. I have 10 (5 of each group) different binary ...
1
vote
1answer
85 views

Strength of association test with binary variables

I have a dataset with different purchases for two different items from the same users. So the users purchased the two items at different points in time. I also have 3 different variables: ...
2
votes
2answers
113 views

Comparing predictions from models

I'm wondering how to compare the predictions of three different models - a logit, a probit and a linear probability model - when predicting a binary outcome. I'm currently working with simulated data, ...
0
votes
2answers
720 views

Clustering a binary matrix

I have a semi-small matrix of binary features of dimension 250k x 100. Each row is a user and the columns are binary "tags" of some user behavior e.g. "likes_cats". ...
1
vote
0answers
25 views

Finding range of time with best probability of positive event occurring

I have data representing a couple hundred of independent experiments. Each one contains time - how long did the experiment took and outcome: positive and negative. There is 10% of positive outcomes. ...
1
vote
0answers
69 views

Binary Classifier evaluation when Precision is more important than Recall

Problem statement A set of points is given. We want to classify those points in two distinct classes with labels $\{0,1\}$. We count the "hits" of the classifier based on the $1$ class. Assume that we ...
0
votes
0answers
47 views

Decompose LibSVM model into binary classifiers

I have a multi-class .model trained with LibSVM. Is there a way to decompose this model into different binary .model files? For example, if I have a .model trained for $n$ classes, I would like to ...
0
votes
0answers
12 views

How do you compare methods when they produce different binary answers?

I am trying to compare two methods for evaluating diagnostis of menisci in the knee. One is ultrasonographic where we can have 6 different diagnostic outcomes. The old method that serves as the gold ...
2
votes
1answer
78 views

Determine if an action increases the proportion of 1s in binary data with unknown population

We're trying to improve search results, and we're trying to determine if certain changes (adding a word to a synonym list, removing it from the query, etc) have a statistically significant improvement ...
0
votes
0answers
39 views

Maximizing F1-measure, when you have an algorithm for minimizing another loss function

Let's say you have an algorithm for minimizing the following loss function: $$ loss = \sum_i l(y_i, f(x_i)) $$ Let's say you are in the binary classification case, and the ratio of negative to ...
1
vote
0answers
115 views

Canonical correlation analysis

I have to do canonical correlation analysis between two multivariate datasets X and Y. One dataset contain numerical data and the other binary data.I would like to know what features are highly ...
0
votes
0answers
57 views

Probabilistic Modeling based on aggregate finite element results

I have results from 50 experiments performed. The only outcomes I have are structural failure, or no structural failure (go or no-go). My input variable is an external load. Say my structure failed x ...
0
votes
1answer
110 views

Calculating total score for a scale including polytomous and dichotomous items [duplicate]

I have a variable that is measured using a 13-item, 4-point Likert scale with the exception of one item (yes $=1$, no $=2)$. How can I calculate the total score for this variable?
2
votes
0answers
32 views

Patterns in binary data sorted with rank indices

I have a sequence of binary data, each row of which has seemingly random bits and associated with an integer value ("rank"). When we have a binary datum, we always can calculate the rank related to it ...