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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6 views

Sample size for binary/categorical variables

I have a data set composed by 1000000 projects. Each project is characterized by its size in terms of KBs and a binary variable that is 1 whether the project is active, 0 otherwise. The distribution ...
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0answers
11 views

Measuring entropy of a 2d matrix

In this answer to the question Measuring entropy/ information/ patterns of a 2d binary matrix, the base-2 entropy of the 2-d matrices obtained from a series of moving window sum filters is measured: ...
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2answers
43 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 ...
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0answers
21 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 ...
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0answers
25 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 ...
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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 ...
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0answers
31 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 ...
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1answer
29 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 ...
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0answers
55 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
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0answers
49 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 ...
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0answers
34 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 ...
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1answer
63 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: ...
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2answers
99 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, ...
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2answers
152 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". ...
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0answers
20 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. ...
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0answers
44 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 ...
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0answers
36 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 ...
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0answers
11 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
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1answer
71 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 ...
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0answers
25 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 ...
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0answers
78 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 ...
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0answers
47 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 ...
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1answer
71 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?
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0answers
29 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 ...
4
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1answer
72 views

RandomForestClassifier Parameter Optimization

I'm a ML novice and I'm wondering if someone can critique what i'm doing (this is a bit open-ended). I have a very small corpus of text documents (n = 122). There is a binary decision associated ...
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1answer
36 views

Finding statistical significance between two binary tests

I have two sets of data. One with a sample size of 82 with 53 "hits" and 29 "Misses." And a second sample of 105 with 67 "hits" and 38 "misses" Given that the second set of data is a control, is ...
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1answer
70 views

similarity measures with missing values

How to handle missing values when computing similarity (or distances)? (I have binary feature values and do use the simple matching coefficient, but I feel that the answer to this question may be more ...
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0answers
21 views

Predicting binary vectors as a single response

My responses consists of vectors of 12 bits - each bit means a particular event in 1 month. I need to predict the probability of an event in all months -> so the predictions should also consist of 12 ...
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0answers
29 views

binarization of variable - experimental threshold choice. Is it good approach?

I have some ratings averages values from 1 to 5(users were rating on 1,2,3,4,5 scale). I would like to split them into two classes: credible, ...
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3answers
463 views

Logistic Regression and Inflection Point

We have data with a binary outcome and some covariates. I used logistic regression to model the data. Just a simple analysis, nothing extraordinary. The final output is supposed to be a dose-response ...
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0answers
35 views

unbalanced response variable

I have some general questions. Suppose I have a dataset with binary response Y, and some predictors. If the Y is not quite balanced, with say, many more 1's than 0's. Will it bring any potential ...
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1answer
62 views

Calculating and using factor scores

I have performed a factor analysis of 14 binary items (Satisfactory vs Not Satisfactory) which yielded 2 factors with 7 items each. I am interested in creating simple factor scores by summing ...
1
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1answer
70 views

How can I analyze “win rate” over time (i.e. on/off data over time)?

I have a series of data points that consist of 1) a time, and 2) a win or a loss. I would like to be able to determine the aggregate win rate for particular time periods, and graph it. For instance, ...
4
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1answer
155 views

Visualizing longitudinal data with binary outcome

For longitudinal data with a numeric outcome, I can use spaghetti plots to visualize the data. For example something like this (taken from the UCLA Stats site): ...
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0answers
33 views

How to treat binary outcomes with categorical explanatory variables

I am trying to apply a GLM in R. I have a binary response (success vs failure), and 3 categorical explanatory variables : Sex (male or female), Food (present or absent) and Wind (none, low, high). I ...
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votes
2answers
122 views

What are the most commonly used predictive models when dealing with binary data?

I know everybody uses logistic regression as the starting point, but I'm curious to know: What are the other commonly used predictive models when data is primarily binary?
1
vote
2answers
71 views

Unsupervised Dimensional reduction for mixed data types

I have a data set with about 50K rows and 100 columns. You can consider every row to be representing one restaurant. My goal is to calculate dissimilarities between all the restaurants - Gower's ...
0
votes
1answer
42 views

Comparing two survey items with a third variable

I want to compare the results of two items by age category and do not really know what test to use. I tried a Cochran–Mantel–Haenzel–test at first, but I don't think it is testing what I really want ...
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0answers
34 views

Binary features for prediction

I have a set of relatively long (~1000) binary features with scalar values [0-10] attached to them. My aim is to write a predictor that learns to map the features to the [0-10] interval to predict new ...
0
votes
0answers
53 views

how to perform factor analysis for clustered longitudinal binary data?

I measure a longitudinal binary outcome (correctness of detection, 0: incorrect, 1: correct) with respect to 5 different experimental conditions (1 baseline and 4 treatments). The outcome is always ...
1
vote
1answer
74 views

Cluster large boolean dataset

I got a dataset with about 5,000 columns and about 135,000 rows - all fields contain boolean (binary) data. I am looking to classify each of these columns into one of 50 groups, based on similarity. ...
1
vote
0answers
92 views

How can I measure the association between 40 binary variables?

I have 40 binary (0/1) variables with 70 observations and would like to measure the association of occurrences between them. Is the presence or absence of a variable is associated with the presence / ...
1
vote
1answer
629 views

(Multiple) Correspondence Analysis for count data entered as binary variables

I have a data set, 1014 cases and 55 variables which are binary and is in the form of ...
0
votes
1answer
95 views

Coefficient of determination for binary responses

D.R. Cox and Nanny Wermuth seem to suggest that the coefficient of determination (R squared) is misleading when you have binary responses, in fact if I am understanding well, they are saying that the ...
0
votes
1answer
51 views

Two different methods…different results?

I have a response variable and 10 predictor variables (all ordinal). I wanted to see if there was any evidence of a relationship between the response and predictors. I used a two proportion z-test to ...
2
votes
0answers
52 views

Ways to compare ordered binary datasets?

This question regards the best way to compare ordered binary data. My situation is as follows: I'm interested in evaluating how well a model conforms to human performance data on a set of validation ...
0
votes
1answer
255 views

Variance and covariance of binary data

The variance of a set of $n$ binary variables $D = <x_1, \ldots, x_n>$ is $$ {\rm var(D)} = \frac{k(n-k)}{n^2}, $$ where $k$ denotes the number of $1$s in $D$ (see ...
4
votes
2answers
222 views

Prediction of a binary variable

I am establishing a model for prediction of a binary variable (Yes/No) depending on three continuous variables ($A$,$B$,$C$). I applied logistic regression analysis for a learning dataset vith the ...
4
votes
5answers
135 views

How to measure a classifier's performance when close to 100% of the class labels belong to one class?

In my data, I have a class variable, denoted as $C$. This class variable values are ${0, 1}$ (binary). Almost all observations of $C$ are 0 (close to 100%, more precisely, 97%). I would like a ...
2
votes
0answers
91 views

How to measure the strength of association between binary variables where the majority of values is zero?

I have two binary variables, $X_1$ and $X_2$, which take value in {0, 1}. The overwhelming majority of their values are 0. I wanted to know if there is a way to appropriately measure their association ...