Questions tagged [binary-data]

A binary variable takes one of two values, typically coded as "0" and "1".

Filter by
Sorted by
Tagged with
0
votes
1answer
37 views

Goodness of fit for Linear Probability Model (LPM)

I'm running a linear probability model (LPM), i.e. my outcome is binary and I have predictors that are categorical and continuous (I'm aware of some of the pros and cons of using LPM for a binary ...
0
votes
0answers
16 views

Outlier Analysis on Qualitative Data [closed]

I have qualitative dataset to analyze with also many extra variables containing 1s and 0s. While trying to perform an outlier analysis with robustness techniques is not possible, I was wondering if ...
0
votes
0answers
17 views
+50

Pre-study sample-pairing validity (two same-scaled IVs, binary DV)

Summary: is pairing samples ahead of time okay for testing? What test do you use given the resulting assumptions? Overview Goal: The goal is to determine which IV has a stronger influence on (...
2
votes
1answer
33 views

Can Hosmer-lemeshow chi-square statistic explain calibration?

I'm doing a logistic regression and created a calibration plot. I also conducted a Hosmer-Lemeshow test and got the corresponding chi-square. Is there any relationship between the calibration plot and ...
1
vote
0answers
27 views

Checking if amount in subgroup is significant to population

I have a population of known size N. For each element I can state whether an attribute is true or false. I can also divide the population into distinct sub populations. Each sub population is of the ...
0
votes
0answers
39 views

Binary Logistic Regression all binary categorical variables

I am running a binary logistic regression for my data using mini-tab. I feel as though I am doing something wrong because the p-values given for each of binary categories for an independent variable ...
0
votes
0answers
21 views

How to deal with unbalanced binary independent variables in logistic regressions

Suppose I want to investigate the impact of some binary independent variables (let’s say: sex and height [tall/short]) on my binary response (alcohol consumption for instance). The distribution of my ...
0
votes
1answer
21 views

Running A Regression Analysis where the Response is a Binary Variable [R]

BACKGROUND Hello, I am relatively new to R. I am trying to execute a regression of winning percentage against a certain set of statistics. I have had experience with regression when the data is ...
0
votes
1answer
17 views

Can I conclude that the classifier is always good when Precision-Recall Curve above the baseline?

I used logistic regression for highly imbalaned data (1=0.6% , 0=99.4%) Since PR curves are sensitive to imbalance, so i used it, but I don't know how to interpret graph appropriately. This is PR-...
0
votes
1answer
18 views

Minimizing population risk for logistic loss

I am working on trying to show that the minimizer is equal to as given in this question. However, I can't this exact result and am starting to my book exercise has a typo. Here is my work:
0
votes
1answer
40 views

how to caculate 95% CI for AUC? try 384 times or Hanley et al. (1982) method?

I am working on a prediction task to predict heart disease risk. The data size is around 1500 and is splitted into train, validate and test datasets. I am use train dataset to train and use validate ...
0
votes
0answers
8 views

Display inverted ROC plot

my anomaly detection algorithm gave me an array of predictions where all the values greater than 0 should be of the positive class (= 0) and all the other should be classified as anomalies (= 1). I ...
0
votes
0answers
22 views

k-medoids on binary data

I have a binary dataset and I would like to cluster it with the k-medoids algorithm. The dataset is not huge: I have 10 dimensions and around 250 objects. I am clustering physical infrastructures ...
0
votes
0answers
30 views

Basis of Binary Classification Probability

I am fairly new to Machine Learning and recently I have built a binary classification model and the model architecture is an MLP with two hidden layers. I am predicting, from a protein sequence, the ...
1
vote
0answers
41 views

Which formula to use for logistic regression with different predictors?

I'm doing a logistic regression with "Choice" (Yes or No) as dependent variable and 3 different predictors, including reward, demand (5 level each) and condition (0 or 1) and their ...
0
votes
1answer
21 views

How can be normalized value from logistic function used to determine probability of binary classifier outcome?

I would like to discuss chapter that comes from Foreign-Exchange-Rate Forecasting With Artificial Neural Networks. This chapter (see screenshot) describes a binary classifier made from neural network ...
1
vote
1answer
14 views

Using individual predictions from binary classification model to predict class proportions in group

Suppose I have a group of users of a paying app and I want to predict each month the users that are not going to renew their subscription. This is called churn rate. To do that I create a binary ...
2
votes
1answer
45 views

Does the output of a binary classification model equal to the probability of a positive outcome?

Assuming you have a binary classification model $M$ i.e. that for an input $x$ it outputs a number $M(x)=\hat{y}$ where $\hat{y}\in[0,1]$ predicting the binary label of $y\in\{0,1\}$. For example, a ...
1
vote
0answers
14 views

Can I pool studies in a meta analysis with binary and continuous outcomes? [duplicate]

I'm currently completing a meta-analysis (in r using the meta/metafor package) looking at predictors of treatment response in patients suffering from a particualr mental disorder (psychosis). Some ...
0
votes
0answers
23 views

Assumption testing: Binary Logistic regression with ONLY categorical variables - Help?

I am doing a project with a bivariate outcome variable (yes/no) and 8 predictors, which are measured categorically with 2 to 5 categories each. How do I test the assumptions of regression in SPSS for ...
0
votes
0answers
28 views

When is the Conditional Expectation equal to the Best Linear Predictor for Binary Variables

Given random variables $X$, $Y$ and $Z$ where $X$ and $Z$ are binary, when is $E(Y|X)=BLP(Y|X)$? What about $E(Y|X,Z)=BLP(Y|X,Z)$? What about $E(Y|X,Z,XZ)$? This is what I have so far: $E(Y|X)= E(Y|X=...
0
votes
0answers
12 views

Determine if two groups differ for a series of binary variables - logistic regression

I am trying to determine how to analyze my dataset. I have two stimulus categories (Type 1 and Type 2) and then a series of variable observations that are binary (did respond/didn't respond, did ...
0
votes
0answers
16 views

For a group of n equally probable outcomes, how many ways can groups of n outcomes occur when each outcome is independent of previous selections?

Example: I have 3 coinflips. How do I calculate the probability of any possible outcome if I repeat the 3 flips many times? There are 8 possible sequences for the 3 flips ranging from all heads to ...
1
vote
0answers
20 views

Is there an equivalent statistic to partial R-squared in logistic regression?

My dependent variable is a binary outcome(Y); therefore, I am using logistic regression. I am interested in what proportion of variance of Y is explained by the variable X1. In other words, I am ...
0
votes
0answers
6 views

Help with calculating probility of outcomes between two correlated binary events [duplicate]

My google fu has failed me to find a method for this. I would assume there is a deterministed equation for what I'm trying to do but maybe it's more complicated than I am thinking. I have two binary ...
0
votes
0answers
62 views

Choosing a test

Let's say you run a restaurant and you want to work out which ingredients result in the best feedback (unhappy, neutral, happy, somewhat unhappy, somewhat happy) of the restaurant. Your data might ...
0
votes
0answers
5 views

GLM residual assumptions modelling binary response variable

I'm taking a intro to modelling course at my university. We are currently learning about modelling Binary response data. I am confused about the assumptions of the Generalised Linear Model, in R. ...
0
votes
0answers
16 views

Random effects covariance parameters: Participants ID

so I have a very basic question which really confuses me. I'm comparing the acceptance rate (yes vs. no) of two independent groups, participating in a task where they have to decide if they either ...
1
vote
1answer
33 views

measure if some binary events happen in random or are correlated

I have thousands of binary processes of uneven length like those below: ...
0
votes
0answers
18 views

Implementing Granger causality for 2 binary event timeseries

I am trying to understand how to implement granger causality to binary valued timeseries data (0/1). I only found one other question on here at Granger Causality Analog for Binary Time Series, but the ...
1
vote
1answer
47 views

Exploring shifts in response to dichotomous dependent variable

I have one dichotomous dependent variable (buried with grave goods or not) and a series of categorical and continuous independent variables (age at death, year of death, sex, socioeconomic status) for ...
1
vote
2answers
16 views

How do covariates influence the sample sizes for survival and binary outcomes?

Currently, I try to wrap my head around the concept of how covariates influence non-normal outcomes like survival and binary outcomes. I know that in linear models the unexplained variance shrinks ...
1
vote
1answer
221 views

Question on Optimal predictors for the 0-1 loss function

The input $X \in \{0, 1\}$ and label $T \in \{0,1\}$ are binary random variables, and the set of predictors that we consider are the functions $y : \{0, 1\} \rightarrow \{0, 1\}$. Recall the $0$-$1$ ...
2
votes
1answer
38 views

Difference-in-differences - Binary data

I am working on an exercise using conversion rate data on a travel website. The conversion rate is defined as the number of users in a given time period that make a purchase. There are two groups, A ...
1
vote
0answers
103 views

Estimate Causal Effect of Treatment on Binary Outcome

I am a newbie with zero experience regarding the estimate of causal effects of treatment on binary outcome and this is my first post on stackexchange. I have an unbalanced panel sample of about 5,000 ...
0
votes
0answers
9 views

Can I use LMEM to select categorical features if some features are interactions?

I have sort of a general best practices question here. I using LMEM to do some exploratory analysis from a project, and I just want to see whether my approach holds any water. The project is this -- I ...
0
votes
0answers
16 views

Calculating Area Under the Curve Receiver Operating Characteristic AUC ROC [duplicate]

So on wikipedia here is the definition for area under the curve of the receiver operating characteristic. Can someone give a simple example of calculating this given some predictive results in a ...
0
votes
0answers
39 views

How to interpret (deviation coded) GLMER fixed and random coefficients

I am a Master's student dealing for the first time with glmer modelling on binary data. Part of the data that I collected during an online psycholinguistic ...
1
vote
0answers
244 views

Find the best threshold for logistic regression?

I am working on a customer purchase problem. I have 150 campaigns sent by email (or adds if you prefer), that I denote C0, C1 ......
3
votes
1answer
28 views

Is my interpretation correct? - Independence of binary predictors in multiple linear regression

I'm confused about the interaction of binary predictor values in multiple linear regression. Here's an example to illustrate my problem. Say that I want to investigate the relationship between life ...
3
votes
1answer
305 views

Predicting a binary variable whose values in the sample are severely unbalanced

I have a data set with a binary variable which is 0 for 94% of observations and 1 for 6% of observations. If I fit a model (say logistic regression) to predict this variable in a way that maximizes ...
0
votes
0answers
13 views

Saturating growth model for binomal data

I need to estimate a probability from a set of successes observed over time. I this application I have multiple ‘looks’ at the data, and need to estimate ‘p’ from this. Because of this, i thought that ...
3
votes
2answers
167 views

Why does the glm function converge and not give an error when all y's are equal to the same value?

I need to fit a univariate logistic model with few observations (between 10 and 20). In some cases, y is equal to the same value (example 1) for all observations. Theoretically, the model should not ...
0
votes
0answers
8 views

How to deal with a large set of missing values in categorical variable

I have a dataset of around 5500 observation. One the variables is Gender for which at least 25% of the observations are missing. Dropping the missing values seems a ...
0
votes
0answers
14 views

Testing binary data for automation vs manual handling

I am looking for a suitable test for a set of binary data. Basically, we are verifying a piece of automation for a molecular biology process. We are testing samples that are either positive or ...
0
votes
1answer
20 views

Linear regression for rank variable(DV) vs binary variables?

Im triyng to find the influence(relevance) of three binary variables(1/0) on my dependent variable that is a 1-10 scale. Is linear regression the best type of regression for this kind of analysis? ...
0
votes
0answers
24 views

Which predictive model is best fit here?

I have two predictor variable both numeric with right skew. My outcome variable is binary as positive and negative. Sample size id 157 and positive cases are only 10. That's just 6.37%. I know there ...
4
votes
1answer
42 views

Small group size inference for logistic regression

Please note this analysis is being done retrospectively (i.e., all data have been collected). I have a binary response variable $y_i \in \{0, 1\}$ and two covariates $x_{1i}$ and $x_{2i}$. $x_{1i}$ is ...
-1
votes
1answer
44 views

Determining sample size for comparing rate of occurrence between two groups

Scenario: You are running a comparative clinical study. A test product is being used by one portion of the population (Group T) and a control product is being used by another (Group C). The Question: ...
0
votes
0answers
19 views

Should "rake throw" data be treated as binary, Poisson, interval-censored, ordinal, or...?

I'm currently analyzing "rake throw" data (see here for details), which are a type of data I'm not as familiar with. The gist is that aquatic plant presence and abundance are often estimated ...

1
2 3 4 5
25