Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

learn more… | top users | synonyms (1)

0
votes
0answers
14 views

How to deal with categorical features.

Recently I am playing in the famous Big-Data website Kaggle. There is a Display Advertising Challenge. In this competition, you are giving a training file which include huge records. the records is ...
0
votes
0answers
13 views

Is there deep learning,especially RBM, code that is really good to do classification [on hold]

For example, I found some code , but they didn't do wake-sleep algorithms to adjust the weights. I am especially interested in the one that google brain used for recognizing "cat" from youtube, no ...
0
votes
0answers
28 views

Probability of Default

I'm doing a project to predict probability of delinquent for individual loans. Seems the model I fit is not good and I want to improve the model. However, I'm confused by the results I got and don't ...
0
votes
0answers
9 views

package in R for BMA of a logistic model?

I am trying to perform analysis similar to Gerlach et al. (2002). it involves predicting the posterior probability of a particular binary outcome using the previous 5 observations. I was just ...
1
vote
0answers
13 views

geepack: parameter estimates change sign depending on correlation structure

I'm working on a dataset with the following variables: ...
0
votes
1answer
25 views

Estimating Multinomial Multilevel Logistic Models by Binomial models

I would like to fit a multinomial multilevel logistic Model. Unfortunately I couldn't find a package that implements this. I tried Stata's ...
0
votes
0answers
20 views

How can Principal Component Analysis applied to logistic regression or binary dependent variables? [on hold]

How to establish logistic principal component analysis? Is it meaningful to apply PCA to binary dependent variables?
0
votes
0answers
24 views

Logistic vs. Linear regression for recovery rate modeling

i am trying to model recovery rates in my data that are in the range of (-.1,+1). Around 8% of my observations are negative too. Broadly, below is the dist.: RR<0: 8% RR=0: 30% RR>0 and ...
0
votes
0answers
15 views

Measures of goodness-of-fit using multiply imputed data in Zelig

I am running a logistic regression model in R using multiply imputed data created using Amelia II, which I am then analyzing using Zelig. I would like to be able to report some measures of ...
7
votes
3answers
95 views

testing logistic regression coefficients using $t$ and residual deviance degrees of freedom

Summary: Is there any statistical theory to support the use of the $t$-distribution (with degrees of freedom based on the residual deviance) for tests of logistic regression coefficients, rather than ...
0
votes
0answers
28 views

piloting a multinomial logistic regression model

I have 11 variables in my data set. farmers Group(1,2,3,4 this is my dependent variable) Independent variables Total holding ,Crop area , barn capacity.....and barn capacity extent match and YPH. ...
0
votes
0answers
20 views

Is there a way to customize my likelihood function for logit models using speedglm/biglm/glm packages?

My goal is to fit a custom logistic regression/survival analysis function using the optim/maxBFGS functions in R and literally ...
0
votes
0answers
16 views

Fitting mixed effects logistic regression with random effects

I have a data frame of 134 observations, 9 independent variables, and a binary, categorical response; please see its structure below: ...
0
votes
1answer
47 views

Relationship between the latent variable as a function of regressors and the logit model?

Can anyone give the intuition behind of the relationship between these two? I see a lot of proofs in books, but no real intuition. Thanks
0
votes
0answers
8 views

hierarchical logistic regression Block non-significant, interaction significant

I'm using hierarchical logistic regression and having some difficulty. Im trying to predict self-harm vs none based on IVs age, gender, alcohol, educational attainment. They are all yes/no except ...
0
votes
2answers
59 views

Interpreting conflicting results from Random Forest & Logistic Regression?

I am using SKLearn and Statsmodel in python to build a RF and Logistic Regression, respectively. I have a feature that the RF indicates is important (feature importance of 0.202, closely behind #1 ...
1
vote
2answers
53 views

Differing p values (significant and insignificant) for the same predictor variable in different AIC models

I'm looking at a multinomial logistic regression analysis of deer behavioural responses to camera traps. The levels of the response variable are no reaction, ...
0
votes
0answers
20 views

Reporting : Risk ratio vs Odd ratio

I have employee attrition model. I have reported odd ratios.My question is " can i use risk ratio?". Example : The odds of male to get attrited is 2.5 times than males. It is non-intutive for layman. ...
0
votes
0answers
17 views

How can i make a fraud detection dataset (I have the data ready but unordered)

I'm a little confused with the creation of the dataset for a fraud detection predictive model. Here i put a link with a sample of the dataset that I made. (the real dataset have ~950.000 clients). ...
2
votes
0answers
53 views

Average of predicted values with logistic regression

I have a large unbalanced dataset (the target has ~1500x more 0's than 1's) on which I train a logistic regression algorithm to predict the probability of success (Not a binary outcome but a real ...
0
votes
0answers
10 views

split file in weka

I want to run a logistic regression were the file is split on a certain value, namely key (major and minor) and I want to see if the other values are able to predict the ranking of a song. But I have ...
1
vote
2answers
74 views

Regression - Is it incorrect to *not* include an independent variable I'm not interested in, but which *may* affect the depend variable?

I am conducting an ordinal logistic regression. I have an ordinal variable, let's call it Change, that expresses the change in a biological parameter between two time points 5 years apart. Its values ...
0
votes
0answers
19 views

Binary regression accuracy vs model fit in R

I ran two logistic regression models, one with a dataset including outliers and one without outliers, with multiple predictors. I checked each model's fit with the le Cessie – van Houwelingen – Copas ...
2
votes
1answer
23 views

How to isolate impact of event in a product's lifecycle?

I'm trying to figure out how a single event affects sales numbers of a song. For example, see what the effect of being featured in iTunes store compared to songs with comparable previous download ...
0
votes
1answer
39 views

Binary logistic regression with interaction terms

I have been reading several CV posts on binary logistic regression but I am still confused for my current situation. I am attempting to fit a binary logistic regression to a series of continuous and ...
0
votes
0answers
8 views

Different sufficiency condition for Goods and bads

I am building an underwriting model for a bank with the following construct Development Sample Window - Accounts opened before Jun'13 (i.e. have completed atleast 12 months as of Jun'14) Bad ...
0
votes
0answers
20 views

Does it work better to subtract mean of data in logistic regression?

I am using logistic regression to predict $X \rightarrow Y \in \{0, 1\}$ based on the featurization $\phi(X)$. The training objective function is \begin{equation} \mathcal{L} = ...
1
vote
0answers
13 views

Case-crossover method with conditional logistic regression for poisson model generated data

I would like to run a semi-symmetric bi-directional case-crossover method on some generated data using conditional logistic regression. I generated data from Poisson distribution Poiss(lambda) with ...
1
vote
1answer
45 views

Categorical variable as response in poisson regression

I have data on damages on flowers from different treatments. The damage was originally count data (number of damages per flower) but the person collecting the data categorized the data in four levels ...
1
vote
0answers
14 views

Logistic Regression and Design of experiment

I have seven factor and one response variable with 32 run and one replication i.e. 64 runs and I want to use logistics regression. I found in th analysis that 4 out 7 factors are significant. I want ...
0
votes
1answer
23 views

mixing binary and real-valued features with SGD

I'm going to be using a logistic regression model and using SGD to determine the feature weights. Is it OK for me to use a mix of binary and real features, without doing anything like scaling or ...
2
votes
2answers
79 views

model for continuous dependent variable bounded between 0 and 1

I'm attempting a multiple regression model where the predicted variable is runoff ratio - the ratio of watershed discharge to the precipitation input. This should generally be bounded [0,1], however, ...
1
vote
0answers
34 views

Logistic regression: Trying to use mean logit as reference group

Question I would like to do a logistic regression where the independent variables are compared to the mean logit, rather than the logit being compared a certain reference group. Example The example ...
9
votes
2answers
613 views

What does the name “Logistic Regression” mean?

I am checking an implementation of Logistic Regression from here. After I reading that article, it seems the important part is the find the best coefficients to determine the sigmoid function. So I ...
0
votes
0answers
21 views

semisupervised classification training on all or part of unlabeled data

I have 3 sets of data. A positively labeled dataset. An unlabeled dataset that has for sure positive (around 75%) and negative data. An unlabeled dataset that has for sure positive data and maybe ...
1
vote
1answer
31 views

How do you interpret the parameters obtained from lasso logistic regression when the response is binary?

Are we still able to interpret the parameters in the same manner as we would in ordinary logistic regression? I'm asking this because I'm toying with the german credit data ...
0
votes
0answers
9 views

Values in predictors have same pattern for two possible value in dependent variable?

I am trying to build a model for auto rejection of crowd-sourced task (eg: human name transcription of census data). My data set has 5 predictors, and dependent variable is either correct or ...
1
vote
0answers
33 views

Logistic Regression: should I worry about coefficient correlation matrix?

With SPSS (v18), in the output of a logistic regression after the "Variables in the Equation" section, there is a Correlation Matrix which represents the correlation of the coefficients. What do ...
0
votes
0answers
12 views

Logistics Regression Stoped at Step 0 with SAS Enterprise Miner

I use some insurance quote data with demographic data as variables and the target is binary (0,1). The total observations is around 50,000 and the variables are around 60. The demographic data is ...
1
vote
0answers
42 views

Multicollinearity in a “population model”

I was talking with a colleague who told me that at the time of making logistic regression across a population did not have to worry about assumptions such as multicollinearity, because when analyzing ...
0
votes
0answers
63 views

Binary Logistic Regression Methods

I have data sample size of almost 15,000 cases. The dependent variable is a dichotomous variable stating whether the patient has the disease or not, Yes=1, and No=0. I have 12 more independent ...
1
vote
0answers
11 views

Motivating likelihood ratio test vs Wald test for paper reviewer

I've got back reviews for a paper I've submitted, with the following problem. I have two logistic regression models, say y ~ A, and y ~ A + B, where B is a factor with several levels. I have ...
0
votes
0answers
15 views

logistic regression with related predictor variables

I have two simulations for physical ability testing that add up to a total test score, coded as dichotomous pass or fail 0, 1. Can I treat the two simulations continuous times as independent ...
2
votes
0answers
25 views

Ordinal logistic model in R

I have the neuropsychiatric questionnaire scores of 300 individuals, of which 200 are normal, and 100 have the disease. The questionnaire is divided into 12 categories (delusion, agitation, ... etc). ...
0
votes
0answers
16 views

Dummy variables in logistic regression vs. svms

Suppose $y$ is a binary outcome variable and $x$ is a categorical predictor variable that takes three levels (1,2,3). In this case, you would create two dummy variables $x_2, x_3$. So $x_2=1$ if $x=2$ ...
1
vote
1answer
47 views

Standardized beta for logistic regressionin R

For my survey data analysis, I ran an Ordinal Logistic regression using the 'polr' function. The summary of the regression is as follows: My question is: Do I need to standardize my beta values? ...
0
votes
0answers
50 views

Is this a case for an ordinal logistic regression? Problems interpreting output

I'm a beginner in statistics and R, sorry if this question may seem trivial. I've collected data measuring several different parameters in 40 subjects at two time-points (t1 and t2). There are 3 main ...
0
votes
0answers
23 views

logistic regression using probabilities of class labels

My goal is to train a logistic classifier. My samples in my dataset have some label noise but for each label I can give a probability how correct this label is. What is the best way to incorporate ...
2
votes
0answers
45 views

Name for the Bayesian posterior probability that a regression coefficient is larger than zero

I have the following logistic regression: $$ \text{logit} (y) = \beta_0 + \beta_1\, x $$ from which I can estimate the following posterior probability (using a Bayesian approach): $$ ...
1
vote
1answer
29 views

Concordance vs. Sensitivity

I am confused between these two terms: sensitivity and concordance. What I understand about these two terms: Concordance: the number of pairs where actual 1s have higher predicted probability of ...