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

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Omitted variable bias in logistic regression vs. omitted variable bias in ordinary least squares regression

I have a question about omitted variable bias in logistic and linear regression. Say I omit some variables from a linear regression model. Pretend that those omitted variables are uncorrelated with ...
3
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34 views

Propensity score matching: using alternative methods to create a distance measure

I would like to use a greedy nearest neighbour method to do propensity score matching. Though I've little experience here, it seems that the distance measure used is generally a propensity score ...
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15 views

Logistic Regression with different priors

I am using standard logistic regression for classification with reasonable results. As expected I get a probability of 0.5 for query points "far away" from the data. However I would like to assign ...
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11 views

Bootstrapping in SAS - PROC LOGISTIC - Next steps ? how to score / perform diagnostics?

My question is as follows. I am referencing the following paper by David Cassell - wherein David talks about bootstrapping techniques in SAS using PROC SURVEYSELECT (many thanks to David - truly a ...
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14 views

Having additional data for only a subset [on hold]

Due to having a maximum amount of data i can request, I can only request additional data for only a targeted group that I am interested in. This data should help my model accuracy for the targeted ...
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7 views

accessing learned coefficeints (coef_) of logistic regression in sklearn

I am wondering about how to interpret the coef_ variable in the logistic regression class of sklearn. Given a dataset with m features and n categories, coef_ seems to be a matrix with the size of ...
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45 views

Correlation using Logistic Regression and Pearson

I am so sorry, I am beginner in statistic analysis, I have project using R to analyze the correlation between dependent variables and independents variables. In this case I have two dependent ...
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1answer
38 views

Normalized likelihoods

AIC (BIC) model selection methods are widely used. These methods can select non-nested models unlike likelihood ratio type selection that requires model to be nested. The AIC has definition ...
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2answers
83 views

Sine link with binary regression

I have used the SIN link to estimate probabilities, mostly with Program MARK. However, I am not sure how the SIN link works. I know the SIN link enables parameter ...
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37 views

Propensity to purchase using regression analysis in R [closed]

I have a dataset with a sample snapshot of it looking like this: ...
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10 views

Single Categorical DV (3 levels), and Single Continuous Repeated Measure IV: which test?

I'm a Ph.D. psych student and am having trouble finding information on which test to use for a continuous repeated measures IV and categorical DV. I would really appreciate some help with this. The ...
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23 views

In plain language, why is there no VIF for binary outcome regression models?

As far as I know, the variance inflation factor is not computed with pseudo-$R^{2}$ or generalized $R^{2}$ in binary outcome models (e.g. logistic regression). Are there other measures of ...
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18 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 ...
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36 views

logistic regression with dummy variables for fractional factorial design

We have conducted a survey experiment with varying amounts of incentive (factor 1 = I1, I2, I3, I4, I5). The experiment was conducted stepwise in three subsequent studies (factor 2 = S1, S2, S3). ...
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40 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 ...
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0answers
11 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 ...
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16 views

geepack: parameter estimates change sign depending on correlation structure

I'm working on a dataset with the following variables: ...
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1answer
27 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 ...
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27 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 ...
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1answer
23 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 ...
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103 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 ...
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30 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. ...
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24 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 ...
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23 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: ...
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48 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
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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 ...
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4answers
81 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 ...
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55 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, ...
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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. ...
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24 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). ...
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54 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 ...
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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 ...
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78 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 ...
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20 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 ...
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1answer
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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 ...
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43 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 ...
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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 ...
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23 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} = ...
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15 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 ...
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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 ...
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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
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1answer
25 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
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2answers
93 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, ...
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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 ...
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624 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 ...
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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 ...
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1answer
39 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 ...
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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 ...
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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 ...