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

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How do I translate logistic regression output into logged OR (and SE) for meta-analysis?

I'm attempting to conduct a meta-analysis using (logged) odds ratios, I'm using the Generic Inverse variance method (Review Manager) as some of my studies only report odds ratios and CIs (not raw ...
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14 views

Weight of Evidence(WoE)/Information Value(IV) in R [on hold]

I am building a credit scoring model in R. I have to run logistic regression. But my number of variables is too high, about 3000. I have both continuous and factor variables. And number of observation ...
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36 views

How to Calculate π In R [on hold]

This GLM From My Data How To Calculate π With R. I Need R Code.
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Checking the proportional odds assumption holds in an ordinal logistic regression using polr function

I have used the ‘polr’ function in the MASS package to run an ordinal logistic regression for an ordinal categorical response variable with 15 continuous explanatory variables. I have used the code ...
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8 views

Softmax maximum likelihood problem: arbitrary constant

I'm doing a multiclassification with a softmax function. The probability of a sample $j$ belonging to class $k$ is given by the softmax: ...
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29 views

High leverage Points In Logistic Regression in R

Do You Know Any Good R Package For This Model?
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26 views

Handling Sparse Data Frames - algorithm selection

I am new to machine learning/statistical modelling. I am trying to run a classification on a highly sparse dataset with 100 features, most of which are categorical (TRUE/FALSE) with the remaining ...
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8 views

Binary Logiistc regression and covariates in SPSS

When running binary logistic regression, where there is an dependent variable, multiple independent variable and covariates, where do I put the covariates in SPSS? Would they go in the covariate box ...
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21 views

Which logistic model should I use in Stata when I have a mix of categorical and scalar variables?

I want to run a regression in Stata. The dependent variable is a scalar categorical variable indicating life satisfaction ls (1= satisfied, 2= intermediate, 3= ...
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12 views

R: Error with mlogit Conjoint modelling - system singularity

I am building choice models on a dates about coffee preferences. I have 5 alternatives: Brand, Cup, Price, Certification and Local Community Support. The data looks like this: ...
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19 views

Logistic regression model [duplicate]

Does one always have to standardize all coefficients in logistic regression models? Also does matlab automatically standardize coefficients or does this have to be done by the user? Thanks for any ...
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R- Cost function in glm

I need to introduce a cost function in a logistic model (I'm using R). As I saw from this question, we can introduce costs in cv.glm. But I don't know how to introduce it in glm. My cost function ...
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44 views

Investigating interaction

Please I need to check for interaction before building an explanatory model (logistic regression). I have 16 interaction terms in total. Please how what is the best way to go about it. Will I need to ...
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184 views

Logistic Regression - Error Term and its Distribution

On whether an error term exists in logistic regression (and its assumed distribution), I have read in various places that: no error term exists the error term has a binomial distribution (in ...
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29 views

Adding weights to data points in logistic regression

I am trying to run a logistic regression on a data sample where the unique identifier is "project". I also have the date on which each project was created. Some projects are more recent than others ...
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39 views

Is it possible to have a case where $D'$ is zero but Logistic Regression is still able to classify accurately?

I want to know if it is possible to construct a problem with following properties: $M_1$ is $n \times p$ matrix of $n$ observations from Class A $M_2$ is $n \times p$ matrix of $n$ observations from ...
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9 views

interpreting the clogit output in R

Maybe this is obvious but I've never done a conditional logistic regression before. In the clogit output after the Rquared value there is a max possible value. I assume this is max possible Rsquared, ...
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31 views

Bootstrapping with bootstrap sample greater than original sample

My original sample has 350 observations drawn randomly from a population of 60,000 people. My independent variable is Default, with 35 observations with value of ...
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29 views

Are insignificant variables included in calculation of predicted probabilities?

When calculating the predicted probabilities in a logistic regression model, do we consider all the variables or just the significant ones? For eg: Let's say my model has: dependent variable Y and 3 ...
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39 views

Testing Logistic Regression Classifier in R

I am testing the logistic regression classifier in R. I created some test data like this: x=runif(10000) y=runif(10000) df=data.frame(x,y,as.factor(x-y>0)) ...
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41 views

Analysis where dependent variables are proportions

I have a set of demographic data (age, race, social class, etc.) for selected geographic areas. These independent variables are each proportional in each type, i.e. Area A: White 70%, Black 20%, Asian ...
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how do i differentiate between alternative specific and alternative invariants using sas?

Okay so my level of expertise in statistics is fresher/rookie. I am trying to predict the the outcome of categorical choices for a product category y (3 choices or 3 flavors of cereal for example). ...
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69 views

Logistic Regression Assumptions

I am preparing a presentation on logistic regression. I applied logit model to a data set and now want to check whether my model meets logistic regression assumptions. I don't exactly know how to do ...
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35 views

How to choose the best logit model using step function in R

I have the data below. I was wondering how I could choose the best model fit of logit model using step function in R. Here is the data in R format: ...
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34 views

Missing data not at random - Advice needed on method

I have been developing a logistic regression model based on retrospective data from a national trauma database of head injury in the UK. The key outcome is 30 day mortality (denoted as "Survive" ...
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21 views

Interaction with contrast and dummy coding

I have a question regarding the interpretation of an interaction using categorical variables where one is dummy coded (0, 1) and the other is contrast coded. The variables are: Var1: 3 levels, ...
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21 views

Alternative specific conditional logitstic regression with clustering on in individual in panel data: scientifically and computationally reasonable?

My scientific interest is to calculate the price elasticity for an overall set of products (books) in a panel dataset of observations over a 3 year period and I was wondering whether asclogit ...
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30 views

Rank deficient bootstrap resamples

Despite years of stat courses I'm afraid I may still not completely understand bootstrapping. My question here relates to nonparametric boostrapping of regression models. As i understand it you draw ...
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62 views

R - glmnet - Not all features being considered

I have just started working with the glmnet package in R. I have s a dataset which has about 130,000 features and about 100 rows of data (actually there are about ...
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25 views

logistic regression with sparse predictor variables

I am currently modeling some data using a binary logistic regression. The dependent variable has a good number of positive cases and negative cases - it is not sparse. I also have a large training set ...
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23 views

cost matrix, unbalanced class, oversampling and threshold probability

Let's suppose I have a cost matrix with TP=+90 FP=-10 TN=0 and FN=-10, and that the class is unbalanced. I need to capture the costs in my decision. To do so, I always consider the probability ...
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58 views

Is there evidence of mediation? Need help with interpretation of mediation analysis results

I have performed a mediation analysis. I have an independent variable T, a mediator M, and outcome Y. (All 3 variables are binary, and I use logit.) (While I used Stata ...
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Extracting cofidence interval vaules from a Logistic Regression

I have a logistic regression model in which I am predicting the size at which a crab has a 50% chance of being mature (probability=0.5) and I've built confidence intervals for the whole model, ...
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21 views

Likert scale and binary logistic model

If independent variables are measured in 5-point Likert scale and dependent variable is dummy, then can I apply logistic regression model here? How independent variables are put in SPSS?
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62 views

Cox Models treatments depending on time until event

I'm trying to get the "productivity" of treatments like sending an email, calling or sending an SMS and their combinations in the paying debtor's probability. I couldn't find one model that satisfies ...
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39 views

variable error on logistic regression/ proc catmod- Building predictive model

I am using logistic regression to fit a model with categorical/multinomial varaibles. data-description: There are over 300 variables as independent variables, sample size is 5000 which is divided into ...
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31 views

Log transformation in logistic regression

I have a model with a natural log transformed variable in a logistic regression and I'm looking for some help in interpreting the odds ratio. The odds ratio is 1.78 (coefficient 0.58). I know there ...
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Probability of Event in Logistic Regression

I've a binary response (1 = event happen, 0 = otherwise) and 8 continuous predictors plus 1 categorical. Fitting in Minitab with a Binary Logistic Regression give me this output: ...
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Sample size for logistic regression with categorical independent variables

Trying to find a sample size for logistic regression I found a rule of thumb in http://www.medcalc.org/manual/logistic_regression.php I cite: Sample size considerations. Sample size calculation for ...
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28 views

Are LASSO regression predicted values also biased?

Since LASSO regression biases coefficients to reduce variance, aren't the predicted values also biased? In my case I am looking at fitted values from a predictive logistic regression model with LASSO ...
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How to best to use Continuous value features with discreet values for logistic regression based binary classification problem

This is related to Minimisation algorithm for a mix of discreet and continuous parameters? I am trying out logistic regression to solve a binary classification problem. Though I am feature-scaling ...
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Closed form for the variance of a sum of two estimates in logistic regression?

In logistic regression with an intercept term and with at least one dependent variable which is categorical, is there a closed form for the variance of the sum of the intercept and the coefficient of ...
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How can I group different levels of classes of a categorical variable in logistic regression?

Suppose I have a categorical variable neighborhood, which can take the classes Neighborhood1, Neighborhood2, Neighborhood3. I would like to know which neighborhoods can be grouped and what ...
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34 views

Relation between the tuning parameter $\lambda$, parameter estimates $\beta_i$ and constraint $s$ in LASSO logistic regression

In the context of LASSO logistic regression, I understand that $\lambda$ is the tuning parameter obtained by cross validation. There is also the constraint parameter $s$ ($\sum_{i=1}^p|\hat\beta_i|\le ...
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26 views

Expressing beta estimate in terms of odds ratio for a continuous variable

I am making a table from results of an analysis using generalised linear model which involves detecting association of a categorical predictor variable over multiple outcome variables. Of those ...
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39 views

Algorithm does not converge in R

I am doing a logistic regression in R, where I am modeling how potholes and weather correlate to accidents. When I run a logistic regression, I get the message "Algorithm does not converge" The ...
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Looking for a layman's explanation of how to manually calculate log odds?

I will start that I am not as math oriented as I would like to and could use a layman's / non-staticians explanation walk through of how to calculate the log odds. I am reading Hosmer, Lemeshow, and ...
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Back transforming a constant for geometric mean

I have a series of non-normal variables that include negative values. I have transformed the data by adding a constant of +10 to each variable (the lowest value was close to -9) and then log ...
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61 views

How to know which feature mainly led to the prediction?

I have a classification problem where I use a model (say Logistic regression or SVM) to determine whether an instance belongs to class 0 or class 1. For a certain prediction on a test instance X, if ...
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30 views

What is the variance of a Polya Gamma distribution?

I have a simple application that needs the variance of a Polya Gamma distribution (I know the mean since I found it here- http://arxiv.org/abs/1205.0310). This paper says that there is a closed form ...