Tagged Questions

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

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5
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3answers
142 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 ...
0
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0answers
23 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 ...
5
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1answer
35 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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0answers
25 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 ...
0
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1answer
22 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 ...
1
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1answer
34 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)) ...
0
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1answer
37 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 ...
0
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0answers
6 views

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). ...
1
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1answer
62 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 ...
0
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1answer
33 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: ...
2
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0answers
33 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" ...
0
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0answers
16 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, ...
1
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0answers
20 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 ...
4
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0answers
19 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 ...
0
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0answers
10 views

Logistic regression using sklearn [on hold]

I am using sklearn to implement logistic regression. this is code I have written till now ...
1
vote
1answer
59 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 ...
1
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0answers
23 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 ...
0
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0answers
20 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 ...
0
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0answers
51 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 ...
0
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0answers
16 views

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, ...
0
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1answer
19 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?
4
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3answers
60 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 ...
0
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0answers
34 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 ...
0
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1answer
29 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 ...
0
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1answer
38 views

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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0answers
26 views

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 ...
0
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0answers
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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0answers
31 views

Kaggle competition question [closed]

I am fairly new to data analytics. I wanted to learn through practising more on the problems posted on Kaggle. This is the topic i am looking at ...
1
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2answers
42 views

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 ...
2
votes
1answer
48 views

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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0answers
16 views

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 ...
1
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1answer
33 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 ...
0
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1answer
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 ...
4
votes
1answer
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 ...
3
votes
1answer
47 views

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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0answers
11 views

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 ...
0
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1answer
60 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 ...
2
votes
1answer
24 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 ...
0
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0answers
14 views

Fitting a logistic regression model with continuous variables without a constant mean

I'm trying to incorporate a continuous variable to a logistic regression with regularization model I've already tested with only binary variables. I know that, if I'm using regularization, I must ...
0
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1answer
28 views

Predict rare happen event using logistic model? [duplicate]

The response variable is binary (dead="1" or not="0"),and there are 4 numeric independent variables. I tried logistic regression and 2 of independent variables are significant. However, the prediction ...
0
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1answer
52 views

Variable Selection for Logistic regression

I am performing logistic regression. I understand assumptions of logistic regression - Outliers, Multicollinearity. What i didn't understand how to select variables at beginning of model preparation. ...
1
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1answer
64 views

How to implement ordinal logistic regression for a factorial design

I have read a few answers (e.g. this, this and this) recommending to use the Ordinal Logistic Regression (OLR) as a generalized method when the Kruskal-Wallis is not suitable. For instance, a 2x2 ...
0
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0answers
16 views

using SAS for decision tree

I am quite new to SAS. I wanted to figure out how we can use Test dataset and Train dataset seperately. As of now i was dividing the existing dataset into Training and Test dataset. My requirement is ...
0
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0answers
33 views

Maximum Likelihood for online decision making

Sorry, this might be a trivial question but I have to ask to be sure. I have a logistic regression model that does a good job of predicting churn. This has been cross validated, etc. Now, imagine ...
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0answers
11 views

Equally spaced ordinal outcome in regression

If in a multiple regression model I have an ordinal dependent variable I have to use ordinal logistic regression. In particular, I have to do that if the distance between ordinal output is not equally ...
0
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0answers
24 views

Do we need to correct p-values when using multiple models?

I am currently studying epidemiology. I am writing a paper that is examining 11 disease states in one species. I am using binomial logistic regression to examine 2 possible predictors (age and ...
0
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0answers
33 views

logistic regression fitted values do not vary, how to interpret?

Im running a logistic model using binary dependent and independent variables. The fitted values from my model are acting categorically so i do not know how to interpret sensitivity/specificity or ROC ...
0
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2answers
40 views

How to modify variables to be significant in logistic regression?

I am running a logistic regression analysis in a particular software. My objective is to study the behavior of the software with significant variables. However, with the data I have, there are no ...
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2answers
124 views

Is it fine to get this results in binary logistic regression?

I wanted to check whether the level of satisfaction relates to the level of support to the value of democracy. Dependent variable (support) is binary variable (Good/Bad) and independent variable is ...
-1
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1answer
28 views

backward selection but regression coefficients not significative? [closed]

I'm running a logistic regression with backard selection method. I get coefficients with p-values>.10. Here's an example: ...