# Tagged Questions

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

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### Modeling strategy to produce predicted probabilities for different aggregations

I have a large amount of data (millions of observations) and am trying to produce a predicted probability of a discrete action based on a number of covariates. So far, this is a classic classification ...
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### Use of logit simulation for impact assessment or establishing causality

My question is that for establishing causality, omitted variable bias is important in regression specification. When relevant variables are omitted, the intervention effect or variable under ...
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### Logistic Regression on very rare events - R

I am trying to run a logistic regression analysis in R using the speedglm package. The data is CNVs (a type of genetic variant), whether that CNV occurred in a case or control and wether genes in a ...
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### Model selection using a standard p-value approach

I need to perform model selection using a standard p-value approach. Using logistic regression we would like to compare the following models: ...
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### Hessian of logistic function

I have difficulty to derive the Hessian of the objective function, $l(\theta)$, in logistic regression where $l(\theta)$ is:  l(\theta)=\sum_{i=1}^{m} \left[y_{i} \log(h_\theta(x_{i})) + (1- y_{i}) ...
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### Exploratory Factor Analysis for Binary Logistic Regression Variable Selection

I have a great interest in learning new methods(at least to me) of variable selection in regards to binary logistic regression when I am working with over 500 potential predictor variables and have ...
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### Given an interaction how to find the region of var1 at which var2 has significant effect on response Y?

I have run a binomial glm in R using proportional data in the form y <- cbind. I have two continuous explanatory variables, ...
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### Can explanatory variables be non-Gaussian?

I am conducting a logistic regression. However, the Shapiro-Wilk test has determined that one of the X variables is non-Gaussian. Do the explanatory (X) variables need to be Gaussian? If so what are ...
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### Can I test a proportion (k success out of n) against an expected probability obtained from a logistic GLM?

I have a logistic regression model which is obtained from literature about the probability of developing a toxicity ($y_{i}=1$ or $0$) when patients are given dose $X_{i}$. $X_{i}$ is a continuous ...
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### Is it good to use a logistic reg if I combine many factors into p and many other into 1-p?

I have a large survey sample. I have a question like "What is your level of satisfaction with ...". It should be my outcome variable. Each respondent can give a unique answer of one of this ...
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### Using Mutual Information for Binary Logistic Regression Variable Selection

In addition to proc varclus, randomForest, and assessing multicollinearity among potential predictor variables, I am seeking ...
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### missing data in levels of categorical variable in logistic regression

I am running a logistic regression model and I have run into an issue that I need clarification on. my model is as follows: levels Bleed 0 1 INF0 86 11 SUP0 104 ...
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### How to conduct a multilevel (hierarchical) binary logistic regression (in SPSS, R, or other software)?

I have a model with occurrence of a disease represented by a binary dependent variable (DV) and 8 independent variables (IVs) at different levels. I need to create a multi-level model, in which the ...
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### Caveats with logistic regression for an expected utility computation?

Suppose we are modeling the probability of heads on a biased coin. We use observable features, for example, its shape and color. We train a logistic regression classifier on a bunch of known coins ...
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### How to interpret regression intercept with one dummy coded categorical predictor?

This is nearly the same headline as my previous question, but it turned out I was asking about multiple issues. I still have not understood the more basic issues, which have to do with the ...
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### Machine Learning System Design: a practical advice

Recently, I stared working on a machine learning competition hosted on Kagge.com. As the first step, a quick and dirty system was developed using Logistic Regression (LR). After running the system ...
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### Does down-sampling change logistic regression coefficients?

If I have a dataset with a very rare positive class, and I down-sample the negative class, then perform a logistic regression, do I need to adjust the regression coefficients to reflect the fact that ...
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### Inference for between group differences (with non-linear time component, outliers and mixed effects)

TLDR: How can I perform inference for the between group differences in a possibly logistic growth with time in the presence of outliers, unequal measurement times and frequency, bounded measurements ...
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### Alternatives to stepwise logistic regression with LARGE datasets

After reviewing related questions on Cross Validated and countless articles and discussions regarding the inappropriate use of stepwise regression for variable selection, I am still unable to find the ...
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### Is logistic regression still valid where there are repeated measurements and generalized estimating equations is the real deal?

I have a model with a binary dependent variable (DV) and 5 independent variables, all of which are matched (each person, twice). I think since these matched INDEPENDENT variables can be considered ...
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### Interpretation of logistic regression intercept with one dummy coded categorical variable

Feel free to critique my overall approach instead of answering my question directly. I want to look at bivariate relationships among a binary outcome and multiple predictor variables before ...
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### Two different methods…different results?

I have a response variable and 10 predictor variables (all ordinal). I wanted to see if there was any evidence of a relationship between the response and predictors. I used a two proportion z-test to ...
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### Is there an R package that implement the proportional odds assumpion?

is there an R package/function to implement the parallel slope test given a clm (ordinal package) or polr (MASS) package?
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### Building Accurate Model & Resampling

There is a model built using logistic regression. The data has a lot of variance. Can the accuracy of the model be improved by either of the following? 1)Resample the training data dozens of times, ...
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### Is the logistic regression model integrable into the potential outcome framework?

(1) I preprocessed data with a matching method (CEM) (2) On this data (binary dependent variable, explanatory variables) , I ran a logit model and estimate predicted probabilities or odds ratios. I ...
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### Pre-post Logistic regression

A friend of mine approached me to help her to interpret her multinomial logistic regression model. They had measured people as 1 of 2 states at 2 time periods. So, each person can have 1 of 4 ...
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### Should weights of neural network without hidden layer match logistic regression?

Should the weights of a neural network without hidden layer and a logistic activation function be the same as the parameters of a logistic regression? Mine are not the same? ...
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### Confidence interval for predicted probabilities

I fitted the following multinomial regression: ...
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### Pooled logistic regression with irregular intervals

I'm planning an analysis that will require pooled logistic regression to analyze a longitudinal dataset with time-dependent explanatory variables (see here - D'Agostino, et al. 1990). However, the ...
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### Aggregating predicted probabilities from a classifier

I have an existing logistic regression used to forecast whether a given action will take place or not. The unit of analysis is the individual person. For the sake of the question, assume a default ...
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### Downsampling proportions for logistic regression

I am working on a model based on logistic regression with a binary response variable and my data consists of ratios of integers (number of positive observations out of the total number of ...
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### Multinomial logistic analysis

I am estimating a logistic model for a binary $Y$ (0=controls, 1=cases), and a set of covariates ($x_1, x_2, x_3, \ldots$) including sex (male, female). I know from the data that risk of $y$ is quite ...
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### Binary logistic regression on SPSS 20 - output seems inconsistent and illogical

I have one categorical dichotomous dependent variable (yes/no - retention of newly learned words) and two independent variables - both are categorical. One independent variable is "delay between ...
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### Assigning values to missing data for use in binary logistic regression in SAS

Many of the variables in the data I use on a daily basis have blank fields, some of which, have meaning (ex. A blank response for a variable dealing with the ratio of satisfactory accounts to toal ...
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### Is binary logistic regression the right choice?

Apologies for the rudimentary question. I'm taking on a project at work that's a bit out of my wheelhouse and I want to bounce my ideas off of those more experienced than myself. We use ...
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### Logistic regression - cutoff

If you are running logistic regression on data, and the prior probability of the event is 50%, and there is no preference for sensitivity or specificity... When would you still want to use a cutoff? ...
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### Logistic regression diagnostics when predictors all have skewed distributions

I'm fitting a logistic regression model Y ~ X1...X10 to 10,000 observations, where my goal is estimate the effect of each covariate on Y. My first issue is deciding what transformations to apply to ...
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### Growth models for a population

I'm studying the growth of a population (users of a website). I have the user count for each time block (which is 2 weeks long). Now, I'd like to understand if this growth follows a well-known growth ...
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### How are the standard errors computed for the fitted values from a logistic regression?

When you predict a fitted value from a logistic regression model, how are standard errors computed? I mean for the fitted values, not for the coefficients (which involves Fishers information matrix). ...
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### Prediction of a binary variable

I am establishing a model for prediction of a binary variable (Yes/No) depending on three continuous variables ($A$,$B$,$C$). I applied logistic regression analysis for a learning dataset vith the ...
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### Why does my ROC curve look like this (is it correct?)

I have a ROC curve generated for a multivariate logistic regression. Does it look correct? This is what I've done: Solve $\theta_0 + \theta_1X_1 + \theta_2X_2 ... = Y$ for the $\theta$s Iterate ...
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### Maximum Entropy and Multinomial Logistic Function

I have a newbie question. I tried to find the answer from Google but couldn't get a clear answer. Is the MaxEnt model exactly same as multinomial logistic regression (i.e., softmax regression)? It ...
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### Do I need a balanced sample (50% yes, 50% no) to run logistic regression?

I'm working on a project using logistic regression to predict student retention. The data were collected through three self-report instruments. We are trying to find out which predictors are powerful ...
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### Ordinal logistic regression to find support for inverse proportionality of a continuous predictor on an ordinal dependent variable

I want find statistical support that dependence is inversely proportional to power. To do so, I have ~260 cases, with four questions about dependence, and one question about power The questions ...
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### Validating logistic regression - formulas needed for simulation

This is related to a data classification problem having a Boolean output variable. Summary: Once I perform the ML task using Logistic regression, I get the required coefficients. I use the ...
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### Binary Logistic Regression in SPSS

I have a response (customer satisfaction) and 10 predictor variables that may/may not have an affect on response. My variables are ordinal, where 0 means "not satisfied" and 1 "satisfied". I used ...
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### P value for logistic regression in octave or python

I m using logistic regression and I am trying to figure out if there is anyway to compute the p-values either in Octave or in Python. thanks
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### When to take logarithms of a variable such as the Herfindahl Index?

Currently I am skimming through a couple of papers in well established journals! I became curious when I found papers with linear regression models using the Herfindahl index as the dependent ...