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

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How to test main effects of categorical variables in a binary logistic regression including an interaction?

I measure two binary responses from each participant (ChoiceVA = V or A, AestheticOnly = 0 or 1). There are two experiments (between-participant). I want to test the following hypotheses: ...
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Logistic regression: Is it legitimate to exclude a main effect (part of interaction term) when predicting new values? [duplicate]

I have two main effects and an interaction term. The interaction (IsolateTemperature) term and one of the main effects (Isolate) is significant. The other main effect (Temperature) is not. I want to ...
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11 views

Logistic-Regression: Prior correction at test time

Using sklean.linear_model.LogisticRegression for a binary classification problem. My classes are unbalanced. The positive class comprises about 20% of the training set. When fitting the model I use: ...
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Multilevel analysis. Between hospitals variance

Please help me with the multilevel analysis. Certain medical procedure is performed/not performed in hospitalized patients. The % of patients that receive this procedure varies across different ...
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How to define my custom cost function to be used in (stochastic) gradient descent?

I have a text classification problem were the classes are 20 cities and the input is text Bag of word features. I am using Logistic Regression and my cost function is negative log likelihood: ...
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How to estimate a Logistic Regression function in a quadratic form?

I am trying to use a mixed-integer programming solver to optimize the following logistic regression function: $$\mathop {\min }\limits_w {{\exp ({w^T}x + b)} \over {1 + \exp ({w^T}x + b)}}$$ There ...
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Using ordered factor as predictor in R [duplicate]

This is a really simple problem I am having, yet for the life of me I can't find a solution searching around. In theory I can simply recode the data, but that is an extreme solution I would rather not ...
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Multivariate Multiple Logistic Regression in R

I have several dependent and independent variables. All my dependent variables are binary, therefore, I want to perform a multivariate multiple logistic regression, is that possible to do in R?
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Logistic regression gives very different result to Fisher's exact test - why?

I have a confusing situation where I have strongly conflicting results from two ways of analyzing my simple data. I measure two binary variables from each participant, AestheticOnly and ChoiceVA. I ...
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confidence interval for aggregated expectation from logistic regression

My model steps: 1.I fitted a logistic regression model $Y\sim X$; 2.then get the probability $P(Y=1)$ for each record; 3.then I summed the probability $R = \sum_i(P_i(Y=1))$ to be the expected return, ...
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Time imputation from interval censored-data for logistic regression

I have 200 individuals with a time $T_i$ (unknown) of infection that is included in the interval $[L_i,U_i]$ (data known) different for each individual. I suppose that Ti follows a lognormal ...
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Is it possible to get a covariance matrix of fitted values for a GLM model in R?

I would like to get a covariance matrix of fitted probabilities for a logistic regression model in R. I would like to do this because I want to find the variance of the difference between the two ...
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Interpretation of sigmoid function in logistic regression

I am having a very difficult time trying to interpret the probabilities that a sigmoid function yields. I'm asking this from a machine learning perspective. I'll lay everything out and explain exactly ...
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Probabilistic interpretation from sigmoid functions

Why do we interpret the results of logistic regression as probabilities? Passing the output of any regression procedure through a sigmoid function results in a probabilistic interpretation with ...
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how is the logistic regression scatter plot created

I have a newbie question about logistic regression fit plots. I'm fitting a very simple binary output based on a simple continuous input ...
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Coefficient changes sign when adding a variable in logistic regression

In my logistic regression the sign of coefficients of a variable (location distance of an amenity) changes based on other variables (with time -ve, with travel distance +ve) in the model. When the ...
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How to calculate multicollinearity of binary variable with other predictors in regression model?

VIF can be used to calculate multicollinearity of continuous variable in regression models. But VIF will only work for continuous variables because this is calculated by running a linear regression ...
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Dichotomizing Continuous Variables in Regression: Good or Bad?

I believe Dichotomizing(also called bucketing/binning) of continuous variable is not always a good idea. My colleague while building regression model always bins continuous variables and only keep ...
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How to deal with underdispersion with binomial data

I'm working with a pretty large dataset (n = 4,500) where 10% of my points (pixels in a GIS landscape) are 1s and the rest are 0s. The full model for my data looks something like this: ...
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Interpretation of odds in logistic regression

I have been reading the odds tutorial on UCLA's stats page. And I am trying to figure out if my interpretation of the results below is correct. Based upon looking at the data the results seem to hold ...
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Comparing Odds ratios between dependant samples?

I am in a bit of quandary with a research project: I have to compare and contrast the epidemiological picture of homicide with the media coverage of homicide in a specific geographic area and ...
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69 views

Generate random data for logistic regression with a categorical independent variable

I am trying to generate a data frame of fake data for exploratory purposes. Specifically, I am trying to produce data with a binary dependent variable (say, failure/success), and a categorical ...
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69 views

Questions regarding Binary Logistic Regression

I am very new to statistics and is currently performing binary logistic regression analysis to test null hypothesis for my dissertation. First, both my independent variables and dependent variable ...
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Random variables of mixed models

I am thinking about using mixed models as part of my research, but I am having trouble understanding its application. In particular, I have two somewhat related questions regarding mixed models. ...
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Complete Logistic Regression framework using K-Cross validation

I'm implementing a logistic regression model in a low event rate data. I have gone through many webpages (including stackoverflow, including my questions) but none answer or describe the end-to-end ...
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Significance of a dichotomized variable from a continuous variable

I am analyzing a X continuous independent variable with a Y binary response. The investigator has interested on dichotomize the X variable by the “best” cutpoint from the ROC curve (for example the ...
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68 views

Logistic Regression Odds Interpret

I was analyzing the different treatments applied to products. It started out with a a plethora of variables but I came to the conclusion that I can essentially only control the treatment applied so I ...
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what does it mean when out of sample AUC is greater than in sample AUC?

I am fitting a logistic regression model on a data set with about 200,000 observation and 100 features. According to SAS output, the model converged correctly with an in-sample AUC of 0.85. However, ...
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Use fitted value from regression on subset of features as independent variable

I am working with a relatively large data set with 2K columns and many variables can be grouped together (a logistic regression). So I am thinking can I use fitted value from regression on subset of ...
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Can multiple logistic regression be performed without a reference/baseline?

I was wondering of it's possible to perform a multiple logistic regression without a baseline reference. The analysis I'm dealing with doesn't have a "natural" baseline reference. Thanks in advance
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How to evaluate collinearity or correlation of predictors in logistic regression?

In linear regression it is possible to render predictors insignificant due to multicollinearity, as discussed in this question: How can a regression be significant yet all predictors be ...
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Partially sparse vectors for training classifiers

Is it a bad idea to use a partially sparse vector for training a logistic regression classifier? By "partially sparse", I mean that about half the vector is actually dense, with real valued numbers ...
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Interpreting interactions in logistic regression output [duplicate]

Using chi-square analysis, I find significant p-values for age (as a continuous predictor variable) and presence of a hip fracture (as a dichotomous categorical predictor variable) for the occurrence ...
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Category prediction in ordinal regression

This could be a naive question. I have three slabs for my dependent variable and when I run the ordinal regression the predicted responses are in first and third slab but no observation is predicted ...
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Is it possible to fit a logistic regression model to a dataset with categorical predictive variables with very high number of levels each?

I want to fit a model to a very large dataset, with a standard binary response variable and with 3 categorical predictor variables with 3000, 15 and 2 levels. Is there any inherent problem in this ...
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Missing value replacement in modeling and scoring

Here I have two questions I build a logistic regression model. While building model I have few observations have NA values, so I replace with mean value. Model is looking good and when we tried to ...
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Low Accuracy using online logistic regression in mahout

I am getting very low value of accuracy on running online logistic regression on standard iris data (150 records). public static void main(String args[]) throws IOException { ...
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Enumeration of covariate patterns in multiple logistic regression

Is there an easy way to identify and flag covariate patterns in SAS or Stata? Working in the context of multiple logistic regression so it would be very difficult to set up flags for each variable ...
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Graph with 2 interacted continuous predictor vatiable

When using glm(link=logit), I detected a significant interaction between two continuous predictor variables. How can I present the results visually using R?
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adjustment of covariates in linear model

I am trying to understand the adjustment of covariates in the linear model such as multiple logistic regression. How does adding a covariate adjusts the coefficients for that covariate (any intuitive ...
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logistic regression- validation dataset

I am working on getting propensity of Households to buy a certain product, I have completed the training dataset for running proc logistic in SAS, my question is 1) My training dataset is a biased ...
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How to answer a clients question on “How accurate your logistic regression model is?”

There are various methods to test the model accuracy, but when it comes to clients you may face people who don't know AIC, ks-statistic, c statistic, confusion matrix, etc. So, how one should answer a ...
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MLE vs MAP vs conditional MLE with regards to logistic regression

We have some set of iid RV's: $(X_i, Y_i), \; i=1,\ldots n$. We believe each to be distributed as $P(X_i, Y_i | \theta)$. So that $$ P(X,Y | \theta) = \prod_i P_i(X_i, Y_i | \theta) $$ Now using ...
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How to deal with unequal sample sizes while fully embrace a dataset?

Imagine the situation: Mythical Seafolk use holes in the seabed as their burrows. Each hole has two parameters - diameter and depth. Majority of holes are unoccupied due to their surplus (n = 235). ...
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Interpretation of multiple logistic regression with interactions in R

I am trying to look at whether 2 variables (one dichotomous categorical and one continuous) predict the occurrence of a dichotomous categorical dependent variable. ...
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36 views

Results with and without interaction

I'm working on an analysis with another person. First we did a logistic regression with study group and variable X. They were both significant. Then we added the interaction between study group and X ...
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107 views

Why am I getting different results for my logistic regression when performed by different software?

My data is simple, my independant variable is continous from 0-1000 and the response is either a 1 or a 0. I'm performing a logistic regression to determine the 50% inflection point. When I put this ...
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49 views

Logistic Regression, SVM or NN?

Just attended Andrew Ng’s online course on ML and although I’ve understood the methods I seem to be missing the intuition on where to apply them in terms of classification problems. What are the ...
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Logistic regression, Chi-square, and study design

I have a study in which I have developed a new predictor (binary) for a disease (also a binary variable). The study has two parts. In the first part, I want to test if my predictor is strongly ...