Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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How do I interpret logistic regression output for categorical variables when two categories are missing?
I am using binary logistic regression; the dependent variable is 1 or 0; the independent variables are two groups: the first group includes continuous variables (...
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54 views
Model for multivariate ordered categorical data with a time-varying continuous covariate
I would like to develop a model for multivariate ordered categorical data that also allows inclusion of a time-varying continuous covariate.
This is for different types of adverse events, that can ...
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1answer
412 views
Logistic regression in R resulted in Hauck Donner phenomenon. Now what?
I'm trying to predict a binary outcome using 50 continuous explanatory variables (the range of most of the variables is -∞ to ∞). My data set has almost 24,000 rows. When I run glm in R, I get:
...
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81 views
Adjusting Logistic Regression Coefficients
I am wondering whether there is ever justification in adjusting your logistic regression coefficients. For example, I have a logistic regression model that predicts that 4% of farmers will go out of ...
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88 views
Interpreting Logit Interaction Term Coefficients (continuous * categorical)
I have the following output from a logistic regression model.
...
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195 views
Logistic Regression Cost Function issue in Matlab
I'm trying to implement a logistic regression function in matlab. I calculated the theta values, linear regression cost function is converging and then I use those parameters in logistic regression ...
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53 views
Implementing a Logit Model With Multiple Predictors
Let's say I have the following equation:
Won = B0 + B1*(Bid)
Once I know B0 and B1, I can generate the probability curve and find the probability of "won" for ...
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162 views
Interpretation of ordinal logistic regression output from SAS
In the SAS output for ordinal logistic regression, how should "Assessment Score Rankings" and "Assessment Score Distribution" tables be interpreted?
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54 views
Ordinal Logistic Modeling
When making ordinal logistic models and you have two or more parameters how can you tell which one has a greater effect on the response variable?
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2answers
50 views
Multinomial logistic predictor matrix
I'm reading Tuerlinkx & Wang, "Models for Polytomous Data". They write: "Apart from the intercept, the predictors that are included in the predictor matrix X can be classified into seven groups: ...
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1answer
20 views
Logistic regression for abiotic influences on behavior
What I am looking to do is test for a correlation between an activity (in this case nesting) with cumulative rainfall from the previous two weeks. For example, say one individual nested on DayX where ...
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1answer
55 views
Predicting dichotomous outcome of temporal data set with covariates
I have a set of data, with outcome and time-varying variables, for patients during the course of their respective stays in the hospital. There is a dichotomous outcome on the last day. The length of ...
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1answer
87 views
Logistic regression without negative samples
I have a data set of RNA reaction values of breast cancer. I want to figure out which RNAs are essential genes by Logistic Regression & LASSO.
The data set has no negative samples. What should I ...
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49 views
Data tranformation in logistic regression
I am running a logistic regression with dichotomous dependent variable (0-1) and with equal interval scale (1-5) as independent variable. The problem is that in order to arrive to meaningful results, ...
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113 views
Logistic Regression failing in some cases
I am working on a website where I collect the results of chess games that people have played. Looking at the ratings of the player and the difference between their rating and that of their opponent, ...
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1answer
126 views
Logistic input with Gaussian noise
Both the logistic function and standard deviation are usually denoted $\sigma$. I'll use $\sigma(x) = 1/(1+\exp(-x))$ and $s$ for standard deviation.
I have a logistic neuron with a random input ...
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61 views
Modeling Future Logistic Regression Covariates
I have a logistic regression model which implicitly estimates the probability that a business will default in each of 8 future quarters conditional upon survival to that quarter. In other words, I ...
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134 views
Logistic VS Linear
What other techniques can be used in place of a Logistic Regression model?
Also is there any other method besides MLE for estimating the Logistic Regression parameters?
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2answers
233 views
SVM prediction sensitivity when compared to neural networks and logistic regression
Basically I want to classify a rather rare status (about 2% of the 2000) with some predictors. I have used logistic regression, neural network, and Support Vector Machines to do it.
All the ...
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104 views
Logistic Regression with dependent observations
I have a dataset that contains 100 different patients over 5 year’s period. Every patient is examined each month with regard to particular illness and marked as healthy or ill (0 or 1). Every person ...
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1answer
127 views
Multinomial regression with categorical choice and predictos and factor analysis
I have a non-ordinal categorical dependent variable with 3 choice outcomes and 20 ordinal categorical predictors and want to do a multinomial logistic regression. However, I want to reduce the ...
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394 views
Diagnostics for Logistic Regression?
For linear regression, we can check the diagnostic plots (residuals plots, Normal QQ plots, etc) to check if the assumptions of linear regression are violated.
For logistic regression, I am having ...
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436 views
Interpreting multinomial logistic regression output in R
I am trying to perform multinomial logistic regression on my data which is as below(just the header).
"category" is my target variable and all other variables are independent variables. category has ...
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38 views
Binary logit with time series
I intend to run a Binary Logit with Wholesale Price Index of different commodities. I have converted these scale variables into categorical variables with the following criterion:
1=Price has ...
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102 views
inverse logistic regression with binary covariates
I am currently using a hierarchical Bayesian framework to investigate a problem with both a single binary response variable and binary covariates, $P(Y=1 | X_i=1), i=1,\ldots,n$. Using R/JAGS I can ...
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115 views
Logistic regression model for analysis of many IVs with a relatively small sample size
I'm trying to determine the influence (direction and relative strength) of certain attributes of incoming students to an academic program on their successful completion of the program. My sample size ...
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2answers
878 views
How to do multiple regression with limited experience and (hopefully) excel?
I am doing a study of how legal need relates to a number of predictors.
Outcome Variable: Legal Need (Yes or No)
Possible Predictors: Age, Gender, Race, Ethnicity, Language, Clinic, Insurance ...
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1answer
109 views
Logistic Regression with weighted instances
I'm working on implementing a logistic regression algorithm in code. It's based this link. Unfortunately, the paper doesn't talk about weighting the individual examples $x_{i}$.
I think the relevant ...
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499 views
Interact categorical variables in GLM in R
I am trying to predict child nutrition (binary) using a set of variables. The two that I want to interact are maternal education (none, primary, middle, HS) and wealth quintile (1,2,3,4,5). Thus far ...
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94 views
Algorithm definition and steps of logistic regression for multiple classes
I am studying logistic regression classifiers for multiple classes and I could only find theoretical explanations of it. I have data like this:
...
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1answer
422 views
Percent correctly predicted of logit model
Is there a standard way to report the percent correctly predicted when predicting a binary outcome? Using glm in r, the results are predicted probabilities. However, in order to make a comparison to ...
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136 views
Logistic regression discrimination threshold with cross validation
I'm using logistic regression to perform binary classification with training, CV, and test sets. When is the most appropriate time to pick a discrimination threshold to balance positive and negative ...
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1answer
274 views
Logistic Regression Algorithm?
I am studying on some Machine Learning concepts. I am looking for logistic regression(multiclass) and logistic regression classifier and I should learn how to change it to penalize large weights.
I ...
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1answer
401 views
Logistic vs Linear Regression
Let's say i run a linear regression model with a binary dependent variable. If I ran logistic regression on the same data would the results be comparable or exactly similar? By results I mean both the ...
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2answers
329 views
How do important and insignificant variables impact model?
I am working to build a model using logistic regression. There is one variable which has strong predictive power. But based on business rule, I cannot include this variable in the model. On the other ...
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1answer
176 views
How to describe characteristics of the curve fit by a four parameter non-linear regression?
I've fit a non-linear mixed effects model with a four parameter logistic function. My specific interest is in characterizing the point on the curve at which the horizontal component of the curve meets ...
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R: mlogit error on data - “system is exactly singular”
So I have data from a randomized blind trial of 1mg of nicotine gum on dual n-back working memory scores; I analyzed them as usual with a t-test and found a small increase in means but a large ...
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1answer
59 views
Experimental Design for Comparative Responses
Suppose I were looking to optimize the amount of certain spices in a chili spice recipe. The textbook experimental design would have me encode the amount of each spice in the design variable, choose ...
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69 views
How to transform an independent variable with parabolic shaped logit plot in logistic regression?
I am building a logistic regression model. I have created some ratio variables. When I look at the logit plot (log odds) of these ratio variables, some of them follow parabolic shape. I am wondering ...
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1answer
183 views
Logistic regression with low event rate
I'm trying to build a logistic regression model to predict 90+ Days past due(DPD) events. The size of the database is 96000, with an event rate of 6%. We ran the entire data set through the info value ...
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50 views
Aliases in fractional factorial designs
I am looking at using a fractional factorial design in order to reduce the number of treatment runs for an experiment involving a binary outcome. The idea is to create the design, then, since this is ...
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52 views
Regression Analysis model
Objective is to predict a car's retail value based on the characteristics of mileage, make, model, engine size, interior style, and cruise control.
Price
The price of the vehicle
Cylinder
...
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1answer
111 views
Reference category in multinominal logistic regression
I was wondering how you get beta values for the final model if you don't
have a reference condition?
I am running a multinominal logistic regression using a dependent variable
that has 6 levels - ...
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53 views
How to code values for males when they're only meaningful for females?
I'm building a predictive model for a medical condition that happens in both men and women. Physicians have reported that in some cases for women, their menstrual history seems to be a risk factor, ...
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1answer
131 views
Logistic regression-like model for non-discrete outcomes
If I have a set of continuous predictors $X$ and a binary outcome $Y$ and I wanted to build a predictive model of $P(Y|X)$, I would start with a logistic regression model.
However, in my particular ...
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1answer
128 views
Checking the regression model's performance
I am R-tool beginner. I have a question regarding how to know the performance of a linear regression model by using validation data.
My approach was
Create training and validation data sets from ...
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4answers
149 views
Extending logistic regression for outcomes in the range between 0 and 1
I have a regression problem where the outcomes are not strictly 0, 1 but rather in the range of all real numbers from 0 to 1 included $Y = [ 0, 0.12, 0.31, ..., 1 ]$.
This problem has already been ...
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4answers
189 views
What type of regression model do I use?
$y = \mathbf{X} \beta$ + $\epsilon$ + $m$
Where y, $\epsilon$, and $m$ are $n \times 1$ column vectors, $\beta$ is $p \times 1$ and $\mathbf{X}$ is $n \times p$.
$y$ is a noisy time-series signal ...
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2answers
199 views
Interactions make terms significant in regression when they should not be
I am writing code to prepare for running a logistic regression on real data. I have sample data for all my IVs but not for the outcome variable. There are many strong dependencies among the IVs but I ...
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1answer
92 views
Algorithm convergence with logistic classifier
I am doing a college classification project, in which I am required to classify some handwritten digits. Assume that my input is a N*D where D is the number of features in each input sample and I need ...
