Questions tagged [logistic]
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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Any technique other than Logistic
All my predictors are binary in nature. So far I have been building the model with the logistic fuction. Could anyone suggest any appropriate statistical technique keeping the following points in mind:...
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performing logistic regression with imputed variables
I am trying to to run a logistic regression (case-control) and the variable of interest is categorical, taking the values 0 to 6. For a subset of individuals, I do not have the exact value (0, 1 .. or ...
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Applying Recency In Logistic Regression
Are there any statistical concepts or theories on how to effectively measure recency to where recent events are given more weight than older ones. I'm creating a logistic regression model and would ...
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Binary panel logistic regression (xtlogit fixed effects) is not converging in Stata, how to resolve?
I have a panel dataset with a sample of 800 groups, each having between 200-500 observations. The data looks like this:
The dependent variable is binomial: ...
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Equation for a logit link function for a series of events
I have modeled some data using generalized linear modeling with a binomial distribution and logit link function. However, my data is not dichotomous, it is actually a series of events. I have fixed ...
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Modeling pass rates for departments and courses within a school
Suppose I have a regression model, for example a logistic regression model, which provides a score between 0 and 1 reflecting whether or not that a student will pass a course given certain variables:
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How to rebalance a dataset for a logit model in Stata?
I want to use logit model in Stata. In my dataset only 3% of my target variable observations are 1, and 97% are 0.
How do I rebalance this data set, so I have more observations labelled 1, and fewer ...
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Reporting of an interaction in a binary logistic regression
I've found some interesting results that I'm trying to write up appropriately, but I'm having a hard time finding any guidance into how to write up an interaction in a binary logistic regression (...
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Is there a multivariate version of logistic regression?
Based on readings with logistic regression, it appears that you could use this analysis to make predictions about categorical variables. Does logistic regression allow you to predict multiple ...
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Maximizing number of positive targets in first decile in logistic regression
When We estimate logistic regression using MLE we try to minimize $-2ln(likelihood)$, which is equivalent to minimization of sum of squared deviance residual.
Is it possible to fit logistic ...
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Log odds ratio and unadjusted log odds ratio when we have a continuous variable
Why bucketing of continuous variables is preferred in logistic regression ? What is the funda behind adjusted log odds ratio and unadjusted log odds ratio when we have a continuous variable ?
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Does every log-linear model have a perfectly equivalent logistic regression?
I am trying to fit a log-linear model to a large number of variables from survey data. There are some reasons that it might be preferable to fit logistic regressions to that data instead. Several ...
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Alternative to LPM and logit regression in Stata
I'm dealing currently with complex dataset that was already tested with Linear probability model and logit regression. I'd like to find an alternative for original regressions.
The sample uses a ...
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Logistic regression model comparison
I want to use logistic regression to look at how a continuous variable that I have measured for a sample of participants (how long they looked at a product) is impacting a dichotomous variable (...
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I'm not sure how to interpret my binary logistic regression output from SPSS
My dependant variable is diagnosis of cancer malignant being 0 and benign being 1. And my covariate is mean radius (of the tumour). I get this:
...
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Logistic regression with categorical data
I'm trying to apply logistic regression to the data with binary predictor. But some of my variables are numerical and some are categorical. If I just do this in R I get the model where for every ...
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Fitting a logistic regression using lassoglm in matlab [duplicate]
I am fitting a logistic regression model using lassoglm in matlab. I issued the following command
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Multiple comparison issue in multivariate logistic regression
I am assessing a bunch of risk factors related to HIV infection by logistic regression.
First I will conduct a couple of chi square tests or t-tests to see if each factor is associated with HIV ...
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In my logistic regression model one of the independent variables is redundant with the interaction term. How should I deal with it?
In my logistic regression is the dependent variable a dummy variable and I also have two independent variables. One of those is a dummy variable and the other is a metric variable. I also suppose an ...
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What does the logit value actually mean?
I have a logit model that comes up with a number between 0 and 1 for many cases, but how can we interprete this?
Lets take a case with a logit of 0.20
Can we assert that there is 20% probability ...
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How to interpret statistics (Emax, D, U, Q, B, etc.) of bootstrap validation of logistic regression
I'm only a linguist, so my knowledge of statistics is very basic.
I fitted a logistic regression model with R (with lrm(formula, y=T, x=T)), and when I use the ...
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Asymmetric S-shaped function mapping interval $[0, 1]$ to interval $[0, 1]$
In the literature, is there any asymmetric $S$-shaped function that maps the interval $[0, 1]$ to interval $[0, 1]$?
Unfortunately I can't post figure so I just describe what I mean in text. The ...
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categorical independent variable with three levels and binary logistic regression
I want to learn which level of a categorical independent variable should I look to interpret the odd ratios in binary logistic regression. For example, I have one independent categorical variable (...
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How are the p-values of the GLM in R calculated?
I have been running some binomial logistic regressions in R on a data set and I realised that the p-values of the estimated coefficients are not computed based upon a Normal distribution. For e.g. I ...
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How does Logistic regression classifier modelize the dataset?
I'm working on a system that be able to detect the hand contour. So I have 270 instance in my dataset: 7 class of hand contour, 8 feature vectors of each instance.
Firstly, I used Weka to determine ...
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Which test(s) for analyzing yes-no answers for control vs treated conditions
To keep it simple, I have sets of data in which I have a control and a treated sample. The data I obtain is "yes" or "no" (0 or 1) for a particular behaviour. I have 150 data points for each condition ...
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Logistic regression as classifier and overfitting
I am using logistic regression to classify data into two classes. The variable to predict (Y) is either 0 or 1.
I have found a rather good estimation of Y by logistic regression, and ended up using ...
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Binomial GLM and different sample sizes
I have a data set which consists of binomial proportions, let's say the success rate of converting a customer depending on the advertisement, the customer age, and various other factors.
For some ...
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Ordinal dependent variable with continuous independent variables
I have an ordinal dependent variable, named D, which varies from very small, small, medium, big, to very big. This variable depends on the independent variables X, V, which are continuous variables. ...
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Modeling a outcome variable heavily skewed toward 0
I am working with a data set to model student performance with numerous variables from the class/school/district/provincial level. Student performance is extremely low though -- 70% of reading ...
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Multinomial logistic regression vs one-vs-rest binary logistic regression
Lets say we have a dependent variable $Y$ with few categories and set of independent variables.
What are the advantages of multinomial logistic regression over set of binary logistic regressions (i....
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Using priors to detect an effect? logistic Bayesian regression
I have designed an idea and am looking for similar approaches in other literature/areas or if I have applied the Bayesian concepts wrongly. Here is a statement of my problem:
I am modeling the ...
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Conditional analysis vs conditional logistic regression
What is the difference between "conditional analysis" and "conditional logistic regression"?
It is also really hard to find out an easy example of that "conditional" means in this case...
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If using interval data (independent variables) and grades (outcome or dependent variable), what type of analysis would one use?
First of all, my background in statistics is a bit shaky these days due to a trauma to the brain. I am considering a study that examines at least three independent variables (e.g., creativity, locus ...
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What data cleaning to do for logit regression with only dummies?
Does anyone know what exact data cleaning steps one need to undertake in order to clean data for a logit regression (not a logistic regression)?
I have only time variables, meaning year and month, as ...
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logistic regression with independent categorical variables with more than two possible values using stata
I have to do a logistic regression with independent categorical variables with more than two possible values. Which is the best way to deal with such variables using Stata or spss? I need to have Odds ...
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How to get SGD to reach global optimal point in logistic regression?
I am trying to write a tool which involves implementing logistic regression. With the batch gradient descent method, the convergence is guaranteed as it is a convex problem. However, I find that with ...
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Is conditional logit a specific form of GLM? And what are its specificities?
Background: For a project, I am fitting a conditional logit model where I have 5 control cases for every realized case. To do that I use the clogit() function in ...
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Estimate just the constant coefficient in logistic regression
How do I calculate the constant coefficient in logistic regression manually, i.e without having to use a calculator?
My model is
$g(Y) = X \beta + \alpha$
is it possible to calculate just the ...
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What is the difference in what AIC and c-statistic (AUC) actually measure for model fit?
Akaike Information Criterion (AIC) and the c-statistic (area under ROC curve) are two measures of model fit for logistic regression. I am having trouble explaining what is going on when the results of ...
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How to interpret a logistic regression model with all negative coefficient?
I have 4 predictors, and 1 binary response. I fitted a logistic regression model. A strange thing is that all the coefficient of the model are negative. Is that possible? Probably I did something ...
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Exploratory analysis: regression model with mutually correlated predictors to explain a dichotomous outcome?
I am attempting to explain a dichotomous outcome variable using a large set of continuous valued sensor-derived variables. Many of these variables are highly mutually correlated, some are based on ...
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Analysing a grouped 0 to 10 scale using ordinal logistic regression
I read in an article that the logit link is considered
suitable for analyzing ordered categorical data evenly distributed among all categories.
I want to do ordinal logistic regression and I have an ...
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Categorical logit Predictor with too many different levels [duplicate]
One of the predictors I had in a logit model is "City". Problem is this categorical variable has too many factor levels. e.g. In a Sample of $\sim 3000$ there are already $\sim 200$ different cities. ...
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Building separate logistic regression models for each categorical variable? [duplicate]
I am building a binary logistic regression model. I am not sure if using the variables as interactions is a better choice than building separate models for level of a categorical variable. Is there a ...
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logistic regression sensitivity and other terms
I'm a master's level statistician and have been doing logistic regression for a while. I'm helping a friend who is taking an advanced stats course and ran across some terms I'm not familiar with when ...
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Success of a logistic regression model
Say I have a model $y=f_n(x_1,x_2,x_3)$.
Here say $y$ is categorical and binomial response. i.e. $y$ can be only 0 or 1. Data shows 87% 1 and 13% 0 values.
I fit a multinomial logit on a test ...
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Problem with interaction variable for logit regression
I have a short question regarding interaction variables:
In a logit regression with 2 independent dichotomous variables (A and B), both variables are significant. By including the interaction (AxB) ...
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Getting a data frame of logit probabilities and their confidence intervals
I have the following model and have used the effects package to plot the predicted probabilities and the confidence interval lines. However, I was wondering how I'd go about spitting out a data frame ...
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How do you test for independence of k binomial variables?
I am analyzing some orthopedic data and our outcome is union vs. non-union of a fracture. One of our independent variables is whether or not the initial fracture was closed (skin intact) vs. open. ...
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