Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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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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3answers
51 views
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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1answer
141 views
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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2answers
174 views
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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138 views
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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83 views
Modeling a outcome variable heavily skewed toward 0
I am working with a data set to model student performance with various variables from the class/school/district/provincial level. Student performance is extremely low though--~70% of reading ...
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29 views
Replicates in logistic regression: identifying significant factors
I'm investigating whether the factors Height (3 levels) and Distance (3 levels) have a significant effect on the proportion of females that are mated by males radiating from a central source. My ...
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364 views
Multinomial logistic regression vs 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? ...
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150 views
Using lme4 for case-controlled logistic regression?
I would like to use lmer for a conditional (or case-controlled or matched pairs) mixed effects logistic regression. However, I am not aware of any published use of ...
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85 views
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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70 views
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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160 views
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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73 views
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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54 views
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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107 views
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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1answer
93 views
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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75 views
Compute categorical variable importance for logistic regression
I am dealing with huge(2 lac rows = 200,000 rows) dataset with a combination of categorical and numerical variables for predicting binary values.
My data set format looks like :
...
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465 views
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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132 views
Repeated measures multinomial logistic regression
I am unsure if this is permissible and just want to get input from others.
I am aware there is another post on repeated measures logistic regression but I did not find what I was looking for in it.
I ...
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539 views
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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41 views
difference between lorenz curve and ks curve
What is the difference between lorenz curve and ks curve in case of logistic regression.What is it that each one do in analysing the data?
I know lorenz curve deals with inequality and KS is a plot ...
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1answer
152 views
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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81 views
Cross Validation in logistic regression [closed]
I have run binary logistic regression on 11 dichotomous variables (IV) in SPSS. The model I got is used to get the probability in EXCEL to cross-validate equation. I am not getting the same ...
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177 views
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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42 views
How to calculate vector-valued power to detect significant coefficients in a multiple logistic regression?
I'm running an experiment. Once I gather my data, I'm going to fit the model
$$
pr(y=1) = \Lambda[\alpha + \beta_1T_1 + \beta_2T_2 + \beta_3T_3 + X'\gamma +\epsilon]
$$
where $\Lambda$ indicates ...
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Reformulate binary classification: Relative penalty of false positives versus false negatives
I have a training data for a set of insurance claims that I used to train multiple models within R (1. Binomial Logistic regression 2. Naive Bayes 3. k nearest neighbor algorithm)
The binomial ...
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104 views
Building separate logistic regression models for each categorical variable
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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53 views
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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44 views
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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208 views
Interpreting the results of a binary logistic regression
This is a basic question. I have been handed a binary logistic regression. The model has significant terms, but the goodness of fit tests indicates the logit model is not appropriate. The author of ...
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40 views
Nested outcome categories in a multinomial logistic
I’m modeling a target-shooting video game. A player can shoot and hit the target, shoot and miss, or switch weapons. For simplicity, the outcomes are HIT, ...
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How to validate and compare models predicting a binary variable?
I have a question about determining which models are "better" and how to assess that info.
Let's say I have three models, each which predicts our bid on won ping. Our bid is a continuous variable and ...
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Categorical independent variable and logistic regression
I am creating a logistic regression model as follows. The dependent variable is outcome of a game (Win/Lost) and the independent variable is the degree of MOON on the day of match. So when I take a ...
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What is an acceptable proportion of events in logistic regression?
In market research I'm building a logistic regression model to estimate the likelihood that clients may change banks. The proportion of events is roughly 10% in my sample.
From university I remember ...
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143 views
Simulating data for logistic regression with a categorical variable
I was trying to create some test data for logistic regression and I found this post How to simulate artificial data for logistic regression?
It is a nice answer but it creates only continuous ...
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137 views
Using Duan Smear factor on a two-part model
I'm running a two-part model on a health insurance claims dataset where I predict the probability of nonzero health care costs using a logistic regression (1st part), then predict the magnitude of the ...
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Pooling data with unequal sample sizes
I have searched far and wide for a clear answer to my question (and am aware that a clear answer may not exist) and I'm hoping someone might be able to help me:
I have survey data for 4 samples of ...
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74 views
How do you perform a bayesian ordered logistic regression in R?
Trying to perform a Bayesian ordered logistic regression in R where age is my outcome variable. I have installed the ARM package but I am unsure how to go about generating my model in R. I also need ...
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Assumptions of generalized linear models
On page 232 of "An R companion to applied regression" Fox and Weisberg note
Only the Gaussian family has constant variance, and in all other GLMs the conditional variance of y at $\bf{x}$ ...
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190 views
Logistic Regression - Bayesian Approach - Assessing Classification Precision
I have recently begun to read about bayesian statistics and I am playing around with the R2WinBUGS package. I'm trying to fit a logistic regression to the spam data (that can be found on the webpage ...
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46 views
Confusion while using lassoglm
I am trying to fit a logistic regression model with L1 regularization on my data. My data has just 12 examples with 150 features. So I used L1 regularization. Now when I use the lassoglm function like ...
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How do I compute a cutoff based on sensitivity/specificity when the characteristics of my sample is different from the population?
I have a dataset containing the performance of a novel instrument to screen for disease A. The novel instrument uses a scoring system to score the subject to determine if they have disease A. I then ...
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How to compare whether the odds of success of different levels of a predictor are different from 0
I hope I am able to word my question clearly. Suppose I have a model below:
glmer(Y~X + (1|subject), family="binomial", data=dat)
The intercept is the log odds ...
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87 views
Question about the validation step for a multinomial logit model
I've been skimming through a couple of books (all german ones, hence I do not cite them here) at what residual plots one should look at if the usual model assumptions in the context of a multinomial ...
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3answers
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What to do when the predictors do not accord with common sense/literature, but the model is fine/best according to log likelihood and LRT?
I would try to clarify the problem and then ask the questions.
The problem (variable names are masked due to confidentiality):
I ran a binary logistic regression, in which there were 5 ...
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Comparing logistic regression models with the same IVs
I have multiple logistic regression models with all of the same IVs/controls and a variety of DVs (all health outcomes from the same sample). The primary IV is the sum of types of childhood abuse ...
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165 views
Significant logistic regression model but poor goodness of fit
What should one do, if the parameters for a logistic regression model are significant as well as the model itself, but the test for the goodness of fit show that the model is bad (i.e. the P-values ...
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Scorecard logistic regression — include or omit credit grade?
I am using logistic regression to create a credit scorecard from past loan data. We will not approve loans in the future if the applicant has an insufficient credit score (no credit or insufficient ...
