Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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1answer
84 views
Pearson correlation vs. logistic regression coefficients
From a bunch of data points which look like:
...
1
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1answer
59 views
Ordinal variable with 0.3% of observations in one category - delete, ignore?
The response variable in my ordered logit model has 5 categories ranging from '1 = strongly disagree' to '5 = strongly agree'. However, only 0.3% of observations fall into category 1 (4 observations ...
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0answers
301 views
Intepretation of crossvalidation result - cv.glm()
My logistic model has been suspicious due to enormous coefficients, so I tried to do a crossvalidation, and also do a crossvalidation of simplified model, to confirm the fact that the original model ...
3
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1answer
244 views
Observed vs predicted values from a logit model
I have a logit model and am trying to understand and compare the predicted and observed values generated by the model. Let's say data set had 100 values and I generate all the predicted probabilities, ...
2
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1answer
153 views
Enormous coefficients in logistic regression - what does it mean and what to do?
I get enormous coefficients during logistic regression, see coefficients with krajULKV:
...
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1answer
63 views
Binary regression with error-in-variables
I try to predict the binary, dependent variable $Y$ using a single predictor $X$. $X$ contains some amount of error, due to measurement problems.
I would like to come up with a model for $X$, e.g. ...
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2answers
147 views
Logistic regression and odds ratio
If the odds ratio is greater than one with an insignificant p value for a variable in logistic regression should the variable be kept in the model?
Can I select the variable with odds close to 1?
...
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1answer
96 views
Causality test for logistic regression
For time series there is the Granger causality test. Is there some causality test for the logistic regression?
2
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2answers
343 views
What is the difference between logit-transformed linear regression, logistic regression, and a logistic mixed model?
Suppose I have 10 students, who each attempt to solve 20 math problems. The problems are scored correct or incorrect (in longdata) and each student's performance can be summarized by an accuracy ...
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1answer
101 views
How do factor categories with no variance influence logistic regression?
I'm modeling the effect of a categorical predictor on a binary dependent variable using logistic regression. I'm comparing models with/without the predictor using a likelihood-ratio test.
Two ...
3
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1answer
360 views
Power calculations, logistic regression with continuous exposure--cohort
I'm trying to estimate power in a logistic regression with a continuous exposure in a cohort study (ie, the ratio of the sampling probabilities is 1). I have population cumulative incidence ...
4
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0answers
122 views
Is standardization needed before fitting logistic regression?
My question is do we need to standardize the data set to make sure all variables have the same scale, between [0,1], before fitting logistic regression. The formula is ...
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0answers
33 views
Does it make sense to include higher level predictors when there is no higher level variance?
I want to test the relative importance of incident, victim and neighbourhood characteristics on the probability of a crime being reported to the police. I use a three-level random intercept logistic ...
2
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0answers
91 views
Variable selection with restricted cubic splines
Is there any function in R for doing variable selection (backward elimination) in a multiple logistic regression using restricted cubic splines like mvrs procedure for STATA?
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1answer
124 views
Variable selection and logistic regression
I am using Matlab, I have a $600 \times 9$ matrix with each row representing the 9 features which I am trying to evaluate using logistic regression.
I understand that I need to perform feature ...
4
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2answers
257 views
Likelihood-ratio test or z-test?
Consider the following two logistic regression models:
$$
\begin{aligned}
&\text{Model A: }&P(Y=1)&=\frac{\text{exp}\left(b_1+b_2X_2\right)}{1+\text{exp}\left(b_1+b_2X_2\right)} \\
...
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0answers
70 views
Extremely unequal sample size in logistic regression [duplicate]
Possible Duplicate:
Does an unbalanced sample matter when doing logistic regression?
I’m hoping for help on dealing with unequal sample sizes for logistic regression analysis. Any ...
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4answers
311 views
Is the logit function always the best for regression modeling of binary data?
I've been thinking about this problem. The usual logistic function for modeling binary data is:
$$
\log\left(\frac{p}{1-p}\right)=\beta_0+\beta_1X_1+\beta_2X_2+....
$$
However is the logit function, ...
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0answers
45 views
Fitting a logistic curve with absolute value loss
I was wondering whether the procedure of fitting a logistic curve with absolute value loss has a well known name / commonly available implementation.
The idea behind this is that if I have two ...
1
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1answer
52 views
How can I implement logistic regression in live decision system?
I got the equation for logistic reg, and I am comfortable with the result. Let's say logit(p), ln(p/q), or the model is something like
$\text{logit}(p) = b+a_1X_1 + a_2X_2 + a_3X_3$
For example ...
3
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1answer
114 views
Indicator variables and backward elimination with GLM
I am running logistic regression using glm in R on data, that has some indicator variables to it. Two of those have multiple levels and have been rewritten as ...
4
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2answers
220 views
In logistic regression, does the lack of significance of the parameter estimates in a test sample indicate overfitting?
I am trying to build a logistic regression model where I have a dependent variable $y$ and independent variables $x_1$, $x_2$... $x_n$. $y$ can take only two values - 0 or 1.
My original modelling ...
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1answer
37 views
what model to use [closed]
I am currently studying a rate of a procedure and how does the rate differ between races. It appears that the procedure is more offered to Hispanic patients than any race and is more done in the ...
4
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1answer
203 views
What's the most pain-free way to fit logistic growth curves in R?
This isn't as easy to Google as some other things as, to be clear, I'm not talking about logistic regression in the sense of using regression to predict categorical variables.
I'm talking about ...
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1answer
180 views
Confusion related to multicollinearity, FA and regression of heterogeneous data
I am currently working with a data set that contains about 26 IVs of almost all sorts of scale of measurement (binary, nominal, ordinal and interval scale variables). There are strong reasons to ...
1
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0answers
73 views
Explain ridge in the log-likelihood for Logistic Regression classifier
What does the ridge parameter change in a Logistic Regression classifier as for example implemented in Weka Logistic classifier "Parameter -R ridge". The paper describing the underlying theory: Ridge ...
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0answers
84 views
How to test proportions of a Categorical response variable for a Repeated measures design with Unequal Sample Size?
I have a question about the analysis of a unequal sample size repeated measures data with categorical response variable.
This experiment looks at 5 young and aged persons and for each of the ...
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1answer
75 views
residualize binary outcome variable
Does it make sense and what is the correct approach to residualize a binary variable? For a continuous variable y, I simply run a regression that predicts ...
3
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1answer
152 views
Logistic regression: how to choose negative examples for training set
I want to predict the probability of rain based on the measured weather parameters like temperature, humidity, etc. Let's not get into why I want to do that despite the fact that weather websites ...
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0answers
31 views
Do we need to apply the same transformation of predictors on a test dataset?
This maybe a stupid question. But I hope someone could help me. I first divide the dataset into training (75%) and test (25%). Then fit a logistic regression model on training data set. When fitting ...
5
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1answer
183 views
How to run a logistic regression with multiple related dependent variables?
Background
In a small online study I asked people (n=100) which products they would purchase. The choice set contained 20 products for which they had to indicate whether they would buy a product or ...
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2answers
427 views
Interpretation of the regression coefficient of a proportion type independent variable
If I want to use some proportion type independent variables in a logistic regression, then what will be the interpretation of the regression coefficients corresponding to those proportion type ...
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1answer
129 views
Logistic Regression with holdout sample [closed]
I am trying to run a logistic regression in R on my data where my independent variables are 13 continuous variables and my dependent variable is binary. I want to segment my data so that I train on ...
1
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1answer
70 views
Variable entered in logistic regression model is part of another variable entered in the same model
I´m trying to find variables predicting a disease by using first logistic regression for each variable on the disease and then entering the significant variables into a multiple logistic regression ...
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1answer
79 views
Simple way to fit large number of single factor logistic regression models in R - automatically
I have a dataset with one binary target variable called “target” and many many factors “F1”, F2”… “F200”. I’m trying to come up with code to fit 200 single factor logistic regression models and return ...
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0answers
109 views
Regression with both dependent and independent variables in proportions
I have a dependent variable which measures the proportion of staffs who departed last year for about 200 organizations. The organizations are of different sizes (small, medium, large). There are some ...
4
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3answers
176 views
What are good techniques for modeling small datasets?
I’m working on a classification problem. However, my training dataset is very small (just 800 items in training dataset) and each data item contains a small number of features (just 5 features). ...
4
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1answer
118 views
Adding a quadratic term: should I use the squared original (and not the squared standardized?)
In a multiple logistic regression I need to standardize one of the variables because I need to add a quadratic term. Whether I add the quadratic term as the squared original or the squared ...
2
votes
2answers
147 views
Importance of variables in logistic regression
I am probably dealing with a problem that has probably been solved a hundred times before, but I'm not sure where to find the answer.
When using logistic regression, given many features $x_1,...,x_n$ ...
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1answer
114 views
Panel data analysis with ordered probit model
I have a panel dataset of survey responses collected by the world bank in Egypt in 2004, 2006, and 2008. I want to run an ordered probit model to test the impact of firm characteristics on their ...
2
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2answers
511 views
Plotting logistic regression interaction (categorical) in R
Hello I have the following logistic model with a categorical variable interaction which I wish to plot in R but I am struggling to find any solutions -
...
3
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2answers
322 views
How to combine results of logistic regression and random forest?
I am new to machine learning. I applied logistic regression and random forest on a same dataset. So I get variable importance (absolute coefficient for logistic regression and variable importance for ...
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0answers
97 views
Stuck with interactions in logistic regression analysis
I would like to get some tips, because I am currently stuck with my regression part. I am using binary logistic regression. The aim is to compare two separate groups' responces. I have a MV (moderator ...
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0answers
53 views
Which test to compare two datasets?
I have used a stimulus (stimulus1) in a perception test, to see if the participants perceive it as A or B in a forced choice task. (the stimulus is composed of several features f1,f2...)
Then I have ...
1
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3answers
80 views
Binary Logistic Regression: Direction of B's different in multiple than in bivariate cases
I am interested in the combined effects of 12 continuous/interval predictors on a dichotomous/binomial outcome and thus am using logistic regression.
First I ran 12 separate bivariate logistic ...
5
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0answers
154 views
How to test for mediation when working with binary data?
I want to assess if a single variable is mediating the effects of a set of IVs on a single DV. All variables in the model (IV, DV and the mediator variable) are dichotomous (0, 1) and observed. What ...
2
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0answers
312 views
Measure of goodness-of-fit in Ordinal Logistic Regression with continuous independent variable
In case of the ordinal logistic regression, both of the goodness-of-fit statistics, Pearson and Deviance goodness-of-fit measures, should be used only for models that have reasonably large expected ...
4
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1answer
553 views
How to simulate artificial data for logistic regression?
I know I'm missing something in my understanding of logistic regression, and would really appreciate any help.
As far as I understand it, the logistic regression assumes that the probability of a '1' ...
2
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0answers
45 views
Dealing with dependant data when estimating probability of an event happening
I have 10 year worth of data from 1970 to 1980 (40 quarters).
For each quarter I have five measurements M1, M2, M3, M4 and M5.
TWIST: Although the data I have is on individual patient level the ...
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2answers
140 views
CI for logistic regression
What does it means if no CI was given for binary logistic regression analysis in SPSS output?
