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

learn more… | top users | synonyms (1)

0
votes
0answers
9 views

loan default model

I have a loan dataset that includes all the loans originated from 2000 through the most recent quarter. For each loan, available are information at origination, such as loan size, FICO, LTV, LTI ...
0
votes
1answer
23 views

How Spark MLlib: how does the LogisticRegressionWithLBFGS work with discrete variables?

How does the logistic regression model on Spark MLlib (LogisticRegressionWithLBFGS) work with discrete variables (for example sex,race, or indicator variables which ...
-1
votes
0answers
17 views

Logistic Regression with negative signal

I'm trying to build Logistic regression to identify bots. But I found in my dataset that presence of one feature indicate that this is NOT a bot. Unfortunately this feature is not appearing often ...
0
votes
0answers
10 views

How to model a 2x2x2 within-subjects glmer with dichotomous dependent variable

I have a 2x2x2x2 within-subjects design with a dichotomous dependent variable. So far I've modeled this as follows: mod0=glmer(DV ~ fact1 * fact2 * fact3 * fact4+(1|subject), family="binomial", ...
0
votes
0answers
13 views

Robust softmax solutions for Theano?

I am implementing multilayer perceptrons with the softmax activation function over Theano. In some extreme cases I am running into problems with too high/low values in the softmax function that ...
0
votes
1answer
61 views

How to improve this logistic regression model

I am using following data and self-explanatory code to create a model for prediction of 'low' (low birth weight) from modified birthwt dataset. I am using 80% for training and 20% for testing: ...
0
votes
0answers
20 views

How to use Spark MLlib like SAS or R on a logistic regression [on hold]

I have a question about MLlib in Spark.(with Scala) I'm trying to understand how LogisticRegressionWithLBFGS and LogisticRegressionWithSGD work. I usually use SAS or R to do logistic regressions but ...
0
votes
0answers
22 views

Interpretation and meaningfulness of regression coefficients

I have performed logistic regression on banking data which is trying to predict the bad customers correctly due to the cost involved. I have build a model and pasting a picture of the output obtained ...
1
vote
0answers
13 views

logistic regression when data consists of shared and non-shared variables

Could someone point me toward a specific method to model data that consists of two groups of observations having the same dependent variable and sharing some explanatory variables, BUT also having ...
1
vote
0answers
17 views

logistic regression? chi square for trend?

Each semester from 2009 to 2014 (total 10 semesters), students answered an electronic questionnaire before going to a lecture. Answer options were nominal or ordinal, mostly binary: 1 sex (m/f) 2 ...
0
votes
0answers
18 views

Regression model and Social Network Analysis

I want to study the internal Italian migration using the network analysis. My nodes are the Italian cities, the edges are people who move from a city to another. I built my edge list in SPSS. I have ...
0
votes
1answer
18 views

Should I keep or eliminate an insignificant confounding variable?

Let's say that I am fitting a logistic regression model for a binary outcome and I have two covariates: $x_1$ and $x_2$ (both quantitative). I am confused as to what the correct course of action ...
0
votes
0answers
9 views

ROC and post estimation COX Harrell's C using your dataset

I have built a predictive model using a combination of logistic and cox regression models. I did it using a dataset of about 5000 records. I would like to calculate the AUC and the Harrell's post ...
0
votes
0answers
17 views

Diagnosing Unusually High Prediction Accuracy in Logistic Regression Model

I have constructed a logistic regression classifier in Matlab, using all self-written code. The data set I decided to use is the Breast-Cancer data set from UCI's machine learning repository. This ...
1
vote
0answers
15 views

Interpreting p-values of log regressions

The following output is for a log log model. ...
1
vote
0answers
18 views

How to interpret p-values on log log model?

If the p-value of log(independent variable) = 0.0023 for the hypothesis that the independent variable=0, how do I interpret the p-value? Does this interpretation change if this was a simple linear ...
0
votes
1answer
14 views

Testing if variables have a non-linear relationships with the dependent variable

How can I find evidence that a independent variable has a non-linear relationship with the dependent variable? Can I possibly achieve this by squaring all the independent variables and estimate a ...
0
votes
1answer
170 views

Binary logistic regression with only positive training examples - does that even make sense?

(I have learned about polynomial linear regression, logistic regression, and neural networks.) I have a binary logistic regression problem. I need to classify things to be true or false. What makes ...
0
votes
1answer
33 views

Logistic Regresion / SVM / Random Forest Implementation in Matlab

I would like to implement (L2-regularized) Logistic Regression, (L2 regularized) SVM and Random Forest for multiclass classification in Matlab (without using a toolbox or the corresponding functions ...
3
votes
2answers
40 views

Does it make sense to generate prediction intervals for the estimates of a logistic regression?

Say I have a binary outcome of 0 or 1 and suppose I were to use logistic regression model to estimate the probability a new sample will have an outcome of 1. I have read answers (for example here: ...
0
votes
0answers
5 views

Treatment for High Population Stability Index

What are the ways we can stabilize population if we have high population stability index greater than 0.2 in a predictive model? Or how to adjust if it is less than 0.2 but greater than 0.1?
2
votes
0answers
6 views

GEE Logistic Model with Subject Specific Predictions?

I have fit a marginal logistic model or GEE Logistic Regression model using SAS' proc genmod to obtain estimated parameters associated with mortality (death). Using SAS, I am able to obtain ...
0
votes
0answers
25 views

How to validate cluster formed in cluster analysis? [on hold]

Various methods such as One-way MANOVA, LDA and logistic regression have been mentioned in literature. Could you please suggest how to choose a method out of these? and Why? In R for cluster ...
0
votes
0answers
7 views

Do odds ratios have an effect on the variance components (level-2 variance) in multilevel models

I am estimating logistic multilevel models and have a question regarding the variance components (i.e. level-2 variance). I want to report my results as odds ratios and I am wondering if the ...
0
votes
0answers
7 views

Predicting individual treatment effects as the difference between predicted outcomes with and without treatment

To provide some context, I am trying to (a) identify the best ad to increase support for a particular issue among a large group of people, and (b) identify the people most likely to respond positively ...
2
votes
1answer
44 views

Why does the inclusion of an intercept in my logistic regression cause my $R^2$ to decrease dramatically

I am running a logistic regression in order to determine the error rate of an outcome given some covariates. Two of my covariates are indicator flags for the location. When I include an intercept, ...
0
votes
2answers
42 views

Type of predictors for logistic regression

Can predictors in logistic regression be categorical, numerical and ordinal? If categorical, can they be trichotomous?
1
vote
0answers
12 views

Switching “outcome” and “exposure” in multiple logistic regression

I read this question on whether switching the "outcome" and "exposure" changes the odds ratio in bivariate logistic regression. Which it does not. I'm wonder if this also holds for multiple logistic ...
0
votes
0answers
6 views

clogit in R: original variable or demeaned?

Conditional logistic regression is a fixed effects model. If you're modeling the dependent variable $y$, a glm fixed effect model doesn't actually model $y$. Instead, the glm fixed effect models ...
1
vote
0answers
22 views

Power Analysis for Logistic Regression with one nominal variable

How do I estimate sample size or do power analysis for logistic regression with one nominal independent variable? Is there a way to do it with Stata?
0
votes
0answers
37 views

How to separate categorical variables in modeling

Suppose I have a dataset as follows: ...
1
vote
0answers
13 views

Multinomial logistic regression and interaction [duplicate]

I am running a multinomial logistic regression and have my final model, but now want to check for interactions between my two exposure variables and my independent variables. When I run this, one of ...
0
votes
0answers
6 views

Why do logistic curve gives a very good fit to USA's population projection but it does not so for other? [closed]

I'm studying population science and working with population projection right now. Can any one please describe the reason behind very good fitting of Logistic Growth Model in case of the projection of ...
2
votes
1answer
32 views

Is it possible to test for a linear trend when running a logistic regression?

I have a dichotomous DV and a single factor with three levels. Is it possible to test for a linear trend in the log-odds for each level of my factor?
0
votes
0answers
22 views

distribution of residuals in logistic regession

I am fitting binary outcome using generalized linear mixed model (glmm). I checked the Studentized and Pearson residual and they do not seem to be normal. Is it expected that residuals in logistic ...
0
votes
1answer
42 views

How to treat variable in logistic regression?

I have a variable I do not know how I should handle my logistic regression. The variable is the number of registered students each semester. If I plot it against my binary outcome, I get the following ...
0
votes
1answer
31 views

Ordinal Logistic Regression Predicted Probabilities

I'm looking for a way to produce a matrix of predicted probabilities on data that went through SPSS's logistic regression test. I only use two ordinal variables with a range of 1-4 and 1-10 ...
0
votes
1answer
32 views

Interpreting odds ratios as percentages?

## OR ## (Intercept) 0.0185 ## gre 1.0023 ## gpa 2.2345 ## rank2 0.5089 ## rank3 0.2618 ## rank4 0.2119 ...
3
votes
1answer
36 views

Modelling a binary outcome when census interval varies

For a current piece of work I’m trying to model the probability of tree death for beech trees in a woodland in the UK. I have records of whether trees were alive or dead for 3 different census periods ...
0
votes
1answer
37 views

What goodness of fit tests, for logistic regression models, are available in R?

I'm planning to work on some credit risk models using logistic regresson in R. Binary response. What all goodness of fit tests are to be known and WHAT PACKAGES are required for the same? Thank you. I ...
1
vote
1answer
69 views

Interpretation of the Odds-Ratio for percentage value in logistic regression [duplicate]

Running a logistic regression, I have a dependent variable Loyal Customer can be 0 or 1 and an independent variable ...
0
votes
0answers
22 views
1
vote
1answer
60 views

Do we need to adjust sampling weight in logistic regression?

Suppose, I am using malnutrition data from Demographic and Health Survey. This survey used multistage cluster sampling. Here is a sampling weight (probability weight). If I want to say nationally ...
1
vote
0answers
26 views

Non-significant interaction effect

I currently have a regression where adding an interaction effect between two significant variables (a float and a boolean) makes them non-significant. Given that this interaction effect is not ...
0
votes
0answers
10 views

using both raw and weight of evidence values in logistic regression

I am building a logistic regressin model for probability of take-up for a lending product. I have a number of continuous variables. In the past, I have always used EITHER weight-of-evidence ...
1
vote
1answer
59 views

Modeling a proportion using longitudinal data

To illustrate my question I'll make a (very) fictional example. I have a set of 17 year old people that every year report how many cigarettes they smoked and how many miles they ran. Very few of ...
0
votes
1answer
18 views

How is the F-Stat in a regression in R calculated [duplicate]

I am running a regression and I'd like to be able to do the calculation to get to the F stat .3062. How is this .3062 calculated? Can you help? ...
1
vote
0answers
18 views

Rule of thumb for sample size for mixed-effects logistic regression analysis?

Is there a simple way of calculating the minimum number of participants (and/or items) needed for a mixed-effects logistic regression analysis? In particular, what should I do if I don't know what to ...
0
votes
0answers
12 views

How to fit an logistical autoregression in R?

I modeled the relationship of $X$ and $Y$ by the logistic function. The residual plot displays autocorrelation which I'd like to rid. I want to try adding trend component to $X$, thus the model ...
0
votes
0answers
26 views

Logistic regression (multinomial)

Having trouble getting my head around this. I should mention, I am not a staistician and all my 'knowledge' is self taught. I am trying to compare 4 hospital sites for patient outcome (either ...