# Tagged Questions

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### Concordance and Discordance role in modelling

I am new to statistics and was asked to develop a statistical model, which I had started, they ask me to carry out concordance and discordance now, however I don't know anything about these terms ...
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### Blocks and other questions about logistic regression with SPSS

I am trying to use logistic regression in SPSS. I am wondering, do I have to tell SPSS that, for example Gender, is a categorical variable? Also, I am planning to ...
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### Pre-post Logistic regression

A friend of mine approached me to help her to interpret her multinomial logistic regression model. They had measured people as 1 of 2 states at 2 time periods. So, each person can have 1 of 4 ...
161 views

### Assigning values to missing data for use in binary logistic regression in SAS

Many of the variables in the data I use on a daily basis have blank fields, some of which, have meaning (ex. A blank response for a variable dealing with the ratio of satisfactory accounts to toal ...
86 views

### What is the Hotelling $T^2$ used for?

Hotelling's $T^2$ distribution arises in testing differences between means of different populations. But is it often used? Can it be implemented in a modeling procedure, let's say, logistic ...
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### What happens when you fit a linear regression to binary dependent data?

Logistic regression is typically employed when there is a binary dependent variable. What is the difference in the output when a linear regression is fit instead?
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### Which model should I use to fit my data ? ordinal and non-ordinal, not normal and not homoscedastic

Here is the kind of data I have: I have two predictor variables: 1) discrete non-ordinal --> c('a','b','c') 2) discrete ordinal --> c(10,100,200,500) Response variable: Proportion of TRUE over a ...
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### Which model should I use? Logistic regression?

Here is the data I have: Response variable : It contains proportions and it takes discrete values 0, 0.2, 0.4, 0.6, 0.8, 1. But there are 109 possible discrete values Predictor variable.1: Discrete ...
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### Use of 3 different methods - is it the right approach?

I am writing a master's thesis on crowdfunding. For this research I set N independent variables and 3 DVs. The reason for doing so is that I want to explore the phenomenon from the aspects of all 3 ...
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### Multinomial logit model

Why do we need to use a base category (normalised to zero) when working with multinomial logit models? I would also like to ask why do we need to report conditional logit coefficients? Wouldn't ...
203 views

### Not all Features Selected by GLMNET Considered Signficant by GLM (Logistic Regression)

I wanted to create a predictive model of mortality after patients had undergone a surgical procedure. But I also wanted to avoid doing what most researchers do by first performing univariate analysis ...
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### How would you explain logit coefficients to someone with no statistical background

Similar question here. The question I highlighted above provides an overview of how generalized linear models work. However, I find people often want more and ask about how the coefficients were ...
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### 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, ...
111 views

### 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 ...
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### Resources for developing prognostic index-scores

I am looking for online resources or books explaining how to develop prognostic indexes-scores step by step. I am mainly wondering about model validation and transformation of regression coefficients ...
421 views

### Fitting logistic to small number of points in R

I'm trying to fit a logistic function to some data points. Each data "set" has 6 points that I'm trying to fit a seperate logistic function to. Here is some sample code: ...
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### Flexible version of logistic regression

I'm trying to fit a logistic regression where there is a huge difference in the number of data points in either group (70 Vs 10,000). A statistician friend of mine has told me that this is a known ...
144 views

### How to explore/model this problem?

I have data extracted from a state machine. Each row of data looks like this: label1,label2,label3,impedance,did_state_change The column data types are described ...
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### Using Fractional Polynomials for Logistic Regression Modelling in R

I am learning logistic regression modeling using the book "Applied Logistic Regression" by Hosmer. In chpaters, he suggested using Fractional Polynomials for fitting continuous variable which does ...
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### Covariate present in a logistic regression model as a effect modifier, but not as main effect [duplicate]

Possible Duplicate: Including the interaction but not the main effects in a model I'm studying logistic regression now. And I have a question: Suppose I have a logistic regression model as ...
152 views

### Modeling the probability of winning on a sales site

Let's say that I have a dependent variable, the probability of winning on ebay, and I want to model that on various variables. Let's say I have data on each individual ebay item I am bidding on and ...
446 views

### Properties of logistic regressions

We're working with some logistic regressions and we have realized that the average estimated probability always equals the proportion of ones in the sample; that is, the average of fitted values ...
345 views

### What is the best way to reduce false negative percent in the model?

My logistic regression model seems to identify successes very well (about 85% - 94%), but fails to identify the failures (only identifying 18% - 32% correctly). I have thought of weighting the ...
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### Is a logistic regression biased when the outcome variable is split 5% - 95%?

I am building a propensity model using logistic regression for a utility client. My concern is that out of the total sample my 'bad' accounts are just 5%, and the rest are all good. I am predicting ...