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

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Is this interpretation of mixed ordinal logistic regression correct?

I am doing mixed ordinal logistic regression using clmm function in ordinal package. Before running the clmm model I have changed my DV into ordinal variable using: ...
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9 views

Linear regression for classification

Suppose, I have a classification problem with 2 classes 0 and 1 and evaluation criteria is AUC. I used the following method: fit a linear regression and then pass its predictions through the logistic ...
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96 views

Binary outcome in randomized controlled trials — OLS or logistic?

I'm running a randomized controlled trial which has good balance in the co-variates. I'm unsure whether to use: OLS: $P(Y_i=1) = \beta_0 + \beta_1 \text{Treat} + \epsilon_i$. This is problematic ...
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8 views

Diference between glm and bigglm estimates

How does bigglm function in biglm package work for logistic regression? I thought that it is not possible to calculate LR on chunks of data and then merge results. Will glm and bigglm yield ...
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30 views

How to reproduce a plot with fitted value graph and lowess smooth graph superimpose? [on hold]

I have a binary response variable (y) and continuous explanatory variable (age). I utilised logistic regression to analyse them. I have a plot of y against age. What I want to do now is superimpose ...
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13 views

Forecasting Unobserved Values from a Bayesian Multilevel Model

I'm interested in forecasting from a Bayesian multilevel logistic regression. The setup is as follows: $$y_{i,j} \sim \mbox{Bernoulli}(p_{i,j}) \\[0.5em] \mbox{logit}(p_{i,j}) = \beta_{0,j} + ...
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38 views

How to evaluate the optimal cutoff of ROC curve related to logistic regression using roc from the R package pROC?

I would like to get the optimal cutoff of an ROC curve relating to a logistic regression. I am using the roc from the R package pROC. I am assuming same cost of false negative and false positive using ...
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6 views

What's the best way to model two insurance categories that are non-exclusive?

I am modeling insurance status in a logistic regression as separate dummy variables for private, Medicare, Medicaid, uninsured, etc. For people that are dual eligible, should I have a separate "dual ...
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23 views

Interpretation of odds ratio

Can anyone help me interpret the results on the attached figure (drivers of preterm birth in Missouri)? This is the result of a multivariate logistic regression analysis. What can be inferred from ...
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7 views

Fitting several growth models using grofit vrs nplr?

I have having a tough time fitting a a series of grow models to a fairly simple dataset. I'd like to fit several growth models and compare using AIC or some other model selection method. However I ...
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13 views

Develop a model from the 89 specimens that you can use to predict the group membership of the remaining 199 specimens’ [on hold]

I have written some codes in R i dont know if i got it right i need your help and guilddance to go about this problem it will be due in two days time (Vole Data)- Consider the “microtus" dataset in ...
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25 views

SPSS logistic regression. categorical --> dummies

All our variables (question asked to students in our questionnaire) given by school are answered by: 1) very important 2) important 3) unimportant 4) vert unimportant we want to use these variables ...
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Interpreting Odds Ratios for Natural Log transformed Variables

For those who are using Stata the following command clogit Y X,or would produce the odds ratio from the Conditional logistic regression which is the change in the ...
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how should l write the code for this question ?"display the longest ?? [closed]

"Display the details of the student that has been working the longest in the school (in terms of the hire date)>> help me to write this code for this question if you ?? quickly ??
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2answers
25 views

Can a continuous effect modifier be categorized into quartiles? [duplicate]

Is it statistically sound to dummy code a continuous variable (effect modifier) into quartiles and compare the odds ratios of an IV vs. DV in Q1 and IV vs. DV in Q4 in logistic regression? If so, how ...
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17 views

Mixed logistic model with complete separation

I want am trying to produce a mixed logistic model but certain explanatory variables suffer from complete separation. I am aware that I need to either use exact logistic regression or a firth ...
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35 views

Logistic Regression Get 100% R-square but no predictors are significant? [duplicate]

How could that be possible? The model is significant too. The null model already predicted 70% correctly. After adding predictors, the model predicts 100%. But no single predictors are significant. I ...
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1answer
16 views

Modelling ordered data which violates proportional odds assumption

I have a dependent variable which describes how many pounds an individual contributed to a cause. The amount is in whole pounds and out of a maximum of 5 (ie. 0,1,2,3,4,5). I have 2 independent ...
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24 views

Adjusting Binary Logistic Formula in SPSS

I am running a binary logistic regression in SPSS, to test the effect of e.g. TV advertisements on the probability of a consumer to buy a product. My problem is that with the formula of binary ...
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35 views

Fitting logistic function in R, response unconstrained to 0 < Y < 1

I want to fit a logistic function of the form $$f(t) = \frac{C}{1+ab^{-t}}$$to some data that I have, using R. There is some uncertainty to $f(t)$, and its ...
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26 views

Logistic regression and the 2 by 2, or 3 by 2 contingency table

I just have a question about logistic regression and the 2 by 2 or 3 by 2 or n by 2 contingency table: the table can be found here: http://en.wikipedia.org/wiki/Contingency_table My question is when ...
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11 views

(mgcv) Put constrain on max (or min) predicted value

I want to fit my data using a logistic gam model with cubic regression splines. I know for sure that in reality my estimated probability should not go above 0.5 (due to mislabeling). So I thought ...
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47 views

LogisticRegression - binary classification, “custom threshold”

I have a binary classification problem that I am trying to solve with sklearn's Logistic Regression. I am aware of the fact that the predict_proba() function is apparently only an approximation of the ...
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Ridge Logistic Regression in R [on hold]

I write the code for Iterative Newton Raphson for logistic Regression. Now I need to use the Ridge logistic regression. Any help to edit the code to have the coefficients after applying Ridge. And the ...
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Inference possibilities for matched case-control study

We have contracted out collection of survey questions for the group of our customers. These customers even when sampling all of these represent less than 1% our our customer base. We would like to ...
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35 views

Bayesian Network or Logistic regression?

The Bayesian Networks and Logistic regression can be used to predict events or give to each customer the propensity to have a behavior. Which are the advantages or disadvantages of these 2 methods? ...
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Model for the response of campaign in generalized linear model

Part of this question concern actual case and other is hypothetical case. Suppose that agent calls list of leads and offers them particular product. Agent records response in the CRM system which ...
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32 views

How to determine whether a dataset can be learned by Logistic regression?

As far as I know, Logistic Regression can deal with data in which positive and negative samples can be separated by a linear hyperplane. But if the data cannot be separated by a hyperplane, it cannot ...
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41 views

Dealing with Postcode in Regression

I'm building a logistic regression model and one of the variables I have is postcode, I might be over thinking this but is it fine for me to leave postcode as is and regress it as: ...
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34 views

Method to identify the point in which the slope of a predicted probability becomes significant

I'm running a logistic regression in which I'm predicted a binary response from a continuous predictor... I'm interested in determining the exact point in which the predicted probability ...
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56 views

How to regress two categorical variables

I'm not looking for a detailed answer, just some pointers towards possible things I could read to better understand this problem. Let's say that we have a survey that asks two questions, $X$ and $Y$. ...
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21 views

How binary quantile regression divides the dependent variable into quantiles

I'm not very clear with binary quantile regression. As if it was ordinary quantile regression, it would divide the dependent variable's value by its ascending value into quantiles. But I cannot ...
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Is monotonic sigmoidal relation between p and X'B in logistic regression equivalent as logit[p] having linear relation with X'B?

Is the requirement of monotonic sigmoidal relation between p and X'B in logistic regression equivalent as logit[p] having linear relation with X'B? X is the vector of independent variables and B is a ...
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Logistic regression and cluster ID

The dataset consists of all prescriptions classified as on or off-label (0 or 1), meaning possible more than one prescription per child (pnr-number) I want to know the off-label rates per year for ...
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41 views

Random-effects probit model

I am currently using a mixed binomial model with the following specification in a paper I recently submitted (using lme4): ...
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131 views

Zero-inflated negative binomial models: why not use two separate models?

Zero-inflated negative binomial models have two components: a count component (negative binomial regression part) and a zero component (logistic regression part). Why not just run two separate ...
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Model block not significant but interaction dummie is, should I interpret it?

Im doing a binary logistic regression with various blocks. I got 2 interactions. Of 1 the block is not significant in total, but some dummie combinations of the interaction are. Should I still ...
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81 views

Logistic regression simulation in order to show that intercept is biased when Y=1 is rare [duplicate]

I'm trying to simulate a logistic regression. My goal is showing that if Y=1 is rare, than the intercept is biased. In my R script I define the logistic regression ...
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27 views

How to evaluate variable contribution to a prediction

I need to produce a logistic regression model that: Gives a ranked list of the most important factors Allows you to break out most important factors for each new observation scored Given that I'm ...
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28 views

I have a very large value for Exp(B) in logistic regression, what is the problem and what should I do?

What is the problem in statistic when odds ratio (Exp B in logistic regression)has large value and no confident interval value or 00 (zero)
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Can I use regression to predict a binary variable based on 35 variables?

I try to build a model behind a dating website which gives an optimal match between two people, based on 35 variables such as: age location interests characteristics car yes/no etc My ...
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Describing Results from Logistic Regression with Restricted Cubic Splines Using rms in R

Updated I have been developing a logistic regression model based on retrospective data from a national trauma database of head injury in the UK. The key outcome is 30 day mortality (denoted as ...
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Methods for ordered logistic regression validation?

We are building now a model using ordered logistic regression in R. I am trying to think one step ahead and am looking into possible approaches for validation. Currently we have like 800 obs ...
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881 views

Why isn't Logistic Regression called Logistic Classification?

Since Logistic Regression is a statistical classification model dealing with categorical dependent variables, why isn't it called Logistic Classification? Shouldn't the "Regression" name be reserved ...
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40 views

Checking linearity assumption of logistic regression using smoothed plot

I would like to check on the linearity assumption of my continuous variables in my logistic regression. I have produced some loess plots and I can see that they are not linear. What are the next step ...
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29 views

Logistic regression for paired comparisons

I am not a statistician; I'm an engineer, so much of this is a foreign language to me, though it seems like it wouldn't be that hard to understand if explained in a different way. I am trying to ...
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69 views

How to build a predictive model with a billion of sparse features?

I am making a model to learn a dataset which has a big feature number and sparse samples (I am planning to use logistic regression). The feature number can be as big as 1,000,000,000. It is sparse ...
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Logistic principal component regression where PCs are correlated with an additional binary predictor

My scenario is this: I collected a bunch of vegetation data (% cover counts in a quadrant at different heights) in patches where birds were seen foraging and also in control patches where no foraging ...
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Paper showing that logistic regression intercept biased in rare events

I'm studying the logistic regression for estimate the Probability of Default of SME's. Fortunately the event (firm's default) is a rare event. King and Zeng tell us that "logistic regression can ...
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Is there a way to force a relationship between coefficients in logistic regression?

I would like to specify a logistic regression model where I have the following relationship: $E[Y_i|X_i] = f(\beta x_{i1} + \beta^2x_{i2})$ where $f$ is the inverse logit function. Is there a ...