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

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How to structure dyadic data?

I have never worked with dyadic data before but need to do that now. So my question touches upon the very structure of dyadic data. The subject of the study is countries and their ties to each other....
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P>0.5 cutoff not “optimal” for logistic regression

I am not interested in the merits of using a cutoff or not, or how one should choose a cutoff. My question is purely mathematical and due to curiosity. Logistic regression models the posterior ...
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Logistic GEE Models with Extreme Class Imbalance

I have two questions Question 1: I have a longitudinal data with extreme class imbalance: 9 cases of the event of interest out of a total of 3000. I believe I have 3 options and this is the of ...
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Calibration curve for binary logistic regression model? [on hold]

I am doing an external validation of binary logistic regression model. How can I plot the calibration curve of deciles using SPSS and R ? Observed outcomes are binary (1/0) and predictive outcomes ...
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Understanding Bayesian logistic regression for binary classification

Say I scale input features: The input features get first scaled so that every input feature has a mean of 0 and a standard deviation of 0.5. (according to Gelman2008 - "A weakly informative default ...
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2answers
76 views

P>0.5 cutoff not “optimal” for logistic regression [duplicate]

PREFACE: I don't care about the merits of using a cutoff or not, or how one should choose a cutoff. My question is purely mathematical and due to curiosity. Logistic regression models the posterior ...
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0answers
21 views

FIML using Mplus

I am trying to translate some logistic regressions from SAS to Mplus. Some are fairly straightforward, e.g., no random effects, and others are mixed models with random intercepts. The example here ...
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33 views

How to compare ordered logistic nested models?

Let's say that I have a full and a restricted model that looks like this: ...
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Hosmer lemeshow test becomes significant when cut off value changes

when i am building my model in r & looking the goodness of fit test for model fitting, at .5 threshold level, my p value >.05, which tells me that my model is fitting the data well. As soon as i ...
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13 views

RMSD vs. Log-loss

I have four vectors of numbers, one is the ground truth (binary, rach number is either 1 or 0), the other three are the corresponding prediction (each number is a probability from 0 to 1) generated by ...
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20 views

Performing spatial logistic regression in R

I am trying to perform a logistic regression with the following code Y ~ x1+x2+x3,data=data, family=binomial(link="logit"). However on inspection of both ...
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18 views

Modeling an indicator variable with continuous properties

I'm trying to model auction participation for a single individual. It occurs to me that their participation is binary (yes/no), but also continuous in the 'yes' case. Any general pointers for how to ...
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Consider a linear regression model with p parameters, fitted by OLS to a set of training data $(xi , yi)$ $1≤i≤N$ [on hold]

Consider a linear regression model with p parameters, fitted by OLS to a set of trainig data ($x_i$, $y_i$), $1≤i≤N$ drawn at random from a population. Let $\hat β$ be the least squares estimate. ...
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How to estimate “partial” attribute profile choice model?

How does one estimate a choice model (McFadden MNL) on a design where there is a set of fixed attributes and a set of "variable" attributes that cycle in and out of choice sets? I believe this is ...
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44 views

Quantitatively analyzing relationships between multinomial and multiple binomial variables

I’m analyzing crowdsourced Twitter data, where workers labeled tweets. Within my dataset (N=2,400), I have one IV (call it ‘ds’) with 2 levels that differentiates which dataset the workers labeled. I ...
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1answer
16 views

What metric to use as the cross validation error in the training set for a binary classification problem?

When I am running cross validation on the training set for a binary classification problem, what metric should I use if I am only interested in obtaining the largest AUC (area under receiver operating ...
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17 views

Does a higher wald chi-square statistic indicate a better predictor?

In a logistic regression does a higher value of wald chi-square statistic mean a better predictor? I've oven noticed that it is the case. If this theory is not true can someone explain why with some ...
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Does selection of predicted vs. reference class matter in hierarchical multinomial regression?

A simplified example: There are three classes: $1$, $2$ and $3$. They have a natural order, i.e. $1<2<3$. I have a different number of observations of the classes, e.g. $1$ has been observed ...
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Logistic regression: Is there a significant difference for probability p between groups of Bernoulli random variables?

Let $S_{I+1} = \{1,2,\cdots,I\}$. And assume that there are exactly $J$ observations $(x_j,s_j) \in \mathbb{R} \times S_{I+1}$ for each integer $j$ such that $1 \leq j \leq J$. For each $i \in S_{I+1}$...
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36 views

Logistic regression with only categorical predictors

So I started off with a model which included both continuous and categorical predictor variables. But now I wanted to drop the only continuous variable (distance to shore), because to my opinion it ...
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1answer
29 views

How can standard logistic regression model fractional response variable while denominator is available?

I have X and Y variables, as well as a cluster variable (State). X and State are derived from Database A, while Y and State are derived from Database B. X is a sentiment score ranging between -1 and ...
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14 views

undersampling-unbalanced data

what are the correct steps for undersampling in classifying models? for instance if a have an unbalanced dataset with 950 non event and 50 events I will undersample creating a dataset with a 50-50% ...
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should i normalize for size? using roc-curve to compare classifiers

background: I plan to use a roc-curve to compare 4 classifiers. My data is made up of 2000 family members (x1, x2, ... x2000) and each member is part of a family of a certain size (y1,y2...y215). ...
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Getting the intuition behind the GEE for logistic regression( concepts and equations)

I need to run a logistic regression but my data are clustered. What should I do? Should I run a GEE? If so could you please suggest an excellent book on this topic which gives a good intuition on ...
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Understanding complete separation for logistic regression

Why does logistic regression not converge for a linearly separable data set? For linear separable data sets the model parameters go to infinity when mimizing the error function (according to ...
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How to deal with categorical target variable that has more categories in prediction than training?

I'm building a logistic regression model and found out that with my categorial target variable there are more categories in my prediction set than my training set. To be clearer: In e.g. my training ...
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Non-parametric estimation of error distribution in regression

Consider the following model: $y = 1$ if $g(X\beta) + u > 0$ and $y=0$ otherwise where $u$ is $iid$ according to some distribution function $F$. I want to recover the distribution $F$ without ...
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Logistic regression model: remodelling significant vars only

I did a logistic regression on 8 vars (continuous & categorical) with stepwise selection, 4 vars came up significant. I then remodelled using only those 4 vars and 3/4 became insignificant. Why so?...
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21 views

How to reduce variables in logistic regression?

I am running a logistic regression to predict Yes/No. I have more than 200 independent variables. I have tried to input all the variables, the result is terrible. It is obvious that one variable will ...
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15 views

Hosmer Lemeshow test dependent on cut off value?

when i am building my model in r & looking the goodness of fit test for model fitting, at .5 threshold level, my p value >.05, which tells me that my model is fitting the data well. As soon as i ...
0
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0answers
7 views

what should be validation parameter for Logistic Regression(LR) in online learning plus rare event scenario?

We have been following below paper to predict CTR( Click probability) of different ad items. This will be used to serve different ads based on probability values. http://olivier.chapelle.cc/pub/...
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Using Monte Carlo simulations with subsequent element removal

I'm attempting to build an evaluation set for a logistic regression classifier and I've run into a statistical problem. The study involves a very large population (G) that has two properties of ...
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Is logistic regression a valid way of analyzing A/B testing results?

I'm very new to the idea of A/B testing and I want to see if my train of thought here makes sense. Suppose that I run an experiment with two designs. I get two sets of resulting data, one for each ...
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Critique on my Logistic Regression?

I've created a multivariate binary logistic regression web app using shiny and R for one of my final projects of the semester. I would like a little critique on it and would love to learn more of just ...
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39 views

Book about generalized linear models [duplicate]

Does anyone know a good book about generalized linear models. I am a practitioner and need to master the concepts of generalized linear model, but also my experience tells me that knowing about the ...
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Data under detection limits for regressors in logistic regression

How could I handle left censored data (under detection limits) in a variable that I want to use as a regressor in logistic regression? What's is the best approach?
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1answer
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Reporting Logistic Regressions in APA

I am trying to figure out the best way to report the results of a logistic regression in an APA paper. My understanding is that the odds ratio is the most important for interpretation so I don't ...
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How can I calulate predicted mean of variable x1 from this model

Final Analysis of BDHS model ...
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Simple random sampling - No natural strata

I have data from surveys given out to visitors to a branch of my organization. A random sampling of these visitors without regards to any strata was used to determine who gets the survey. Given that ...
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Repeat measures with missing data

Need guidance: I have repeat measures (5 successive measurements) of symptoms (categorical) & labs (continuous). N=809 patients. Outcome var is 1. composite outcome (sum of complications) ...
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a question about solving logistic regression

While studying the slides [Link] (https://www.dropbox.com/s/rdwzjjah9f2mb2j/Logistic%20Regression%20to%20ILRS.pdf?dl=0) on logistic regression, I faced a question. In slide 15 and 16 it is stated ...
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Is having more features definitely equal to having a higher chance of overfitting?

I am doing a EEG data classification problem. Currently I am using the ANOVA test to help me select K best input features (with K a parameter to tune) and feeding the selected features into a logistic ...
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Does “Log loss” refer to Logarithmic loss or Logistic loss?

I know I've seen it both ways, so is there a difference between the two, and which one is more commonly referred to?
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1answer
40 views

Data Transformation Needed for Logistic Regression?

I'm planning to do logistic regression with my dependent variable as either with injury or no injury with one of my independent variables as average computer use. I have attached a sample ...
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Supervised Binary classification with numerical and text data

I have dataset in which some features take numerical values and some features take only arbitrary text(note that it is not categorical in nature). Each row has a target of 0 or 1. How would I apply ...
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Logistic regression: high proportion of events

I am trying to calculate a priori sample size for a bivariate logistic regression with 9 covariates (some categorical; some continuous). My problem is that I have a high proportion of events to non-...
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1answer
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polr not matching contingency table results

I am trying to tie the odds ratio from a 2x2 cross classification table to the intercepts of a logistic regression on those 2 variables. I have a cross classification table that produces 2 odds ratios ...
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4answers
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How to increase the accuracy of my logistic regression model?

I am dealing with a tricky, unbalanced data set and trying to run a logistic regression model. One class is present with a 10:1 ratio. My objective here is to boost my predictive accuracy - minimize ...
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Is multinomial logistic regression appropriate for a dataset containing categorical data with small cell counts?

I'm analysing a large dataset from a questionnaire with 560 respondents. A cluster analysis performed based on coded free-text data resulted in 11 mutually exclusive clusters. Based on explanatory ...